AI50 Connect
Hanh Brown
AI50 navigates the forefront of technology, delving into the nuances of artificial intelligence, especially focusing on Microsoft's Fabric and Azure AI platforms. Each episode illuminates the latest in scientific innovation, with a special lens on how these advancements interface with the aging population
We unravel the complexities of AI and technology's role in society, providing deep insights and thoughtful analysis. Join us as we explore the ever-changing world of technology, unveiling its profound effects on our daily lives and the broader societal canvas, encapsulating the marvels and intricacies of our digital era.
Recent Episodes - Season 5
Sean: 00:00:05
I think nowadays we are in a golden age. This will potentially cause a paradigm shift in drug discovery and development. And also there's not just an efficiency gain, but also a new insight gain. So for example, when we're designing our new molecules, now we can use those kind of generative AI methods to design brand new molecules with designed properties that never existed before.
Hanh: 00:00:33
Hello, I'm Hanh Brown. Welcome to AI50, where we harness the power of AI to create innovative solutions for the 50 plus demographic and their loved ones. Our mission is to develop cutting edge language model applications to cater to the unique needs and preferences of older adults and their parents and grandparents. Whether you're part of the 50 plus community or have aging family members, Our goal is to ensure that everyone benefits from advancements in the AI technology. So join us as we explore AI's
Hanh: 00:01:08
potential to revolutionize the way we live, learn, and connect. So I'm thrilled today to introduce our guest, Dr. (Sean) Liu, a pioneering leader in AI and data science at Novartis, a global healthcare powerhouse. Well, imagine struggling with a complex, life altering disease, desperate for effective treatments and hope for the future. Well, that's where Dr. Liu's groundbreaking work comes in. With his expertise in AI and data science, he's revolutionizing pharmaceutical
Hanh: 00:01:47
research and development, accelerating the discovery of innovative medicines across multiple therapeutic areas. Including cancer, cardiovascular diseases, and rare disorders. So today, we'll dive deep into Dr. Liu's inspiring journey, the challenges of integrating AI into pharmaceutical research, and the ethical considerations surrounding these cutting edge technologies. We'll also explore the lessons he's learned from his SBIR awarded data mining research. And his vision for the future of AI
Hanh: 00:02:20
in patient, in shaping patient care. So, Dr. Liu, welcome to the show. Thank you, HaHanhthank you for having me. Yeah. Well, thank you. Thank you so much. So, can you share something about yourself that maybe not too many people might know?
Sean: 00:02:41
Yeah. I'm glad to talk about AI Infirmary, uh, my personal experiences and my views. Uh, as a standard disclaimers abuse mine, not the company. So, uh, I have background in engineering and computer science. I got my Ph. D. Information science from the University of Pittsburgh. So when I was looking my Ph. D. Research topics, I look at a long list. And eventually bioinformatics
Sean: 00:03:07
touched me because from early age, I know that biology and medicine could improve human health. But I thought it's mainly conducted through experiments. While I am not very hands on and not a handyman. So I thought it's kind of a little bit challenging for me. But then I realized that, uh, using compute computing computational methods, we could also unlock a lot of insights in biology and medicine. And suddenly that widened my eyes. So I decided to I want to focus on this
Sean: 00:03:40
because it can give my work more grand meaning of which is improving health. And after that, I went to postdoctoral training in bioinformatics at Johns Hopkins University, so where I learned gene, Uh, regulation and, uh, how genes are expressed in different human tissues and that relevance to, uh, uh, human diseases. Um, and then, uh, I went to a small ai, uh, tech company called, uh, intelligent Automation in Maryland, DC area. Uh, so, uh, it is, it, it was there that I transitioned from, uh, a student, uh, a post-doctor fellow to an, uh,
Sean: 00:04:21
independent principal investigator. Um, so I, uh. Uh, what was applying, uh, um, the small business innovation of grounds, uh, with the government government agencies and also conduct research in, uh, data mining, but also with applications in biomedical, uh, uh, area. Then, uh, I thought I could, um, continue doing this until I got an opportunity to join Eli Lilly and the company. Uh, so my years at Lilly, uh, have, uh, two parts. Uh, the first is with the, uh, research IT and, um, Research,
Sean: 00:05:00
uh, informatics, uh, department. And second part is, uh, with the, uh, enterprise level, uh, data science center. So, uh, and the, um, and this happened, uh, coincide with the, um, the uprising of AI and deep learning. That's around, uh, 20, uh, 17, 20 18. Uh, because, uh, AI was, uh, catching. Everybody's attention. Every industry and leaders, they want to invest and see how that improves their productivity. Uh, and I was glad I have. I was being able to witness the whole transition process that how is getting,
Sean: 00:05:38
um, um, prevalent and how people are using that to show its value and benefits to, um, health care to patients to a lot of other, uh, important social issues. Awesome. Yeah. And then, uh, my, uh, now I'm, uh, with, uh, Novartis and also, uh, working on data and AI to, uh, enhance, uh, drug discovery and clinical trials. Uh, so I'm, uh, quite happy I have the opportunity to use data and AI to, uh, help the industry and, uh, eventually, uh, patients and healthcare.
Hanh: 00:06:12
Absolutely. Such important work. And I appreciate it. Your work that you do now. A recent study by Accenture suggests that AI has a potential to revolutionize the pharmaceutical industry with an estimated 150 billion in savings by 2026. So what inspired you to pursue AI and data science? And I know you've touched on it previously. Was there a particular experience or realization that motivated you?
Sean: 00:06:42
Yeah. Um, so, uh, interestingly, uh, I have been in the whole, uh, um, journey that, uh, how AI, you know, got, uh, revived, uh, and, uh, now got, uh, you know, such a key component in R& D. Uh, you know, in the, uh, 1980s, uh, AI, uh, there was a movement in AI, uh, especially, uh, in the robotics. And then, uh, when it goes to 2000s and then that's when the Internet and becomes popular. So a lot of, um, people still do, uh, machine learning this kind of research. But, uh, at that moment, uh, the data
Sean: 00:07:17
maybe is, uh, not that big enough. And also the computing power is not that big enough. And probably applications were not abundant at that time. And people usually call that data mining. Thanks. And text mining, uh, image processing, image analytics. And people really call that AI. Maybe people call that a machine learning, but the AI itself was not frequently used. And then when we get in the, um, around the, uh, the early, uh, 2010s, and then the rise of deep learning image processing
Sean: 00:07:51
then suddenly ignite the revolution. And then when we get into the middle of 2010s, then, um, the rise of deep learning and also especially the introduction of the transformer models that totally changed the whole game. Previously, we talked about AI, it's about, it's more about traditional models, about, uh, Logistic regression decision trees. But after the introduction of the transformer and those deep learning models, then it constantly means a different thing. So it means like more computing power
Sean: 00:08:27
and more better pattern recognizer from a gigantic amount of data. To enable insights, discovery to improve efficiency and also even introduce the shift of paradigm. So in the farmer, what inspires me is that there is being a long decades of challenge. We all know that people often see that it takes over 10 years and a billion dollars to launch a new medicine. And now the numbers have been updated. People have been saying it actually takes more than 13 years and the 2. 8 billion to launch medicine.
Sean: 00:09:07
And the success rate is relatively low, is around 10 percent from the beginning to launch. Then people have been thinking how we could improve the R and D. Process the productivity in farmer. Um, there are many people have been looking at from many different perspectives from experimental perspectives and also computing perspectives. And now is the rise of AI. Obviously, we all think, uh, you know how I could improve. So in my view, I could have every
Sean: 00:09:36
aspect of the pharmaceutical R and D. Uh, including the early discovery, clinical trials and real world evidence. So, um, um, yeah, so there's a lot of, uh, uh, contents to cover, but let me just, uh, elaborate a little bit. So, for example, in early discovery. Very important task is about finding targets, designing molecules, and so that we can move to the clinical trials and testing on patients to see the safety and efficacy. So previously, when people are finding the novel targets, they usually go to the literature and also doing bioinformatics
Sean: 00:10:17
analysis of gene expression data, etc. for your attention. to manually put together all kinds of evidence. They can make a decision so you can think that, you know, PubMed has millions of articles and it's really hard for people to digest them and then a new content keeps popping up. So with the natural language processing, it is possible to digest this huge literature and generate precise gene disease and drug relationships so that people can navigate among this kind of information networks
Sean: 00:10:56
to tailor to their hypothesis generation and therapeutic needs. Uh, and also, um, Uh, we'd go. Uh, and also there's, uh, not just, uh, uh, efficiency gain, but also, uh, in a new insight gain. So, for example, um, when we designing our new molecules, uh, now we can use, uh, uh, those kind of, uh, generative AI methods, uh, to design brand new molecules, uh, these, uh, desired properties, uh, that never existed before. Um, and also, um, more recently. Some AI based biotech companies are pushing the, um, AI design molecules
Sean: 00:11:36
against AI predicted targets into clinical trials, and it's been going on quite well, and some molecules have already entered into a phase one or phase two clinical trials. And, uh, if successful, this will prove that it is possible to use data and AI, uh, to reduce costs and budget and speed up the efficiency in pharmaceutical, uh, development. And this is, um, and any of this is successful and more companies, uh, will do the same. And this will potentially cause a paradigm shift, uh, in drug
Sean: 00:12:10
discovery and development. So these are all the exciting things that, uh, motivate me. Um, to come up, work and, uh, every day and communicate with people and, uh, also, uh, make my own, uh, contribution to the field. Yeah,
Hanh: 00:12:23
It's a, it's a great time to be doing work in all regards, you know, in the realm of AI, uh, gosh, customer service, productivity, creativity. Life long learning. So I concur with everything you're saying. Now, integrating AI and machine learning into pharmaceutical research can present numerous challenges. So what have been some of the biggest challenges? And how have you approached and overcoming them?
Sean: 00:12:56
Yeah, um, That's a great question. So definitely there are many, many challenges. So for me, I like to categorize them into two parts. One is about the technology stack. The second is about business use cases and applications. So for the business stack, if we further break them down, it includes data algorithms and platforms. You know, in order for AI to work, Uh, we definitely need a lot of data to cover the knowledge space because, uh, you know, these are the mathematical
Sean: 00:13:27
and, uh, statistical algorithms. They need data to learn what is the, uh, the popular, what is the sample space look like? So, so that way it can generalize into a model and predict new things, given a new inputs. So, um, the data are challenge is obvious, right? I mean, data are desperate and, uh, uh, distributed across different, uh, areas. And also it could, um, you know, coming from, uh, inside, uh, different organizations and it could, uh, coming from the, uh,
Sean: 00:13:57
the public, uh, the open space. Now, how do we harmonize all those datas in a standard format that can fit into, uh, AI models? That's definitely a big challenge, right? Uh, and when it goes to, uh, algorithms. You know, we are all motivated that I can do so many things, but, um, the reality is that, uh, no, uh, no algorithms is 100%. We need a lot of, uh, training, validation and testing to see the performance. We always need a new algorithms to improve the performance. So that way we can make models more practical.
Sean: 00:14:29
in reality. And when it goes to platforms, there are many computing platforms supporting the data storage, supporting the GPU computing, model training, testing and also deployment. So definitely there's a lot of challenges there. Um, and when it goes to the assuming we have worked hard and have all the things in place. The next thing, how can we Turns this, uh, uh, the whole technology stack into, uh, innovative medicines to patients, uh, to help with patients.
Sean: 00:14:58
Then this goes to, uh, very different, uh, disease areas and, uh, the unmet medical needs, uh, and how we define the priorities, uh, what kind of AI models we want to do first. So there's a lot of challenges and concerns there. So, um, yeah, but the, uh, you know, accompanying the challenge also opportunities and excitement. So I think I'm glad to embrace both challenge and opportunities. Yeah.
Hanh: 00:15:24
So now, uh, do you use AI systems such as Azure AI and Fabric to ingest the data or do you have your own at Novartis?
Sean: 00:15:35
Yeah, that's good question. Uh, so, um, you know, um, nowadays, uh, the farmer, uh, industry, now they have a lot of collaborations with those tech companies. So, uh, so it is not uncommon that we use Azure. We use AWS, et cetera. Um, but I would say I would like to embrace the idea of agility. Right? Uh, because many times, uh, our new goal is to build a models useful for decision making, uh, in making new medicines in helping patients.
Sean: 00:16:06
Right. So, um, Many times we start, uh, from the, uh, exploration, uh, at that stage, it does not need a lot of, um, you know, rigorous, uh, computing power, uh, et cetera. We can even, uh, start with, uh, on h HPCs, right? So, uh, so, so for me, um, then, um, I would say nowadays the, uh, the choices of infrastructure, uh, uh, is a lot right? Then, uh, then it's really, uh, depends on the business needs and the cost, budget, uh, et cetera.
Hanh: 00:16:35
Very true. I'm finding out that many companies, whether they're small, midsize or, you know, fortune 500, they're looking for AI systems and not just models because to ultimate, to reap the full benefits of AI is to have an ecosystem that speak to each other, right? So that we don't have various plugins and various operating systems. So, now as AI becomes more prevalent in healthcare, ethical considerations become increasingly important. Now, what do you see as the key ethical considerations surrounding
Hanh: 00:17:10
the use of AI in healthcare? And how do we ensure that these technologies are developed and used responsibly?
Sean: 00:17:19
Yeah, that's an excellent topic and I have a lot of fundamental issues there. So, um, So to me, I think if we think about from the patient's perspective, right, there's a lot of a patient privacy issue. Uh, there is the when it goes to a modeling, there's a buyers that could be biased in data and models, right? And also when we go to the clinical studies, uh, there's also a bias, uh, in the, uh, selecting patients, uh, participating in, uh, clinical trials. And also nowadays we are in the digital, uh, world, uh, the digital health
Sean: 00:17:53
is, uh, booming and is supporting, uh, patients, uh, in the real life and also in, uh, clinical trials. Then, um, how does the results communicate transparently to patients, uh, to those investigators and of course, not just to AI modelers, right? So these are the fundamental issues. Um, so, um, so for privacy, uh, I think, uh, the data, um, you're, you know, uh, we all know in healthcare, the patient data is, uh, De identified and anomalized, right? There's already material computer science algorithms systems for doing that.
Sean: 00:18:30
So we definitely to adopt this kind of technologies to make sure we do not leak personal private information. And also, when it goes to our models, when we select samples, then there's a lot of considerations about the human demographics. And how do we ensure that uh, The air models are inclusive, cover data points from different, uh, patient groups, uh, and separate populations. Uh, so that's a fundamental issue that we have to deal with when we do data gathering, uh, cleaning, uh, pre processing, and also when we do a model
Sean: 00:19:05
evaluation, uh, testing on, uh, you know, different, uh, patient groups. So these are the things that we have to, uh, go through, uh, definitely. And, um, uh, Uh, for clinical trials, uh, is similar things right now. How do we ensure that, um, you know, more patient populations, uh, different disease areas, different ethnic groups, different geographic regions, they could all participate to help test the safety and efficacy of the drugs because eventually the drugs when they approve, they will go to a much larger population. And, uh, so that's how, how
Sean: 00:19:39
do we, you know, create more. You know, robust, uh, results, uh, in the, even in the discovery and, uh, uh, clinical development, uh, process, we need a lot of, uh, involvement, uh, from different perspectives, uh, of the patients. Mm-Hmm. Uh, and, uh, and, and also, um, uh, we goes to the, uh, transparency, uh, communication. Uh, I think interestingly, uh, recently, uh, FDA has, uh, a guidance, uh, uh, in the, uh, about AI in medical devices. Uh, it, it was saying that,
Sean: 00:20:08
uh, the, uh, the results of. predictions from models, whether it's about the health outcomes and adverse events. So those things should be transparent across to all the stakeholders involved, which meaning including patients. Uh, investigators, uh, the AI modelers and, uh, abusing these people, uh, et cetera. So, um, uh, so I'm glad that, uh, you know, the field, uh, is starting to realize, uh, the importance, uh, that, uh, we should, uh, using AI to build, uh, abuse, uh, build trustworthy ai, we
Sean: 00:20:37
should, uh, you know, uh, be transparent and also engage the, uh, the end users. Mm-Hmm. , uh, in the process. So, so that we have more confidence about what AI. Uh, is working and what is not working currently and how can we, uh, find ways to make, uh, work even better? Yeah.
Hanh: 00:20:57
So true. Consumer focus. And include them in the, uh, upstream feedback. So that's awesome. So now you have received an SBIR awards for your data mining research. Uh, the small business innovation research program has been very instrumental in supporting cutting edge research in various fields. With over 43 billion in awards granted since its inception. Now, what lessons have you learned from your SBIR awarded data mining research,
Hanh: 00:21:28
um, that you think could be valuable for other researchers in the field?
Sean: 00:21:34
Yeah, I love this topic. So, um, as mentioned, um, When I was trans, trans, transitioning from a student to an investigator, I've gone through the whole process, how to apply, uh, the, uh, the grants, uh, from the government agencies. It's very much like, uh, the pitch to, uh, venture capitals, uh, for nowadays, uh, biotech companies, right? So, um, so to me, uh, there are some, uh, key elements that I learned. Uh, the first, uh, is to have the, uh, you know, the right teaming and then right technology, and then
Sean: 00:22:03
right, uh, um, objectives and tasks. And also eventually the right commercialization, uh, commercialization strategies. So, uh, so for example, um, you know, uh, there's a constant opportunities out there, uh, calling for proposals, uh, from government agencies, uh, from state, uh, agencies, from, uh, venture capitals, uh, et cetera. So, uh, then how do we, uh, grasp those opportunities? And the first, of course, uh, I mean, there should be a match of, uh, expertise and interest, right?
Sean: 00:22:33
And we select, uh, in the topics of example, a data mining in health care or data mining in social media analytics in psychology in human behaviors, right? We identify those solicitations, of course, and then once we have that, we should forming a strong, very strong team because, you know, the SBIR and any other grant applications, they need a very comprehensive views to cover the whole team. are the challenges, right? I mean, one or two teams or want to in the persons or individuals, they cannot do that.
Sean: 00:23:04
Definitely. So, uh, so what I learned is that, uh, yes, I realized I do have a lot of strength and I do have a lot of weaknesses, right? Uh, in real, in this kind of realization, and I, uh, I, I learned how to identify, you know, potential collaborators. You know, there's a lot of work to do networking, right? And when you show people, there's a grand opportunity to foreground. And if it happens to, um, you know, reside in a person's expertise, they're really very happy to participate, right?
Sean: 00:23:35
So because that's going to be a women's situation. So from this way, you need to identify What is missing, right? Because, um, you know, we talked about again, the technology stack, the data algorithm platform, you know, anything you're missing, you should be able to find someone who can back it up for you, right? Experts in the field. And once you got those kind of very strong points, elements you put together, it's time to cook a very nice proposal, then, uh, then, you know, we have to plug in the right technologies and in ground
Sean: 00:24:04
writing, you know, there's a way we have to, um, Um, describe the overarching goal on the list of business goals. And on each, um, a goal, we have to have a very detailed tasks, right? And then, you know, so basically, it's kind of a framework, right? We definitely need a framework. I mean, I mean, most founders, they wouldn't like those kind of ad hoc studies. They need a framework. Systematic frameworks that was a long term investment, meaning like you set up the infrastructure, you set up initial
Sean: 00:24:40
success of use cases and you keep adding new features, new use cases to that right? And also this is not sufficient because eventually we have to turn technology into impact, right? Then that needs a lot of, uh, you know, the business side development, the commercialization strategies, right? And, of course, for small companies, there's a lot of limited resources. Usually we have to partner with those bigger, larger organizations to do the commercialization. We show them our current technology and what is coming and see, you
Sean: 00:25:18
know, is that, you know, aligned with their, um You know, portfolios and the willing to, you know, looking to our technologies and collaborate and help and co develop the technologies, right? So, yeah, so it's quite important to find the commercialization strategies. So, given that all I think is quite exciting field, and I do encourage people to grasp those kind of opportunities, or at least think about that.
Hanh: 00:25:42
Mm hmm. Mm hmm. Well, I certainly have. Maybe we can talk about that afterwards. But, you know, with the advancement of AI, AI agents, and this whole ecosystem that you and I talk, How, what impact does that have in, um, putting together a team, uh, because a lot of the team members that we thought of was once important to have, can some of that be done or enhanced, um, through AI? What is your take on that?
Sean: 00:26:15
Yeah, so the teaming, um, So, yeah, you know, uh, I would say, uh, so, um, a I as a technology is definitely a fancy and then it relates to the business goals, whether we really want to get out of the business, right? That's business school. And also another quite important question. Part is a collaboration, right? As I just mentioned, you know how you put strength of people and forming a strong proposal, a strong program. So, um, I thought, uh, in in nowadays in AI technologies, they could not. I mean, those concepts are amazing.
Sean: 00:26:53
So, uh, I could find opportunity to collaborations and even through different ways of networking. I mean. There are so many ways that AI people, business people, um, by their industry or academic, uh, they can come together and, uh, you know, forming, uh, a team. And, uh, and, and, and again, I like the agility because I do believe, uh, the true scientists, they're coming from the, uh, the bottom up way, like from, uh, the, the front tier scientists who have been thinking this constantly and from experimentalists
Sean: 00:27:24
who've been doing the, uh, doing the experiments, generating data. Uh, things like that. So that maybe also need to formulate a cultural and also a welcoming environment to facilitate this kind of collaboration. So there's a lot of, uh, aspects. I mean, we can talk a lot. Yeah, it depends on the
Hanh: 00:27:47
people's angles, interests. Yeah, that's true. So AI and data science are poised to shape the future of health care and patient care. So now looking ahead, what excites you the most about the potential of AI and the data science to transform? Uh, patient care. And what do you think will be the biggest areas of impact?
Sean: 00:28:09
Yeah, yeah, this is a great question. So, you know, the ultimate goal is of health care and, uh, you know, farmer is to help with patients, right? So I think nowadays we are in a golden age. So, so for example, um, as mentioned, uh, like digital health can bring a lot of, um, medical devices. Uh, at home or your day to day work on your journey, right to help monitoring your health status and also the advance of biotechnologies, all kinds of omics that could potentially give us more
Sean: 00:28:41
insights into the reality of what is happening in different populations, different, different patient groups so that we can enable, uh, better Precise tailored medicines for different patients. So, um, and and also, uh, there's a very good timing, you know, especially through the pandemic. We all realize the health is quite important to our families to society. Then it's also good timing for the health care health educations through AI. There's a lot of learning. Uh, out there, uh, either on podcast or on the, uh, the article, social media
Sean: 00:29:22
and, uh, or, uh, seminars, people talking about, you know, all kinds of ways, how do we, uh, improve health because, uh, fundamentally, uh, I, you know, humans, uh, you know, we have, uh, our, uh, bodies that doing magic every day. But, uh, you know, there's so little, we really know what's really going on in the human body, in the tissues, in the, uh, cells and in DNAs, uh, and in cell division, uh, you know. you know, this kind of things. So, um, so I think it's quite important using this time using a I to You
Sean: 00:29:54
know, further increase the social awareness of this health issues. So then how human bodies works, what kind of food. Environment are good to our bodies, right? And so that way we can, you know, have the whole population society to be aware of this thing so that we can reduce the chance of having serious disease in the beginning, right? Um, and of course, things happens. Things are not working as expected. There could be gene mutations. There could be. You know, all kinds of ways aging, right?
Sean: 00:30:28
And these are all kinds of things could make us sick and sometimes getting into serious diseases. Then fortunately, then that's how farmer and health care are coming to help, right? So we develop those innovative medicines in case people we get into those very difficult medical situations. So there are still a lot of technology ways to do that. So I would say, think about this, uh, uh, now this, uh, AI, uh, booming age, uh, there's all kinds of ways, uh, that we could help with patients. And for patients themselves,
Sean: 00:31:02
they have all kinds of ways to, you know, engage the community, engage research, uh, researchers. And I'm glad, uh, all the, uh, the few that realize, uh, patient centric is, uh, uh, It's a huge, right, the way we all should be, uh, doing that. Yeah.
Hanh: 00:31:18
So true. There is no better time to, uh, with the available resources, um, guidance to have healthy aging, right? Yes. Um, there's abundance and what a great time to embrace the AI, um, to enhance your lives and longevity and with the tools and resources out there. Uh, even this conversation, for instance. So oh, it's great. Yeah. Yeah. Young researchers in AI and healthcare can benefit from the wisdom of
Hanh: 00:31:53
experienced professionals like yourself. Now, the World Economic Forum emphasized the importance of mentorship and knowledge sharing in fostering the next generation of AI talent. So now, what advice would you offer to young researchers looking to make an impact in the field of AI and healthcare?
Sean: 00:32:12
Yeah, this is my favorite topic, uh, because my, uh, I have my, uh, nephews, uh, entering college and were seeking advice from me. So I realize, uh, for nowadays, uh, young people, they, uh, kind of feel excited about AI, about other technologies, about, uh, healthcare. care, et cetera, but they are at the same time are kind of puzzled and and also I frequently I chat with graduate students before they graduate, I mean how to select your PhD topics and after you graduate, where do you go and you know how to jumpstart your career, so So I
Sean: 00:32:41
was recording on my own experiences, so I was thinking, uh, the key is to finding your passion and your strength, right? Uh, the passion, you may have a lot of interest, but what is your true passion? The only way to tell is to, you know, try that, right? Try that out. For example, for my PhD, uh, topics, I, I tried a bunch, uh, so many different areas. Then I finally, I thought, oh, okay. The biomedicine touched me better, so I chose it, right? So and then also find
Sean: 00:33:13
your strengths, right? What are you good at, right? If you're good at mathematics, you can think about, you know, this kind of AI modeling, algorithm development, if I model Into the, uh, uh, interactions. Then there's, um, you know, uh, you can, uh, think about those kind of, uh, the, the healthcare, like how to help, uh, be patient, uh, advocacy, uh, those, those kind of things. And you feel, uh, strong at electronic engineering how to build medical devices to help patients, right? So yeah, you need to find strengths
Sean: 00:33:43
and your, uh, uh, uh, passion and combine them to create, um. Your own portfolio. And also, um, I'd like to like to see, uh, to say, uh, be yourself and never give up, right?
Hanh: 00:33:59
So true. Overcoming setback is crucial, a crucial part of research process. So, um, from your experience, what strategies have you been most effective in overcoming setbacks and challenges in AI and data science research?
Sean: 00:34:15
Yeah, right. So there's many aspects, right? So, so there could be business aspects, business strategy, the market process, uh, and even, uh, I mean, so I, I, my interest is made on the technology and the science perspectives. So the, uh, the setbacks or the challenges I face is that, uh, you know, You know, again, back to the technologies stack and business applications. So, um, and many times we managed to build AI methods and tools put out there for, uh, users to, um, you know, test on that. So, um, you know, you get different
Sean: 00:34:50
responses from people and some people, they instantly Find benefits and would love to collaborate with you. So these are the great right? And many times you see, uh, neutral feedback or even negative feedback saying, Oh, this is, um, making wrong predictions, making wrong recommendations. I totally lost my confidence in those systems. I would rather. Go out using Google or using some other such tools to digest myself. So, um, so these are all boils down to that.
Sean: 00:35:23
Um, you know, yes, a is capable of the data. Is there? Uh, and the algorithm is there. It may or may not be sufficient enough. Then how do we, you know, build your initial successful use cases. So this need a lot of consideration. So again, my strategy is working with experts, right? You know, you know, before I before those intelligent agents can tell you anything. You know, where can you get the most trustworthy information? Of course, it's from people
Sean: 00:35:52
based hands on experience. Those experts, they're in the field, right? So if you collaborate with them and bring your AI technologies, you can, you can, you know, what is the role of the air? Is that going to be, you know, help me finding novel things that otherwise would never be always simply help me to prioritize things, right? So, so I would say Especially when we talk about a I lending in business cases. The key is that, um, also understanding the requirements and needs of the stakeholders.
Sean: 00:36:25
What are their real pain points? Maybe everybody thought, Oh, I is could have. That's true. But it's too general. What is the specifics? Right? Maybe once we understand those scenarios, having those kind of conversations, we It's like a diagnosis, right? We will know, okay, where's the pain points? Where AI can play? Where the existing data, existing models can, you know, help with?
Sean: 00:36:50
Then, what comes first?
Hanh: 00:36:51
Absolutely. It's not a silver bullet solution. I see it as, um, a GPS. It drives us. It uncovers insights. But we're the driver, right? We're the driver. Um, so, so we need to, I guess, provided quality data and make decisions from the insights that, that it gives us, but ultimately we provided input and we make decisions based from the AI insights.
Sean: 00:37:18
Yeah. Yeah. AI needs to be in the right hand.
Hanh: 00:37:22
Absolutely. And then in terms of, um, the use of AI, you know, this is what I always say to folks, you know, first and foremost, um, understand your, Your process. What are your pain points like you mentioned? Where do you see, um, the most nuisance or repetitive tasks? Or what is it that you want to remove from your day to day work so that you can get to the heart of your work? So then we'll focus on those pain points, you know, so because it's not a silver bullet for everything.
Sean: 00:37:54
So true.
Hanh: 00:37:55
Yeah. So now how do you cultivate a culture of innovation and collaboration with within your AI and data science teams?
Sean: 00:38:05
Yeah. So there's many different ways, right? There's some sometimes there's a bigger, uh, company level of initiatives. So these are kind of, uh, assigned, uh, You know, groups, they're working together, right? Then, of course, your social among those different groups. And among those groups, you can identify people that you have your best fit of interest and strength. And then you can pilot your studies, right? Build your own models.
Sean: 00:38:31
Show its significance, right? Show its accuracy. Show how it could be used in the business processes. So, uh, it's like making friends, right, in the open world, right? I mean, we all love to make friends, but you cannot make friends with everybody, right? In a research scenario, it's the same thing, right? Because the key is that everybody's goal is the same, is we need to have the win win situation, right? We have, you know, one plus one
Sean: 00:38:54
is much greater than two, right? I mean, everybody's looking for that. So, if we set up those kind of tone, and the people know that, and the people can bring their own ones into the table. Then it's very good timing to cook a lot of fancy things, fancy foods, and that will be much greater than two. So I would say, uh, be, you know, be open, be ready and, uh, you know, be proactive to find those opportunities and making our connections. Yeah.
Hanh: 00:39:24
Very true. So what role, uh, do strategic partnerships play in advancing AI and data solutions in health care and how? How can organizations effectively foster these collaborations?
Sean: 00:39:37
Yeah, I think that's so a big topic and so such an important one. Um, I can only share my personal views. So, so the strategy, usually, to me is aligned with the business development. I mean, if a farmer, every farmer, they have their own portfolios of disease areas, their own molecules, their own clinical trials, et cetera. Right, then, then this usually coming from, you know, the business, um, You know, assessment. What is the short term near term goals of the companies? And then the technology is
Sean: 00:40:12
kind of, um, go afterwards. And sometimes I see technology can go ahead. You don't have, like people say, uh, AI driven, AI based biotech companies. They purely work on AI predict targets. molecules. That's so true. But that's kind of can be afford as this environment by those very small companies, right? Because bigger companies that have many more resources, a lot of expertise, right? We never want to, you know, bypass those kind of resource and expertise to pursue
Sean: 00:40:46
something in, you know, uncertain way. So, um, So So how do we form the strategy? I think there's different levels, right? There's a company level. And even like in the farmer field, I saw a lot of alliances. Companies, they come together, share their, uh, you know, uh, data in an uncompetitive way, like, for example, if they have this kind of early discovery molecules about this data, what works and what not works, there's a concessions like by some farmers. They do share, of course, those kind of early discovery data.
Sean: 00:41:21
Uh, and also, you know, government level, of course, and FDA is carefully watching how AI field is, um, progressing and constantly updating their guidance. Uh, and, uh, and when it goes, uh, yeah, then we go back to the inside the organizations are different teams than the strategies. So again, I think, uh, we are all limited by resources, cost, time, budget, et cetera. But now, how do we. Uh, create a winning business cases. Then again, I think this depends on the people, right?
Sean: 00:41:53
I mean, we have to bring together the right people, the right expertise addressing the right business questions. So that way we can get a handle. And, uh, we can show, uh, our early success, broadcast, uh, broadcast success so that way we can attract more people to join the journey and eventually, you know, can improve the, uh, efficiency for the whole industry. And then, you know, there's definitely, uh, we are in a time of revolution. I can see. Yeah.
Hanh: 00:42:22
Absolutely. And many, um, many folks are still. Going through the paradigm shift, it's necessary, but, um, the time is now just don't wait too long. Right? Because I think consumers are getting really smart. Um, they're going to expect AI integration, whether it's in their customer service, information provided to them, um, so that they're armed and equipped to make decisions, whether or not to use your service or products. So it's really, um, empowering
Hanh: 00:42:51
the consumers, the patients. And, um, I think that's key. Um, with the advancement of AI, I think consumers are going to expect that. Yes. So now balancing innovation with patient safety and privacy is a crucial consideration in healthcare AI. So as AI continues to advance in healthcare, how do we strike the right balance between driving innovation And, um, ensuring patient safety and privacy?
Sean: 00:43:27
Yeah, excellent topic. So, um, you know, ePharma, right? I mean, we all know the goal of the clinical trials is to test the efficiency, uh, sorry, the efficacy and safety in patients, right? So, um, I would say, uh, there's many, uh, different angles. Right. Uh, and, um, and nowadays, uh, I think the, the, the, these are all coming from the unmet medical needs. And sometimes there's a new, no treatment for a certain disease. And sometimes there's, uh.
Sean: 00:44:01
There are marketed drugs for indications disease, but there's a drug resistance issues, um, toxicity issues that we have to constantly looking for new targets, new molecules, uh, to, you know, address those, uh, medical needs, um, and, and during this, uh, process, you know, um, so there's a lot of, uh, considerations, I would say, um, Uh, it again. I would like to introduce the emphasize the importance of patient centric way, right? Because, uh, nowadays when we previously I mean, it's purely like the develop the R. N.
Sean: 00:44:44
D. Separate from the patients. I mean, when it gets to the patients, it's the drugs already on the market and prescribed by the doctors. And nowadays, um, innovative companies, they are engaged. The patient voices in the very beginning, like, uh, Because one target, one molecule could work for some population, but for specific patient populations with different biomarkers, different mutations, their, you know, their safety profiles and ethics profiles will differ. Now, how do we engage those
Sean: 00:45:12
patient voices, doctors voices into the very beginning? Uh, that's, uh, I think that's a field, uh, is, uh, uh, like, uh, Working on and, um, and of course, uh, we talk about the safety issues that's unavoidable, right? And because medications, um, they get into the body and, uh, usually they, I mean, many, most of the time they have, uh, onto the tachys, those drugs, they bind to these, uh, uh, the genes, uh, to achieve therapeutic, uh, proteins to achieve, uh, therapeutic effects, but sometimes there could be. Off topic issues.
Sean: 00:45:51
And nowadays, uh, when the society is getting, uh, aging, there is a good, a lot of, uh, drug combination issues. And, uh, some drug combinations, they were not, not, never tested before, and they could have unexpected adverse events. So this again, uh, relates to, uh, regulation and, uh, you know, reporting systems, uh, ensure that we know those adverse events and, uh, think of ways how to prevent that. Yeah.
Hanh: 00:46:15
Mm hmm. Very true. So, now, um, natural language processing has numerous potential, uh, applications in the health care. So, a recent study published in the, uh, Journal of Medicine, Medical Informatics Association, it highlighted the promise of NLP in extracting valuable insights from unstructured medical data. So, what do you believe is the most promising application of NLP in health care? And why?
Sean: 00:46:44
Oh, yeah. I love this topic because I have been working on NLP for so long. So, um, let me give some brief examples, right? So in the pharmaceutical R& D, there's a lot, definitely a lot of contextual information document, uh, uh, you know, in early discovery in clinical trials and also in real world evidence. So, uh, in early discovery, as mentioned, uh, uh, you know, researchers constantly need to return to the, turn to the, uh, literature to find, uh, novel information to, uh, help, uh,
Sean: 00:47:12
facilitate their hypothesis generation. So, uh, NLP, you know, or previously called text mining technologies, then can help you extract, uh, key information about gene disease, uh, molecules and summarize that for you. And also could potentially, uh, extract the clinical trial design and results, uh, results, uh, sections. Uh, so that way, um, clinical teams are, are, are, are, Uh, early, uh, discovery teams, they can digest this information, uh, much quickly than they manually curate this information. And a clinical trial documents is
Sean: 00:47:48
another, uh, key, um, uh, field where, uh, NLP can be applied. Uh, so, uh, a lot of, uh, protocols, a lot of, uh, clinical trial design documents, results documents, and how do we, you know, using, uh, NL, NLP, LLMs to translate that into structured information. You know, you know, very nicely, uh, format, uh, tables, um, you know, uh, and reports. So, uh, definitely, uh, there's a lot of work going on and some proven already, uh, some products are already in operation. People using that to generate those kind
Sean: 00:48:22
of, uh, uh, extraction results, reports. And when it goes to the, um, real world evidence, nowadays we use, uh, electronic health records in EHRs. There's a lot of unstructured information as well. Uh, like, uh, uh, clinical notes, uh, admission notes, discharge summaries, et cetera. So NLP can potentially use this, um, you know, uh, work on those kind of, uh, information, uh, to help predict the, uh, uh, future outcomes. And also those information could be digested and inform,
Sean: 00:48:54
uh, the, uh, clinical trials. So, uh, so these are the classical, um, applications that's already going on. Uh, and, uh, even before AI was. It's called AI nowadays, like, uh, like in 2013, 2014 times, there's a lot already kind of text mining technologies enable us to do that. Now the difference is that with deep learning and NLP, we can get even better accuracy and more flexibility, uh, because, um, you can, you can. You know, using, uh, this kind of ities, using this kind, uh, this kind of things like, uh, prompting, uh, engineering,
Sean: 00:49:26
uh, using, uh, this racks, uh, with uh mm-hmm, retrieval, augmented, uh, uh, uh, uh, the, uh, uh, generation, right? You know, those kind technologies have you give you the flexibility to, you know, interactive, uh, inactively working with models. So those are the differences. By essence, people already realize that, uh, you know, NLP could help with, uh, productivity. And also, I'd like to highlight NLP is essentially a sequence of models, right? Now we use, uh, you know, the word, uh, the, you know, documents of words and,
Sean: 00:50:02
you know, a sequence of words, right? That gives a meaning, a semantic meaning of the document. But now, uh, if we adopt. The sequence models concept, then there's a lot of things actually can be modeled as a sequence, for example, for example, image processing, right, actually, transformers can also be applied on image data. So what people do is that they can do a segmentations of the images, uh, image into, um, A list of patches and those patches is again sequential data that can input into your, uh, transformers
Sean: 00:50:33
so that you can pre training your model and finding your model, et cetera. Uh, and also, uh, excitingly, um, nowadays, we also using those kind of NLP, uh, foundation models in biology, because, um, think about that, uh, you know, just like a words. The, you know, they play together, they interact with each other to become a document. Inside our bodies, you know, the genes, the interact with each other to determine the cell states and cell, uh, cell communicated with each other to determine biology, right?
Sean: 00:51:10
So those things, if you think about that, they could also be potentially, um, transformed into, um, uh, transformer, uh, kind of pre training, um, Uh, paradigm, right? So, so, so in this sense, uh, NLP no longer, uh, because just one text model, it's become a multi model and, uh, it's, uh, goes far beyond text. Yeah.
Hanh: 00:51:34
Well, thank you. Thank you so much. So we're at the tail end of our conversation. Would you like to add anything before I close up?
Sean: 00:51:42
Oh, thank you so much for the opportunity. Um, so, uh, I would say we are in an exciting, uh, uh, area, right? With all the data technology, business applications and medical needs out there. So I think the key is to have the right execution strategy. If we can have the right strategy to put together the data, algorithms, platforms, business use cases, uh, without. Be able to significantly enhance and transform the pharmaceutical R and D and also many, many other, um, uh, societal issues.
Sean: 00:52:21
So I think, uh, and the good thing is that AI now becomes ubiquitous and everybody use GPT or things like that, right? And so, um, You know, these contrast, uh, previous years people talking about keep asking, okay, how to democratize ai. Now, people don't ask this question. The AI is already in your hands, right? So now I do encourage, uh, people to grasp that whether you are, um, uh, tech, uh, technicians or, or technologists or you biologists or you have patients, you will find, uh, the benefits of the ai, uh, uh, from here and there sooner later. So I encourage empathy,
Sean: 00:52:57
embrace this kind of culture. Yeah. Thank you so much.
Hanh: 00:53:01
Well, Dr. Liu, thank you so much for joining us today and sharing your invaluable expertise and AI and data science in pharmaceuticals. Your work is truly revolutionizing drug discovery and development. Bringing hope to countless patients worldwide. And to the folks who are listening or watching, we hope that you found this episode as inspiring and informative as we did. Dr. Liu's dedication to advancing
Hanh: 00:53:28
health care through cutting edge technologies It's a testament to the power of innovation and collaboration. So if you enjoyed this conversation, please like, subscribe, or leave a comment below. We'd love to hear your thoughts. So join us next time as we continue to explore how AI is transforming the lives of the 50 plus demographic. So until then, stay curious, stay engaged. And remember that the future of healthcare is in our hands. So thank you so much for tuning in to the AI50 podcast.
Hanh: 00:54:05
Take care.
Anne: 00:00:05
One of the most emotional moments was that interaction with the young man in the wheelchair who was able to move around with the stroller. But just again and again conversations with parents who tell us about the accidents they had with their stroller. And they're like, if I had this one, it wouldn't have happened.
Hanh: 00:00:28
Hello, I'm Hanh Brown. Welcome to AI50. Where data and innovation come together. We use cutting edge AI technology to create advanced language model applications. These applications are designed specifically for the people age 50 and above. Our mission is to understand and cater to their unique needs and preferences. Ensuring they get the most out of modern technology. So today I'm thrilled to be joined by Anne Hunger, the co founder
Hanh: 00:01:02
and CPO at GlüxKind Technologies. As a parent and tech innovator, Anne is at the forefront of reshaping the baby stroller industry. With AI power solutions designed to assist parents and ensure a safer, more convenient and stress free experience. So Glooks can smart strollers combine cutting edge technology with essential baby centric features. So, Anne, welcome to the show. Hello. Hi, Anne. Thanks for having me. Absolutely.
Hanh: 00:01:39
All right. So, to get things started, could you share something about yourself that many people might not know?
Anne: 00:01:45
Um, yeah. So my name is Anne Hunger. I'm originally from Germany. I moved to Canada about seven years ago and that's where we started GlüxKind. Um, It's also that my German background also inspired the name GlüxKind. It means lucky child directly translated, um, but it's also a figure of speech. So a lucky child can be anyone regardless of age. It just means that regardless of what kind of trouble you get yourself into, it always tends to work out just fine. And that's kind of the, the comfort
Anne: 00:02:21
and the feeling that we want to, to give our customers as well. Regardless of what challenges they face, it's, it's always gonna work out at the end.
Hanh: 00:02:34
Awesome. The global baby stroller market size was valued at 2.6 billion in 2020 and is expected to grow at a compound annual growth rate 5.8% from 2021 to 2028. So can you share your personal journey that led to co-found kin's technologies and what experiences or challenges, uh, as a parent inspired you to revolutionize the baby stroller industry?
Anne: 00:03:09
Yeah, I mean, I definitely didn't think that that was on the agenda for kind of my professional career, but when, um, my husband and I were expecting our first daughter and, uh, in 2019, then that was the first time that we really looked into the stroller market as it is currently. And with all the. Kind of home automation items, all the like smart devices that we have nowadays in our lives, we were just surprised that the stroller market was lacking that and thinking how important a stroller is becoming in every parent's life. Um, We just thought there should
Anne: 00:03:49
be something that's more assistive than the traditional strollers that are currently on the market. We did lots of, uh, market research, lots of conversations with other parents. And, um, that really proved the point or emphasized the point that there's a lot of people looking for better solutions. Um, it's just, you know, Challenging to develop those and, um, so we decided to actually take on that challenge and Yeah, develop our smart stroller and now we're, um, that was four years ago that we started and now we're really at the, at the point where we're
Anne: 00:04:29
starting to deliver our first units to the customers who have been, uh, patiently waiting for their products and, and who are really excited to start using, um, this particular product.
Hanh: 00:04:45
Well, congratulations.
Anne: 00:04:46
Thank you.
Hanh: 00:04:46
Yeah. That's so exciting. So, a study by the Pew Research Center found that 56 percent of parents with children under the age of 18 say they often feel rushed even to do everyday tasks. Now, GlüxKind's mission is to assist parents by integrating AI technology into baby strollers. Now, can you explain how your smart strollers address the common pain points faced by parents, such as navigating difficult terrains or multitasking while caring for their baby?
Anne: 00:05:18
Yeah, you, you, you touch on a really good point. Like there's so many competing priorities now in our lives that, um, it's really hard to just get that time where you're in peace. And spending quality time with your kids. And, um, we just want to give parents more time, more peace of mind to be exactly in that position to spend that quality time with their kids. Um, so we're improving the convenience and the accessibility and, um, the safety of the baby stroller in order to give them that, um, mental space, but also the
Anne: 00:05:58
physical relaxation so that, um, you can. Yeah, really enjoy the time with your kids. And how we do that is our strollers are motorized on like to start with. So you can think of them like an e bike version of a stroller, a power assisted on, on uphill, uh, or uneven ground, or if you load them up with your groceries, it's no more. effort than pushing an empty stroller on super flat ground. Um, so it's really more steering rather than actually pushing and exerting effort when you move around.
Anne: 00:06:35
Same on a downhill. I think a lot of parents, um, have that thought at the back of their heads, uh, that the stroller could run away at any given point in time, if they actually happened to slip slip off the handlebar and we take that worry out of the equation, because as soon as, um, we don't. Parents don't touch the handlebar. If the stroller actually stops and doesn't go anywhere. So you're actually, they're actually more in control than with the regular strollers.
Anne: 00:07:02
And, um, yeah. And then we also have features that enhance the sleeping, uh, for babies. So our rock baby feature is extremely popular, meaning that the stroller just rocks back and forth and I can actually show you, I have the stroller behind me.
Hanh: 00:07:18
Sure, sure. Well, you know, I see so many, uh, cases where this could come so valuable, um, a mom that's currently pregnant, pushing a baby who's, you know, a year old or should be running or walking. Yeah. Um, or she might have multiple kids, you know, and keeping track of what in the stroller, perhaps carrying a baby and then perhaps one that's running behind her. Wow.
Anne: 00:07:49
Yeah. We also get a lot of. Um, inquiries from parents with multiple kids, uh, we're working on, um, um, multiple occupancy product. Uh, right now our initial product is kind of a single occupancy stroller. Um, and yeah, but there's lots more to come and we get a lot of inquiries from exactly, as you say, people who have. A lot of moving parts, either a couple of different, um, kids, different age groups, kids who are out of the stroller, one kid in the stroller or, um, parents with dogs. So just a lot of things
Anne: 00:08:24
competing for your attention. And, um, if you don't have to worry about your stroller or exert a lot of effort, um, into moving with your stroller, then that makes a big difference.
Hanh: 00:08:41
Absolutely. So go ahead, show us. You said you have something you wanted to show it.
Anne: 00:08:44
Oh, it's, it's, let me show, show you later, okay?
Hanh: 00:08:49
Oh, sure. So now technological advancement in everyday products can transform routine tasks into seamless experiences, enhancing both convenience and safety. Now your stroller feature, a dual motor system for power assist. And adaptive braking. So can you share a story about how these technologies have a meaningful difference in the parents daily life?
Anne: 00:09:14
Yeah. I mean, I guess the most meaningful example, um, that we witnessed the conversation that we had is just how much more accessible it is. This makes the stroller to parents of different physical capabilities. So we had a conversation at a trade show with, with a young man who was in a wheelchair and, um, and his, his mom was present as well. Who was also, um, in a wheelchair. And. They were just talking about the fact that there are not really any products
Anne: 00:09:49
out there that would allow them to independently go out, uh, with their kids, that it's a real challenge to, um, continue to have that independence. Once you add a little one into their lives. Um, and with the LR stroller that, that we have, that we're going to release, um, Later this year, it actually drives autonomously, um, and it can drive autonomously just in front of a wheelchair as well. So allowing, uh, people with, um, different physical capabilities to continue to be independent
Anne: 00:10:25
even as young parents of newborns.
Hanh: 00:10:30
Mm. So nice. I wish I had that 26 years ago.
Anne: 00:10:35
You know, that's actually one of the, one of the most common comments we hear when we're at trade shows or somewhere else where we just demonstrate usually the rock a baby feature, parents, uh, walk by and they remember how much time they spend just walking around the block, getting their kids to sleep because all the balls around sleep and how much of a break you get in that very strenuous time of your life, super rewarding, but it is. A lot of, a lot of effort and a lot of stress with, uh, little kids and newborns. So they always say, where was
Anne: 00:11:07
this when my kids were little? That's
Hanh: 00:11:12
Absolutely.
Anne: 00:11:13
100% the top comment we're getting.
Hanh: 00:11:15
My, uh, I have three, 26, 24 and 22. And I remember back then it was either a stroller or a car that would just knock them out. And I love it. Yeah. And there's been a few occasions, let's say if they're sick and they don't feel well, you know, you don't want to be driving at 2 a. m. Right. So we put them in a stroller. We just go like this, like throughout just until they, you know, but I wish there,
Hanh: 00:11:41
gosh, just a, a powered one stroller. Yeah, that would be awesome.
Anne: 00:11:46
Yeah. We use the, we, we have a six, six months old, uh, baby now as well. Um, we, we call him our chief product tester now. Um, and he's slept. So many hours in the stroller while it was rocking at home and allowing us to, um, yeah, just drink a cup of coffee or get a couple of emails.
Hanh: 00:12:11
That's true. So now, according to the survey by the juvenile products manufacturers, 76 percent of parents consider safety the most important factor when purchasing baby products. I'm sure this is a high priority for GlüxKind as well. So how does GlüxKind ensure the highest safety standards in your strollers and, um, what role does the 360 safety bubble play in protecting both the child and the stroller?
Anne: 00:12:46
Yeah, I mean, we, we consider safety, um, obviously one of our highest priorities. That's as I said, initially, for example, um, runaway strollers are such a source of anxiety. Um, for parents that, um, it just, It's so easy to solve for that, but a lot of parents that I, that I talk to, they, they either, um, take like detours to avoid certain hills so they don't get into a position where they kind of hold on to dear life. So with our stroller and the smart brake assist feature, for
Anne: 00:13:22
example, the stroller slows down. And if you happen to let go of the stroller, it just stops. Same with babies don't always want to be. in the stroller, right? So if you want to take them out and want to give them that physical contact, um, and connection, then you can do that. You can hold them with two hands while the stroller actually, um, the empty stroller navigates the sidewalk in front of you autonomously until you want to put your child back into the stroller. So the stroller itself makes mobility. More safe while your child is in there
Anne: 00:13:55
with break assist with the 360 safety bubble that is creates that environmental awareness of any incoming dangers. If you're walking around a sharp corner where you can't see around, but the stroller is like a meter, a meter and a half in front of you. So it would already alert you if there's something coming your way. Um, but also if you want to take your child out of the stroller, you can make sure that. You have a safe hold on your child. You can spend that one on one time, continue your walk and your stroller
Anne: 00:14:30
still continues the walk with you while being aware of what's happening around it.
Hanh: 00:14:36
Mm hmm. Wow. That's some awesome AI technology. So that's great. Um, so the AI and the consumer product market is projected to reach 9. 5 billion by 2025, a growing rate at, I guess, 30 percent from 2020. So AI is not just about automation. It's about enhancing the quality of life by providing intelligent solutions to everyday problems. So can you share with us more about the AI features, uh, in your stroller, such as the automatic rock my baby
Hanh: 00:15:07
mode and how do these innovation contribute to the baby's comfort, um, and the parent's peace of mind?
Anne: 00:15:17
Um, yeah, I mean, the, the core AI feature, um, for the stroller is the self driving. Um, so again, when the stroller is unoccupied, when the child is not in there, um, Um, so either you have a newborn or a little baby who needs that physical connection, we want parents to be able to give them, um, that connection, take them out of the stroller and still safely continue their walk. Or you have a toddler who's learning how to walk, but you still bring the stroller along because they don't walk for very long, they get
Anne: 00:15:50
tired and Yeah, places to go to. Right. So in those cases, when the store is not occupied, it can drive itself along the sidewalk, along a path in front of the user, uh, it stays within arm's reach distance, uh, maintains the same speed that you're walking it. If you stop, it stops. If you step away, because. If your toddler found some cute flowers on the lawn beside the, beside the path, then just the stroller just stops and waits for you to continue the journey. And it also stops at intersections,
Anne: 00:16:21
waiting for the parent or other user to, to provide that input signal that it's safe to cross the street and that they actually want to cross the street. Um, so that's our core AI feature that, um, enables that. To turn this roller into a pure real support gear so that you only have to touch it when the cargo, your precious cargo is actually in there. Otherwise it just comes along with you, um, basically on standby until you want to put your child back in there.
Hanh: 00:17:04
So as a parent and an innovator, what, um, have been most, uh, valuable lessons that you've learned throughout your entrepreneur journey? And how have they influenced your approach to product development and your leadership?
Anne: 00:17:20
That's a lot of questions in one. Um, I guess on a very basic level, um, becoming a parent and being an entrepreneur at the same time really pushes you to, um, figure out your priorities and, because spending time with your kids is non negotiable. And then on the business side, it, yeah, again, it really pushes you to figure out what does have to happen at this point in time and what can wait or what can be handed off or outsourced. And as we're talking about AI, there's so many great tools, AI based tools out there
Anne: 00:18:11
that help you do that and achieve that added level of efficiency that, yeah, you're just able to spend more time with the things or little people that matter to you.
Hanh: 00:18:27
Time suddenly becomes more precious, right? Yeah. And then like you said, time with your, your baby is non negotiable and then whatever's left. You got to take care of your own well being, for instance, and then on top of that, running a business and then figuring out what to own and what to outsource. Well, thank you for doing all that with a newborn, of course, make sure you get caught up with your sleep. I mean, these are very
Hanh: 00:18:53
important things, right? Yeah. Yeah. So that's great. So now can you walk us through some of the key features of the app, um, that you, that you talk about? The, um. Mm hmm. Companion app for enhanced control and monitoring. Uh, how do they empower parents?
Anne: 00:19:12
So, um, I mean, our, our companion app enables the user, whether it being the parents, grandparents, other caretakers like nannies to interact. with the stroller to connect to the stroller and adjust it to their preferences and to the baby's preferences. It's, um, an interface, um, yeah, to also interact with different caretakers. Um, but it was really important for us as well that If you don't want to use the app, if you have grandparents who are going for a walk with the stroller, they don't need to have the app in order to walk with the stroller.
Anne: 00:19:54
So we wanted to keep it very intuitive, um, that the usability is not restricted by having to use a phone and having to have a phone with you. Um, So two of the key things that can be adjusted with the app are the level of boost you want. So the level of assistance that you want from the stroller, both on upper and down here and, um, the intensity of the rock baby. So, because different kids have different preferences and sometimes it's just kind of a smooth back and forth. And sometimes you just
Anne: 00:20:30
need a little bit more. Um, yeah, and then. There's also, I don't know whether I mentioned that before, we have built in speakers for white noise, um, but also story time so that parents have their screen free entertainment package as the kid grows right on the stroller. They don't have to remember different, another thing to bring along. It's a lot of products built into one and all those. additional auxiliary kind of functions are accessible through the app.
Hanh: 00:21:03
Well, I'll tell you with all that I'm hearing, maybe the baby might not want another environment like their crib. You know?
Anne: 00:21:11
Yeah. I mean, um, initially, like, I guess that's a very personal story, but it's, um, anyone can do that. We used the bassinet, the stroller bassinet Um, as our bedside bassinet for our little one as well, which provided the benefit, um, that he got used to the same sleep environment, whether we were outside on the go or in the house and overnight, which makes a huge difference in terms of how comfortable they are sleeping and, um, and their sleep quality.
Hanh: 00:21:46
And I'll tell you, newborn, you know, that phase, Sleep. Oh, it's a big deal. It's a.
Anne: 00:21:53
It's a huge deal.
Hanh: 00:21:57
And, uh, and how long they sleep and whether they sleep straight through. Oh, those are a big deal. Not only to the child, but to everyone around them.
Anne: 00:22:07
Yes. We're, we're going through a rough phase right now with teething. So sleep quality is right back up there as the priority again.
Hanh: 00:22:23
Hmm. Well, that's a wonderful stage to now, um, books can receive the CES 2023 innovation award for their smart stroller design. Now, your modular travel system offers a comprehensive solution from birth to toddler hood. Now, how does this system provide convenience and value to parents? And what sets it apart from all their travel systems in the market?
Anne: 00:22:50
Yeah. So we actually received both the 2023 and 2024 CES innovation awards for the two different, uh, stroller models that we have, which has been, um, amazing to, for us as a very young startup, which got us a lot of exposure globally, um, and a lot of interest from all over the world, indicating that there's parents everywhere that are looking for a solution that provides them more than, than what current strollers do. And, um, yeah, so in terms of the convenience, I think it's not purely convenience, but also added safety and
Anne: 00:23:33
accessibility, um, with the travel system. Um, it's. It's pretty industry standard that you're able to transition your stroller from that newborn stage with the newborn bassinet that's also safe for overnight sleep to a seat that supports a child until they're like 50 pounds. Um, and you also have the option to just pop on your car seat if you're going for a quick trip. So that's It's really the, the essence of a travel system that you have that modularity and the system and the stroller frame is able to accommodate the growing
Anne: 00:24:20
needs of your child in your family. And, um, yeah, I mean, that makes it convenient because we combine a lot of products that parent. Parents buy it separately, uh, currently into one form factor, whether that being like the smart crib, the stroller, the speakers that are built in, um, it's just less things that you have to think about when you leave the house and less things that you need to purchase, uh, initially as you prepare for your baby.
Hanh: 00:24:53
All these extra amenities. That, that was not even heard of, you know, and now it's so accessible. That's great. Now, do you have a moment when you realize the true impact and the potential of your innovation?
Anne: 00:25:08
Was there one moment? I mean, again, um, one of the, one of the most, I guess, emotional moments was, uh, that interaction with the, with the young men in, in the wheelchair who was able to move around, um, with, with the stroller. Um, but. Just again and again, conversations with parents who tell us about, um, like little accidents they had with their stroller and they're like, if I had this one, it wouldn't have happened. And even if it, even if the child wasn't actually injured, just that moment that caused like fear to the
Anne: 00:25:42
parents when the stroller was running away or rolling away a little bit, it's such a traumatic experience. If you can avoid that, that makes a huge difference as well. And, um, again, if parents are able to spend more relaxed time with their kids, they're better, better parents, better, um, for themselves. Yeah.
Hanh: 00:26:11
Yeah, that's true. That peace of mind is huge and safety either add to that problem or can alleviate it, right? Um, stroller is one, going to the park is another. I remember those days. It can be a wonderful place, but it can also be a dangerous place. Yeah, well, you'll see that maybe you're not at the park phase yet, but, uh, no, I think it's wonderful with the AI innovation for strollers. So now as a company founded by parents for parents, how do you ensure that every
Hanh: 00:26:50
feature And design choice addresses real world parenting challenges effectively?
Anne: 00:26:57
Um, well, we've had conversations with close to 700 other parents. At this point, we made sure that we get a lot of feedback as we developed the product on, um, both the hardware choices that we made, as well as the software features that we're implementing. Uh, so that's one thing. Um, And we, my co founder, who's also my husband, we also have a, um, a daughter who's four and a half, who has been the inspiration for the company in the first place, so we can really develop this from a very personal experience as well, in addition to all the feedback that we've
Anne: 00:27:37
been getting from a lot of other parents.
Hanh: 00:27:43
That's awesome. Now, can you share an instance when you face a significant technical, uh, technical or design challenge during your development and, and how did you or your team navigate that situation? And what did you learn from that?
Anne: 00:28:00
There, uh, when haven't we faced a challenge? Um, I mean, there, there've definitely been a lot of challenges, um, developing this product. We wanted to continue providing a lot of the features that parents appreciate about regular strollers. Um, at its core, strollers need to be lightweight, they need to be foldable, in order to be comfortable. usable in all the different situations that they are going to be used in. But then we also add motors, electronics, um, which add weight for when they
Anne: 00:28:42
include cables that need to go somewhere, which, um, conflicts a little bit with the folding of the, of the frame. So I guess that interplay has been a big challenge in the development. But, uh, one thing we, we did is we chose smart materials, um, that are very light and very durable and strong to offset the additional weight that we put in, uh, with the components like the motors and the electronics. And, um, we spent a lot of development time on the folding mechanism to ensure that that still works. It's still in a small form factor
Anne: 00:29:23
that fits in your trunk that can be like stored at home or in your garage wherever you want to keep your stroller, but as it still has all those, um, smart features that enable the. Uh, easier mobility, more convenient mobility and higher accessibility.
Hanh: 00:29:49
That's great. Now, sustainability and ethical design is very important to consumers. So how does GlüxKind incorporate these values into your products and your company culture?
Anne: 00:30:07
Yeah. So in terms of sustainability, I guess the biggest. Um, topic for us is to combine products, a lot of different products that parents would purchase separately into one so that eliminates the need for first producing all those other products, shipping all those other products. And because it's, it's all in one form factor, and it continues to grow with your family. Um, the. Mobility platform, we call it. So basically, the stroller frame
Anne: 00:30:41
can stay within the family and really encourage and enhance a urban lifestyle because you have a support gear that allows you to make bigger grocery runs without using your car. And you, we can provide other attachments. Um, once your child grows out of the stroller that enable you to, yeah, just turn it into like a shopping cart, basically into all your grocery shopping, all your errands in your neighborhood, um, with that stroller frame. Um, and again, we, we have lots of, lots of other plans of enhancing the. and increasing the sustainability of
Anne: 00:31:22
the product, uh, in the future as well.
Hanh: 00:31:28
That brings me to the next question. Looking ahead, what is your long term vision for GlüxKind and what exciting, uh, exciting development or milestone can we expect to see in the coming years?
Anne: 00:31:40
Yeah, so the immediate, uh, Big milestone is starting our first production run in the shipping of our first units. We got a huge backlog in terms of orders that we want to work through. But at the same time, we, we need to ensure the quality, safety of the, of the product. And, um, yeah, so we're starting up slowly, but then, um, yeah, Also on the development side, uh, we, we have lots of plans for, for other products. Again, I said earlier that we get contacted by lots of parents with multiple kids, um, which
Anne: 00:32:19
makes a whole lot of sense. The more kids you put in your stroller, the heavier it is, the more effort it is to move around. So, um, the next products on our website. Roadmap or definitely strollers for my occupancy and, um, and we're also developing a more comprehensive platform to take the load off of parents and, um, suggest them products that they are going to need in their journey, um, so that we can be one source to provide parents with. With products as accessories, and. Yeah.
Hanh: 00:33:01
ThaIt sounds exciting. Wow. No, as a leader in a very rapidly evolving industry, how do you stay informed with the latest trends and technologies? And how do you foster that innovation within your team?
Anne: 00:33:21
Um, I guess staying on top of the trends is, and the technology that is developing so quickly in that AI computer vision space is crucial to our development, um, both on the software as well as on the hardware side. We've been, uh, really lucky to be very well Connected and supported to, for example, the NVIDIA team and attending conferences like, uh, NVIDIA's GTC conference in San Jose that was just in March, I believe, um, is definitely one aspect of how to stay on top of things and, and continue to, um, see what's out there, but also be connected
Anne: 00:34:07
to the people who are pushing the boundaries in those respective fields.
Hanh: 00:34:15
That's great. Now, what advice would you give to aspiring entrepreneurs, especially those seeking to leverage technology, AI or so, uh, to solve real world challenges and make a positive impact?
Anne: 00:34:30
Um, um, I think at the core, it's really important to understand product and the user perspective, um, for which you want to develop a product. Um, so if, if you're developing it, um, for a problem that you're facing yourself, you're always going to have a different level of impact. and relatability to what, what, what really solved the problem that people are facing. And then I guess just try to do it like scrappy initially, but get to, um, Like a proof of concept really fast and then test it with people, whether
Anne: 00:35:17
that actually solves their problem. So that's kind of developing and testing cycle. Um, at the beginning is, is really important and don't spend too much time trying to make it perfect without having that feedback group.
Hanh: 00:35:34
Well, thank you so much. So we're at the end. I wanted to know, do you have anything else that you'd like to add?
Anne: 00:35:46
Um, I mean, I, well, if, if any of your, uh, of the listeners or viewers of this podcast, uh, would love to get one of the strollers, then they can head to our website, uh, which is GlüxKind. com and, uh, sign up for, for our wait list. Um, and then we're happy to, to provide them with the next generation mobility for parents in the coming months.
Hanh: 00:36:18
Awesome. And you could always look and and hunger on LinkedIn. Follow her for sure to get updates on her products. Well, thank you so much for joining us today and in sharing your incredible journey and this groundbreaking work at GlüxKind, your passion, leveraging AI and innovating design to empower parents, enhance safety, comfort and convenience. It is awesome. Very inspiring. Um, so it's exciting to see how the smart strollers are transforming
Hanh: 00:36:51
the parenting experience and setting new standards in the industry. And to our listeners or viewers, thank you so much for tuning in. Uh, if you enjoyed this conversation, make sure to like, subscribe, follow Spotify, YouTube, LinkedIn, leave us comment, uh, give us your thoughts about the future of powered baby, baby gear. So join us next time as we continue to explore the innovative technologies shaping our world. Until then, stay curious, keep embracing innovation. Thank you for your time.
Anne: 00:37:27
Thanks, Hanh.
Hanh: 00:37:28
Thank you.
Harvey: 00:00:06
When I was in med school, I had a really famous person that came to the hospital and all these medical students were logging in to that patient's record because they wanted to see why they were there. And so being able to have that strong compliance monitoring to make sure that we're regulating who has access to that data and then where's that data going? Is it going to ChatGPT? Is it staying in our hospital servers? Is that data secure?
Hanh: 00:00:33
Hello, I'm Hanh Brown. Welcome to AI50, where data and innovation come together. We use cutting edge AI technology to create advanced language model applications. These applications are designed specifically for the people age 50 and above. Our mission is to understand and cater to their unique needs and preferences, ensuring they get the most out of modern technology. So now, picture this. You're the chief medical
Hanh: 00:01:04
officer of a busy hospital. You're working hard to provide high quality care in a changing healthcare world. You feel like there's untapped potential in data your hospital creates every day. You know that ensuring this data, Could change patient care for the better, but you're not sure where to start. Well, that's when you hear about Dr. Harvey Castro, a visionary doctor and strategic advisor for GPT and healthcare. Well, Dr. Castro has a unique background. He's practiced medicine
Hanh: 00:01:43
and led healthcare systems. He's become a leader in innovation in AI and healthcare. He's an expert in making AI technologies work with clinical needs. Dr. He creates environments where people work together. He also navigates the ethical issues of using AI in healthcare. Well, um, this has made him a popular advisor for healthcare organizations. Well, today we have the privilege of talking to Dr. Castro.
Hanh: 00:02:14
We will explore his fascinating journey. Uh, we'll gain valuable insights into how AI is changing healthcare. So join us as we learn from a true innovator. Discover how his guidance can help you unlock the full potential of your health care data. So, Dr. Castro, welcome to the show.
Harvey: 00:02:42
Hello. Thanks for having me. I appreciate it.
Hanh: 00:02:45
Yeah, absolutely. Well, we're thrilled to have you here today. To get things started, could you share an interesting fact or a story about yourself that many people might not know?
Harvey: 00:02:56
Yeah. So, I was working in an emergency room, and literally, I got called into the office, uh, I call it the principal's office, saying, Hey, doc, we need to have a sit down with you. And I was really worried. I was like, Oh my gosh, did something happen? Did I have a bad outcome with one of my patients? And they're like, no, we, we see that you're doing great. We want to see if you can move faster. And I, and I said, well,
Harvey: 00:03:20
can you pull all the stats? And so they showed me all the statistics. And I'm like, I'm actually above the average. They're like, yeah, but we've seen you at work. And when you want to work fast, you can work fast. But we want to see if we can get you to see more patients and I was really upset with them I was like, I I don't understand like am I hurting someone is something going on and they're like we want you to order less tests we want you to spend less time with your patients
Harvey: 00:03:42
and Anything that the ER doesn't can not have to do send it to the family practice doctor And I got so upset. I said to them, my goal is to be a doctor. My goal is to make sure that every patient is taken care of and I'm not doing anything wrong. And I got to the point where I called the owner of this company I was working for. I was one of the partners. And I said, here are your shares back. I went out and he looked at me like I was crazy. He's like, Harvey, Do you realize how much money you're giving away?
Harvey: 00:04:14
And I'm like, yeah, I can't work in a place that they're going to ask me to move the meat and to push people a certain way. I ethically, I cannot do this. And so I walked away, uh, fast forward, the company sold, made all this money. Uh, my business partners call me like, Hey, this could have been you. And I said, no, you know, I sleep well at night, like I'm okay. And so that's something that nobody really knows.
Hanh: 00:04:37
Yeah. Wow. That's great ethics, commit, uh, commitment and conviction to serving your, your patients. Wow. Thank you. So now, what inspired your journey from practicing medicine to becoming an estranged teacher advisor for GPT in healthcare?
Harvey: 00:04:54
You know, that's such a good question. I've always, I call myself a little bit of a nutty professor. I enjoy seeing technology, seeing something that's going on and seeing how I can fix it. And so I was literally in the emergency room coding a patient, and this was when the first iPhone had just came out. And I'm looking at the phone and I told the nurse, Hey, we need to start to strip. Let's take care of this person. They're in cardiac arrest and they're doing CPR.
Harvey: 00:05:21
And she went and got a textbook, started thumbing through. And I'm looking at her thinking, no, no, no. Like, we need to do something quick. And so I had that aha moment that I said, you know what? I'm going to create the first IV Med app in the world. And I did, and I published, and it went viral. And it was such a success where people were like, man, this is saving lives. Like, the old way was taking us a long time.
Harvey: 00:05:43
This way, it's seconds. Fast forward, I jokingly and lovingly say this thing called ChatGPT came out. And I'm playing with it, and I thought, oh my gosh. This is gonna change humanity. This is gonna change the world. And I remember being so excited. I was in this office I ran to my wife and I said, honey I'm gonna write a book on how to use ChatGPT in health care and she looked at me She's like, what is ChatGPT? And what are you talking about? And she thought I was kind of crazy She's like, honey, no
Harvey: 00:06:12
one's gonna read your book. No one knows what ChatGPT is Don't waste your time and I actually like paused and I thought you know what? You I have a conviction. I'm going to do it. So three weeks later, I was selling a book on how to use ChatGPT and health care and fast forward. It's opened up all these doors and companies calling me to give this talk.
Hanh: 00:06:36
That's awesome. Thank you for the work that you do so much needed in the health care. So along the way, how do you ensure that AI technologies is Align with clinical requirements and maintain data integrity?
Harvey: 00:06:55
That's an awesome question. Number one, especially healthcare professionals listening to this. We need you to be on the field with us in AI. How do I ensure this is we have to have healthcare professionals working with the big companies to make sure that they're solving the solution the correct way. If someone like me is not with them. They're going to fix it in the way they see it, but they don't see it the way the front lines see it. And so that's the number one. We need collaborations
Harvey: 00:07:21
with our clinicians. Number two, we need to make sure that our data is validated, that we're making sure that we're using the right data. Case in point, ChatGPT, not many people know this, but when they were training it, they were paying about a dollar an hour to people out in Africa to give it a thumbs up or thumbs down. Well, that sounds good because if ChatGPT, you ask it a medical question, the average person may not know. And so they may say, Oh yeah, that, that sounds good to me. Thumbs up.
Harvey: 00:07:51
What the people don't realize is there weren't doctors giving that thumbs up, thumbs down. And so that is an example of how maybe this technology is not fit. And so to answer your question, I'm a big proponent that we need to have our own large language model, our own GPT, but call it, I'm an ER doctor, GPT, ER, where it's an ER Doctor.
Hanh: 00:08:11
Industry. Yeah. Industry GPT. Basically your own operating system.
Harvey: 00:08:16
Yes. Yeah. And so that would be another way that way. We're complying with the standards. We're making sure that the state is correct. We're reinforcing the data the correct way to go into the weeds. We're creating like a GPT where if I ask a question like, Hey, this person has chest pain and it gives me the different options. Then a graph that shows me how did you come up to that conclusion? So then me as a doctor can look
Harvey: 00:08:37
and say, okay, now I see how the computer got that diagnosis. It put these things together. That's one way. The second thing to go into more detail would be this thing called RAG. Basically, um, imagine if I'm an ER doctor and I had my own clinical notes and then say you had a question, those went to my notes first before it went to ChatGPT and then it would explore that to answer your question. So you're getting a more accurate look at it.
Hanh: 00:09:03
Not only in terms of content, but context, right? And it's, it's timely, it's accurate and it's current. That's the kind of the whole idea of reg. So, no, that's great. I think what you mentioned are like the huge key components, uh, to reap the benefits of AI. So great points. So now in a recent study, uh, of the journal of healthcare innovation, highlighted the importance of interdisciplinary collaboration. It also emphasized continuous learning
Hanh: 00:09:31
opportunities and drive positive change within the healthcare organizations. So now what, um, strategies do you employ to create a synergistic environment that foster innovation?
Harvey: 00:09:46
You know, the number one thing is I always tell everyone that works with me, there are no stupid questions and there are no stupid solutions. We just need to work together. I don't want pride to hinder. So I have an open door policy. I want them to always to be able to come to me. Um, I love this little gadget. It's the Apple vision pro in continuing education. This is a big one. Uh, and this is a crazy story and not many non physicians know this story.
Harvey: 00:10:13
So in med school, the rule is see one, do one. And then teach one. And so, to give you a case in point, I was in residency, so learning how to be an ER doctor, and they said, Harvey, come over here, we're going to teach you how to intubate. It's when you put a tube down someone's throat and help them breathe, artificially. And so they showed me, and they're like, okay, the next one, it's your turn. And I'm like, oh my gosh, I mean, I've read about this, I've seen
Harvey: 00:10:39
it, and so literally I was doing it, and then as soon as I was done, they're like, okay Harvey, now your turn to teach the next guy, or girl. Imagine a world where I had this, and I was able to do this a hundred times. Over and over and over and practice and stimulate and over and over. And then when I did that first one with the real person, it really wasn't the first time. The muscle memory is there, the theory, my procedure. And so that's one way of how we can continue to improve our continuous
Harvey: 00:11:07
learning and create that supportive culture so that people feel like, Hey, this is the new way of learning.
Hanh: 00:11:14
That's true. And do you think that in the age of AI, continuous learning and lifelong learning and all of, you know, all in that realm is so important? And especially if you're going to keep up with the advancements of AI, right?
Harvey: 00:11:30
Yeah. You know, this is an interesting question. I call it the bell curve. We have people that I'll say here in I'm in Dallas, Texas. If I go to East Texas and I talk about a I immediately there's this wall and they're like, Whoa, whoa, whoa, that's the devil. No, no, no, I don't like that. No, that's that's not right. But I get the same talk in Silicon Valley. And they're the ones wanting to be like, yeah, high fives. Like, Oh, I like that. And it's a different thing.
Harvey: 00:11:57
So when it comes to healthcare and what we're talking about right now, we need to keep mind, like, what is the culture in that area? Maybe we don't show them the limousine. Maybe we show them a baby step, something smaller that they can say, okay, I'll accept that knowing that we can give them the limousine, but if we do, we may scare them away.
Hanh: 00:12:15
It's overwhelming. Yeah, no, I agree. You know, when I talk to folks. Sometimes they don't know where to start or what AI or how it can, how it can help them. My, my advice to many is like, start small, identify what your pain points are. I mean, you got to know your business. You got to know who your customers are and what goals you wanted to achieve. And then when you know that, identify what are the hurdles? What are those inefficiencies that you just love to do away and then prioritize,
Hanh: 00:12:44
start with a small gain confidence. I think once you experience that. And then you can dial things up. Uh, it is overwhelming, you know, for folks, yourself and me, like we immerse ourselves every day. So it becomes our vocabulary and the air and just everything in our, in our realm. So I think it's, it's, uh, it's so true that you, uh, you kind of test the temperature or the culture of the group that you're, you're talking to. So thank you. Now, recent study has shed some light on the complex, um, the complex of ethics.
Hanh: 00:13:24
Of using AI in health care and study in the Journal of Medical Ethics looked at the potential risks. of AI algorithms, if not, uh, developed and implemented responsibly, these algorithms could perpetuate biases and disparities in patient care. And the study also stressed the importance of addressing fairness, transparency, and accountability. So, considering the multifaceted ethical landscape of, uh, AI in healthcare, so how do you navigate these considerations? And what steps do you take to ensure that the technologies that you advise
Hanh: 00:14:04
align with the key ethical principles?
Harvey: 00:14:07
Yeah, no, this is such an important question, and I actually appreciate you taking time to ask that. You know, when I think about it, the number one thing that I think of is lack of education. If I'm a doctor, and let's pretend I'm brand new, I just graduated, I may believe everything I see. I may believe, uh, ChatGPT or some GPT that says, Oh, this is it because in my mind, I grew up with it. I've seen it. I'm thinking, Oh, this is the current standard.
Harvey: 00:14:35
Someone like me that's been doing this for 20 years. If you give me an output from GPT, I'll look at him like, Oh, no, that's wrong here. Here's why, because my clinical gestalt tells me otherwise. That's why we need to keep a human in the loop. So to answer your question. I think we need to educate. We need to educate everyone. What are the good, the bad, the unknown. And when it comes to ethical issues, some of the physicians may not
Harvey: 00:14:58
realize this is biased information and they're being told biased information and they're going to continue that biased information and reinforce it. But if we educate these physicians and nurses and health care professionals to say, Hey, keep an eye open for these things know that this is could be wrong. And here's why. The other thing that I think it's so important. I really want this to come out. We go to the grocery store. We buy soup. We buy something.
Harvey: 00:15:23
We look at the cans. We see the food label. Why are we not having a food label for large English model? Why don't I have something that says, Hey, Miss Brown, here's this A. I. Here's the food label. But you know what? It wasn't trained in this data. It wasn't trained in this. It's biased in the following things. And so when you use it, make sure that you keep this in mind. And so then now you look at
Harvey: 00:15:44
it, you're like, Oh, okay, I shouldn't use this tool for this. Maybe I should use this other tool. And I think that will help us create those right ethical frameworks. The other thing is we need transparency. That example that I gave you with GraphGPT, if I don't know how you got to that conclusion, kind of like in grade school when we do math in our head and our teacher gets on us like, no, no, no, show me the work. Same thing. Let's be transparent. Show me how I got to this.
Harvey: 00:16:12
What database did it go into? Where did you get that information? We're using PubMed. We're using recent studies. Did you confabulate this thing? Is this hallucinating? And so we need to be as transparent as possible. And we need to make sure that all the stakeholders involved, including our patients, are aware of the good, the bad and the unknown. When I consult hospitals, I'm telling them, Hey, we need it. Yeah.
Harvey: 00:16:33
A bill of rights, but like the bill of rights for AI at your hospital because patients are going to use Dr. Google now they're using Dr. GPT or Dr. ChatGPT.
Hanh: 00:16:42
Or Dr. Perplexity, right?
Harvey: 00:16:44
Yes. Dr. Perplexity. Oh.
Hanh: 00:16:45
Wikipedia.
Harvey: 00:16:47
Yes. And so we need as a society. To make sure that all the stakeholders understand what they're doing. I say this often, I'm, I'm worried for the people here in the United States, but I'm even more worried for people outside the U S that can self diagnose, walk over to the pharmacy and say, Hey, ChatGPT told me I need this drug. And they start taking it and there's wrong on so many levels. So I think we need to educate to make sure that these ethical guidelines are there for all of us.
Hanh: 00:17:16
Absolutely. It has some huge implications, but do you, do you see that? You know, AI in my mind, how I internalize this, it's a, it's like a GPS, right? But it still needs a driver and that's you, that's you and I were the driver. We, and it's all in our prompt, right? Um, we steer it, it gives us, it uncovers insights, uh, but it's, it requires you and I to prompt accordingly.
Harvey: 00:17:43
Yeah. My favorite phrase to what you just said is the way I see it is human, which in my case is doctor plus AI. It's going to beat out the best human out there and the best AI out there. And so let's be that GPS, let the human in the loop, but then I'm a human at two in the morning. Am I met best? Am I ready to go? Will I make mistakes? Possibly more, but can I afford mistakes? I cannot afford any mistakes, but if I augment myself and I use AI and I
Harvey: 00:18:12
use my clinical gestalt and together, I'm going to give such better care. Not that I'm stupid, not that I don't know, but at the end of the day, I'm human. But if I have these algorithms built into my electronic medical record, built into my workflow, now it's going to be better. Um, I'll show you this quick prompt. I got these uh, metaglasses and right now it's connected to ChatGPT, so if you ask me questions, it could hear it. Tell me what I need to say and they'll tell you, but in a clinical case, I could take a picture of an x ray, analyze
Harvey: 00:18:41
it, it'll tell me what it is, what it's seen, and so this is the type of stuff that will become common for every day. The other thing, um, this is a 3D model that I printed, it's the rabbit that's coming out, and they're saying, yeah, it's just like an app, but just work with me for a second. Imagine someone's having a heart attack. And I need to call the cardiologist, the hospital, the calf team, all these people. But if I could take a picture, obviously, make sure that's HIPAA compliant. And it automatically, I say, hey, code a heart attack.
Harvey: 00:19:12
And it automatically sends texts, pictures to the right people, to the right algorithm. And within seconds, I can still work on the patient, but that part of the work is done. And so that's what I'm saying. Like, let's use this technology and see how we can help people.
Hanh: 00:19:26
Absolutely. I love it. I love your thinking. You're innovating and encouraging the listeners to really take it to heart and proceed it with enthusiasm, but with caution and bring the good out of it and serve and solve more problems. So now, can you share a specific example of how AI has directly improved patient outcomes, directly?
Harvey: 00:19:54
Oh, yeah. No, this is awesome. There's so many that come to mind, but I'll focus on two. Since I'm an ER doctor, I'll share this one. One of my colleagues has this AI device and technology, and I'm jealous because our hospital doesn't have it, but here's what it is. Say someone's having a stroke. The AI is able to in real time, read the cat scan and send text to the radiologist, the doctor in real time saying, Hey, this person's having to bleed.
Harvey: 00:20:18
I'm reading the extra myself or the cat scan and then automatically whatever the radiologist is doing and saying, Oh, my gosh, I need to take care of this because it's showing alert. And then me in the front lines in the emergency room is telling me, Hey, This is, uh, a stroke. And so now I can start the ball rolling instead of waiting. You know, the radiologist has a list and then possibly missing it. That's one that immediately I'm going to be helping patients. Um, the other one that comes
Harvey: 00:20:44
to mind, uh, one of my friends invented this is pretty cool. It's basically a, a large language model device. That sits over the patient's bed, and it's just looking, and it's basically for the elderly. And so, as we know, if, God forbid, an elderly falls and breaks their hip, their mortality goes up. I mean, multiple things, especially, um, there's just a lot of stuff that hit their head. What this device does is in real time analyzing, and if the patient is making
Harvey: 00:21:10
a gesture, It can analyze but if it's ripping the IV or making the gesture of getting out of bed Then the ai is immediately texting the nurse texting the doctor saying hey your patient's about to get out and then simultaneously In their language using ai and saying if it's in spanish senora garcia, don't get up And so then it's talking to them and then and then i'm like wow, this is gonna save lives this is gonna be amazing because You know healthcare is expensive and I know hospital administrators as a formal one I used to pay people to sit by a patient to keep an eye on them now having
Harvey: 00:21:44
a device like this would be amazing.
Hanh: 00:21:50
Absolutely. But you know, um, here's another, um, consideration. Integrating AI into existing healthcare systems come with, comes with, um, significant challenges. There's the technical, there's the operational and cultural barriers that healthcare organizations face, uh, when adopting AI technologies. So, these challenges include, uh, for instance, data quality, standardization issues, interoperability concerns, and resistance to change among healthcare professionals.
Hanh: 00:22:28
Very common things, right? Now, there's also concerns about the potential impact of AI on the workforce dynamics and job roles within the healthcare organizations. And when you, uh, try to move this to, um, ensure a smooth transition and buy in from all the key stakeholders at all levels, it's so important for the successful of AI integration. So given the complex challenges, um, that you've discussed and I, uh, just added, so how do you approach the integration of AI into existing healthcare systems? And what strategies have you
Hanh: 00:23:08
found effective in overcoming, uh, these barriers and ensuring successful adoption process?
Harvey: 00:23:18
You know, you're going to laugh when I say this, I, I, I, my analogy is equivalent to arguing with your spouse. At the end of the day, how do you fix this? The solution or what's the solution? It's education. You educate each other on how you see it and you find that compromise. Same in health care. Someone comes in with a shiny object and say, Hey, we want to put this in your hospital. It's about educating the team. To your point, helping with the culture.
Harvey: 00:23:45
They're going to be resistant to change the interoperability issue going in and having someone like us health care that we know it. And when we integrate these things, we know that ahead of time that this has to be compliant. This has to be able to work with the electric electronic medical record. If that's what I'm trying to do. And so some of the other solutions. People are scared of this technology and they're worried that this is now going to be another cyber security issue. So one of my suggestions is
Harvey: 00:24:12
saying, you know what, I get it. Let's create a large language model and let's use something like LLAMA3 and let's put it in your hospital servers. That way you're in control of the data. It's not leaving. Your servers is staying inside your servers. And that's one idea that hospitals are very receptive saying, Okay, I makes me feel better knowing that this data is here because they know that if that data leaks, Oh, my gosh, you know, with HIPAA issues that could be literally millions of dollars that are
Harvey: 00:24:39
at risk if they don't do this correctly.
Hanh: 00:24:45
So what you're encouraging them to do is to have their own AI ecosystem, um, their own operating system, okay, where they can ingest their own data and not have it leak, but using whatever model applications out there. For me, it's Microsoft Azure AI, but there are others. I think that's key, right? To ensure, give them that confidence that is secured, private, and transparent. I mean, to me, that, that should be the first thing when you talk to folks who are hesitant about AI is to give them the confidence of their, their, their customer
Hanh: 00:25:23
service, their sales and marketing, their patient data, and so forth. So that's great. So now what excites you most about the potential of AI in revolutionizing health care delivery?
Harvey: 00:25:36
Gosh, my brain just exploded with all of that. Um, I get excited about a lot of things. Number one, seeing the ability of certain health care professionals sustained a profession because of a I makes me excited. Let me explain. If I know a physician or nurse is going to retire because they're tired of the system and let's say they don't like the documentation and let's pretend that we use AI to, but this conversation we're having is transcribing and it's going and now
Harvey: 00:26:02
they're like, wow, I don't have to type. Man, that makes me excited because now I know that with this aging population and aging workforce that we have, we're gonna get to a point where we're already there. It's gonna get worse.
Hanh: 00:26:16
Yeah, we're there.
Harvey: 00:26:17
Yeah. So if we can leverage a I to help decrease burnout. Help, um, job satisfaction with our healthcare professionals, then man, that's a huge win. So, to me, that's number one. Number two, obviously that's helping with efficiency, helping us with repetitive information, uh, things that we don't like to do. Give it to the ai, let AI do it. Mm-hmm, and, and AI can do that. The other part that makes me excited as a doctor is the predictive analytics.
Harvey: 00:26:43
I'll give you the example of New York Tron where I'm about to discharge. You pretend, and the AI is going through your medical record and says. Ms. Brown, there's another 20 patients that are, fit her profile, and if you send her home today, she's gonna come back by tomorrow in the next 10 days. And then to be able to use predictive analytics and say, you know what? My clinical gestalt missed XYZ. You know what? The AI is right on this one. I am NOT gonna let her go home yet.
Harvey: 00:27:12
I need to make sure I address these factors, and then I'll let her go. I was like, wow. I'm helping her. I'm giving her better care, and so that makes me really excited. And then the last is on the personalization part. Man, AI can take huge information that our brains can't handle. If I did a genetic makeup of what you are, and in my brain I need to figure out what your genetics and what diseases, I mean, that's a lot of information. But if I could put it into AI, And
Harvey: 00:27:37
help me create a better personalized medicine for you than man. That's amazing.
Hanh: 00:27:45
Exactly. When it comes to older adults, it's very personalized just because you have dementia doesn't mean your treatment is generic for all folks with dementia, right?
Harvey: 00:27:55
Correct.
Hanh: 00:27:56
And I love what you're saying is that even though you're using AI, but the key of it is you're using it to enhance or augment. Yourself, right? So it's to improve yourself. But nowhere does it replace your skills, your expertise and your experience. It enhances it. That based on what you explained. So that's awesome because I think that's one of the fears, right?
Harvey: 00:28:19
Yeah. Its. It is. And that goes back to my bell curve analogy. Someone that has had 2030 years may have a hard time realizing a I know some of this. And that's why I'm thinking not to take away from that person or her him or her. It's a combination of the two. But let's leverage, let's leverage those 20 30 years. The other parts of this is at some point that person is going to retire. But if I can create a digital twin of that
Harvey: 00:28:43
doctor and literally download their brain and put those clinical gestalt into an A. I. Algorithm. Now that carries on to the next generation of doctors that can take that wisdom that's not going to be found in any textbook ever. And that's what I will bring to the table.
Hanh: 00:29:01
Absolutely. And you know, for the users that have been, uh, prompting in their AI system, whether it's ChatGPT, um, CLAUD, or, you know, whatever applications, all the prompts that you are instilling, typing away, in, in some ways, you are creating a digital twin of yourself, right? Yeah, people don't realize that, but that's exactly what they're doing. And there's nothing wrong with that, because due to that digital twin that you may not be aware of, it enhances your creativity, your productivity, and even your critical thinking.
Hanh: 00:29:40
Because for every prompt and output that you get, You have to take it to the next level. Whether you want to improve the output, and it requires you to use your critical thinking. So now, how has your experience leading to leading health care systems influence your approach to a adoption and health care management?
Harvey: 00:30:07
That's a good question. You know, I feel that having the understanding of medicine, understanding what it is and being in the front lines Has opened my mind to be able to really think outside the box. Let me give you an example. At one point I had my own emergency room that I owned. And one of the texts is doc, why are we going to the patient room when we know that child's broken ankle or arm? Why don't we just take them straight to get an X ray and why don't we medicate them back in the X ray room?
Harvey: 00:30:35
And I'm thinking you're right. We don't have to wait for a label to take care of a patient. Let's do that. And so having that experience of medicine has opened my mind to say, let's think outside the box. I'll show another quick props, and it's this little plushy, and it has ChatGPT. And let me explain as an administrator, knowing medicine and knowing that this technology exists. If I have a child that I have a hard time communicating, why not use the plus sheet to walk them through a scary
Harvey: 00:31:04
moment to explain to them what the MRI is going to do or what's going to happen or speak to them in their language or in their voice of a five year old. That kind of information has helped because I know the problems as an administrator. I've seen it as a doctor. Now, putting those problems and looking at AI and how fast it's moving in some solutions. I'm like, What is wait a second, let's put this technology with these problems and let's create solutions to improve health care.
Harvey: 00:31:32
And that really has given me the edge of being able to have that leadership inside that strategic vision. Um, better allocation of my resources because I'm like, Wait a second. AI can actually do these things that you're not looking at. And so it's giving me an edge for sure. And I feel like all health care professionals will have that edge.
Hanh: 00:31:51
So true. And the plus that you just described, talk about personalization to your client, your patient, right? Now you're speaking to where they are, their language, their age level, and the condition they're in, whether it's, you know, Um, you know, they're there for an MRI or something. So true example of, um, relatable. Well, that's awesome. Yeah. Now, assessing the success and the effectiveness of AI in healthcare, uh, is so important to ensure that the
Hanh: 00:32:23
value, um, and the impact is worthwhile. And there are multiple metrics and frameworks for evaluating AI performance in clinical settings. Some of the metrics, uh, could be diagnostic accuracy, patient outcomes, operational efficiency, and cost effectiveness, right? And factors, uh, like user satisfaction and workflow integration, the AI's ability to enhance clinical decision. Um, are all, um, variables. So now, developing a comprehensive and standardized metrics for assessing AI success is very challenging.
Hanh: 00:33:06
Because different healthcare settings and AI applications may require tailored evaluation approaches. So given the importance of measuring AI effectiveness, So what specific metrics do you use to assess the success of AI implementations?
Harvey: 00:33:23
You know, the, the main thing I look for is I look at the team, you know, do we have a cross disciplinary team or do we have a healthcare professional? Do we have a AI specialist? Do we have an administrator? Are they all working together? And then the second that I look at is, are they communicating? Is the right hand talking to the left hand? Are they really, and those are some of my metrics. Because if they're not regularly meeting or communicating, they're going
Harvey: 00:33:47
to start going in different angles. And they're going to start solving it differently. And then the last thing is, I look at, I do metrics where I'm testing the data. Is that algorithm, let's pretend it's supposed to fix problem X. I'm checking it. So a month from now, three months. Is this still fixing X? Or has the reinforced learning created something called data drift where now it's not solving that problem like it used to? And so we need to make sure one of my metrics is to make sure that it is
Harvey: 00:34:15
solving the problem that you bought it for, that you created it for. And that seems so simple and elementary, but at times, if you're not aware of these issues, it's going to start doing that. So all those things are so important once we're developing these AIs in our healthcare system.
Hanh: 00:34:29
Mm hmm. You know, um, I think when you say education, collaboration, synergy and developing that trust, I think that's just key in any environment. But particularly, um, the implications of health care is huge. And when it comes to, um, like AI and all the complexities and the negativity that potentially could come with it, everything that you uncovered is really key. So I think it's important that, um, these silos that we're in. Might occur in the healthcare settings. We have to remove those
Hanh: 00:35:04
silos and collaborate across. Now, do you, or how can AI be leveraged to address health disparities and promote equitable access to care? What's your take on that?
Harvey: 00:35:23
Yes, that's a tough one. You know, again, I'm going to use my ER example because I'm an ER doctor. Being able to take real time data and analyze it Is amazing. For example, if I'm in the emergency room and I see someone with diarrhea, I'm like, Oh, just another diarrhea case. But then if I'm using a I and it's networked with a bunch of hospitals and they're seeing certain cases, they can say, Wait a second. This is bad. X. This is bad.
Harvey: 00:35:51
Me. This is from this one restaurant. Now we're able to communicate. And so to answer your question is, I really think it could help us analyze the data. So data analytics, it could help us with resource allocation. So if I'm looking at my data and I'm saying, huh, this part of Dallas is underserved and we're seeing these type of cases usually from this area, then I can use a I to turn around and say, you know what? Um, we need more resources in this.
Harvey: 00:36:20
It may be there. Water quality. It may be something as simple as they don't. They need a bus route to take them to the hospital. Maybe that area code doesn't have a way to get to the hospital. They can't afford. They don't have a car. They can't afford a taxi. Maybe they could afford it. So then those things is using a I to say, You know what? This is the solution.
Harvey: 00:36:39
Creating these customized interventions. Another one is I'm Hispanic. I speak Spanish. Um, being able to give better discharge instructions, better information. So customize my intervention. So if we're saying, Hey, the iPhone will take care of it, but then my population doesn't have an iPhone, doesn't have a smart device. So then now I need to see how can I fix that? What can I do? And I AI will help me leverage and it will help me figure out
Harvey: 00:37:08
what it is that I'm doing wrong. How can I intervene? And then. That could be my solution. So if I don't speak Spanish, use AI to help me translate in real time. If I give discharge papers that are in English, let's create them so that they're in Spanish, but let's customize them to their culture. Um, someone from Spain speaks different Spanish than someone from South America and people within South America. So why not? Why create one discharge
Harvey: 00:37:33
instruction for that entire culture? Why not create different ones specific for that race, ethics, age, so that we can really talk to them?
Hanh: 00:37:44
So true. Now I'll use an example with folks with dementia because, because that's what I know. Um, dementia in Parkinson's is the, the, the, the, the environment that I live in, because my siblings and my, my parents, um, for those that don't speak their, uh, their language, their native language. And to hear their native language while they're having dementia, um, it's, it, it deeply resonates because it brings back, um, the history, the stories, and what they remember. And I think that's really important
Hanh: 00:38:15
to have the ability, um, to relate to them in that way, right? Because it's hard to read and to get them to register what you're saying. So the ability to personalize, whether it's cognitive decline or the language barrier, that's so important. Right. Yeah. Now, what, um, strategies do you recommend for enhancing AI competency and readiness among health care staff? Like what education, what and where?
Harvey: 00:38:45
Obviously, I am really big on education. So I think we need training programs, but not just anyone. We need health care professionals that understand medicine and a I, you know, a lot of these training programs. When I look at their curriculum, I can tell it was written by a non clinician and that they're teaching the clinician. So it needs to have a interdisciplinary effect where we have doctors, nurses and we're using. So we definitely need the right training programs.
Harvey: 00:39:09
We need to change our education and our continuing education and make sure that A. I. Is involved so that they understand. And again, it goes to my analogy of the bell curve. We're gonna have people like me that are early adopters that want to learn everything they can. But then you're gonna have people that are late adopters and you can't teach those two people the same. And so we need to make sure that when we're teaching, we're teaching them to their level and getting
Harvey: 00:39:29
them all to a certain level. And so what I'm saying is we need practical workshops. We need something that I can go in and, and see the good, the bad, the ugly. But then someone like me might get bored in the first 10 minutes. So we need to kind of, all of us educate ourselves at certain levels. So what I'm saying out there is, We need to make sure that you're following people in health care like I follow you on LinkedIn. I'm learning from you I'm learning from other influencers And so that's
Harvey: 00:39:56
what we need to do is that continual mindset of learning forever to continue to say, you know what? I'm learning from dr. Castro, but i'm learning from miss brown I'm learning from all these experts and we need to create that culture and we need to instill it into the hospital system So that we'll continue to learn
Hanh: 00:40:11
Absolutely. So true. I love that you keep saying the word learning and open mind, lifelong learning, because we're in that place right now. That's period. We are in a place that we must adopt this everyday learning, adapting, opening your minds and trying new things. And the thing is, when you try new things, chances are it may not work for you the first time. Because even earlier on, when I was trying to prompt Well, you know, I wasn't so good.
Hanh: 00:40:39
I did not get the output that I was looking for. So it's not the tool. It's not the AI. It's your ability or inability to prompt. But you got to practice and practice and practice and after thousands and thousands. You know what? I've increased my efficiency quite a, quite a bit because I'm better at prompting. So I think part of the learning is very humble to know that you may not get the results that you want to get right away.
Hanh: 00:41:06
There's humility and there's keep pressing on and a childlike attitude and that's okay and that's what's exciting about where we are right now. Yeah. So that's great. So now how do you ensure. The quality, security and privacy of healthcare data used in the AI applications you described?
Harvey: 00:41:33
Yeah, number one, uh, obviously data encryption. Um, I'm becoming really good friends with our CIO and those individuals to make sure that our data is safe. Um, that's why I gave that suggestion earlier. It makes sense to me to have that large language model. On our hospital servers that it's encrypted that we know are HIPAA compliant that we know that the there's strong access control so that not any user can walk up to any computer and just log in where those access
Harvey: 00:42:00
controls are strong in the hospital. We got to make sure that those are going on. We're Continuous monitoring of who's logging in and what data is using. You know, this is an old example. But when I was in med school, I had a really famous person that came to the hospital and all these medical students were logging in to that patient's record because they wanted to see why they were there. And so being able to have that strong compliance monitoring to make sure that we're Regulating
Harvey: 00:42:24
who has access to that data. And then where's that data going? Is it going to chance you PT? Is it staying in our hospital servers? Is that data secure? And so that's a whole other hour talk that we can have on data security, but that's a very good question.
Hanh: 00:42:39
Yeah. Well, thank you. Well, here's a big one. Burnout. It's a growing concern in the healthcare industry. Now, studies show it can lead to decreased shop, uh, job satisfaction and reduce patient care quality. It can even lead to higher rates of medical errors. Um, so as healthcare organizations seek solutions, some researchers have begun to explore AI's potential in alleviating physician burnout.
Hanh: 00:43:08
So now, do you think, or what's your take on AI power tools that could help streamline clinical workflows and reduce AI burnout administrative burdens? Um, could it support clinical, uh, making, uh, decision making processes? And, um, I mean, we all know, at least from the outside, and you see it more, uh, day to day, there's AI based systems for documentation assistance. There's image analysis, patient triage, uh, could save physicians time and effort. This, uh, would allow them to focus more on direct patient care.
Hanh: 00:43:45
But the role of AI in addressing physician burnout is still an emerging area of research. There's concern about the potential unintended consequences, uh, it includes increased technology dependence. Transcribed And a need for more training. So a lot of complexity. So considering all the potential of AI in this context, do you believe that AI can help alleviate? Physician burnout. And if so, how do you envision a I being leveraged to support physicians?
Harvey: 00:44:18
Oh, gosh, I love this topic. So.
Hanh: 00:44:20
That's a giant.
Harvey: 00:44:21
Yeah. That's a big one. I love this one, though. So let's start with administrative automation. You know, if I'm speaking to you. And I'm catching your eye twitching, your subtle movements. Why not use AI to give me that information of this conversation? So it's transcribing it. But if my computer is over here and I'm typing and I'm looking at you every other sentence, I may be missing. A lot of information and and I
Harvey: 00:44:46
may I have a story of a physician that I hired and he couldn't type. He would type with two fingers and he would literally stay three hours after work and we would work 12 hour shifts and he would say 15 hours because he was trying to keep up with the paperwork. Why not use AI? And he was one that he's like Harvey, I'm ready to retire. But now with a I able to transcribe this conversation. Yes, you can hire another human to transcribe it. We didn't have that.
Harvey: 00:45:16
And so being able to have a I create these automations huge. The other one is mentioned earlier the decision support two in the morning. I'm a tired using a I to help catch things. Give me a better care for my patients. Amazing. We talked about the predictive analytics, you know, but the one that I it's a little controversy when I say is, I see a future where robots are going to come to play and I know people like oh my gosh, he's talking about robots I do I I see a future where say I had a robot next to me and
Harvey: 00:45:45
i'm taking care of miss brown And i'm saying hey, um, what is her hemoglobin? I want to see and based on your voice it's analyzing your voice and saying oh her sugar is this Or it's saying to me. Hey doc when you were examining her I noticed you didn't look at her ears and because of what she says, that's an important part of the exam. You need to go back and check her ears. And I'm like, Oh, thank you. Or what about my, my nurses that are really have bad backs because they're lifting all these patients. But if I had a robot to
Harvey: 00:46:16
say, Hey, help me with Ms. Brown, she needs to go to the restroom. Can you assist her? And now my nurse is like, you know what? I'm not going to retire. The robot is doing all the heavy lifting because physically I'm about to retire because I can't go anymore. So I really think this is going to be a huge solution that we're going to start seeing in healthcare.
Hanh: 00:46:36
Wow. Bless you. And I think you're right. And we just are excited to be a part of this, this day and age, right? It's so exciting to live and learn and grow along with the AI integration in our business life, but also in our home life, because it's like electricity in my mind, right? It's going to infiltrate every aspect. I don't know what part of life it's not going to affect.
Harvey: 00:46:58
Yeah.
Hanh: 00:46:59
Yeah. Yeah. So what advice would you give to healthcare professionals, um, that are wanting to navigate in this system? There's something going on with my Can you hear me?
Harvey: 00:47:20
Yeah, you sound great.
Hanh: 00:47:21
Okay.
Harvey: 00:47:22
Yeah.
Hanh: 00:47:22
I can't see you anymore.
Harvey: 00:47:24
Oh, I see myself, and I see it going so maybe she'll log right back in and so then I'll answer that question as soon as you get back. But to repeat it for everybody else that's able to hear me because I know we're live the question was what advice Um, would I give other health care professionals or students looking to contribute to AI health care? I believe is what she said. And number one, I would say, let's stay informed. Number two is let's develop our skills and then number three is let's collaborate
Harvey: 00:47:59
and then number four Is let's make sure that as we move forward, let's move forward ethically And so when I say stay informed follow, uh, miss brown here follow me follow other experts Um, if your hospital is resistant to change Then share this type of video with your hospital administrator. Be that advocate. If you're actually listening to this, that tells me that you're wanting to learn more. So pass this knowledge, whatever we gave you today to the next person next to you to improve.
Harvey: 00:48:25
And so let's collaborate together so that we can make a better workforce, a better tomorrow for healthcare.
Hanh: 00:48:31
Awesome. Well, thank you so much. I mean, I'm, I'm very blessed to be a part of this conversation, and I'm so thankful that we are in the age of AI, that we can share and we can learn from one another. And it doesn't matter where you are in this journey. We're students. We're students of, um, AI, of large language models, of all these applications that are coming out. So feel free to reach out, to follow Dr. Castro, to myself. Ask questions.
Hanh: 00:48:59
We're going to ask you guys, uh, gals questions as well. And to Dr. Castro, thank you for your passion and expertise and your vision for the future of healthcare is very inspiring. Your journey from practicing medicine to becoming a strategic advisor for GPT in health care is a testament to the transformative power of curiosity, innovation, and the relentless pursuit of better patient outcomes. Throughout our conversations, you've shared invaluable insights into the challenges, and And opportunities of
Hanh: 00:49:30
AI adoption from ensuring clinical alignment and data integrity to fostering collaborative environments and addressing ethical considerations. So your comprehensive approach to AI integration is a road map for success and your real world examples of AI's impact on patient care is very powerful. And your strategies for preparing health care staff. For the AI revolution. Very practical and your commitment to leveraging technology to address health disparities and promote equity is admirable.
Hanh: 00:50:10
So these are all reminders. Of the immense potential that lies ahead into the folks that are listening, watching. I encourage you to embrace the insights shared by Dr Castro today and our conversation. So whether you're a health care professional, a student, or simply someone passionate about the future of health care, it's never been a moment more exciting time to get involved in the AI revolution. Imagine a future where AI and health care professionals work hand in hand.
Hanh: 00:50:47
A future where personalized, efficient, and equitable care is provided to patients worldwide. Where data driven insights guide clinical decision making. Where physician burnout is alleviated. By a I power support system and where health disparities are addressed through innovative technological solutions. Well, this future is within a reach, but it will take collective effort to make it a reality. It will require visionaries like Dr Castro, healthcare organizations, a I developers.
Hanh: 00:51:23
And individuals like you. So I ask you, what role will you play in shaping the future of healthcare? How will you contribute to the AI revolution that promises to transform lives and improve health outcomes across the globe? So the path ahead may be challenging. But with the guidance like leaders, like Dr. Castro and the passion and dedication professionals like you, we can create a healthcare system that harnesses the power of AI to provide exceptional care to every patient every time.
Hanh: 00:51:59
So thank you, Dr. Castro for sharing your wisdom and inspiration with us today. And thank you to our listeners for joining us to this exciting journey. So together, let us heal with data. One bite at a time, take care and thank you for your attention.
Jennifer: 00:00:05
Being willing to embrace failure with a smile on your face. These are the times when you are going to learn the most about yourself, um, things that you like, things that you don't like, maybe in the career that you think you want to pursue. It's okay if you don't like every aspect of the role that you're seeking, find out what motivates you. What you're passionate about. If you're passionate about it, it's not going to seem like a job and it should always keep you curious and wanting to constantly learn,
Jennifer: 00:00:35
but learn from your failures.
Hanh: 00:00:42
Hello, I'm Hanh Brown. Welcome to AI 50, where your data meets innovation. We harness cutting edge AI technology to develop and deploy advanced language model applications. These applications are tailored specifically for the 50 plus demographic. Our goal is to meet the unique needs and preferences of this important group. So now, picture this. You're the CEO of a mid size manufacturing company, and you've been grappling with the inefficiencies in your production process.
Hanh: 00:01:19
Despite your best efforts, you can't seem to pinpoint the root cause of the problems. Well, that's where Jennifer Bradshaw and her team at NLP Logic come in. As the director of product at this leading AI consulting firm, Jennifer has helped countless businesses harness the power of AI to transform their operations. So today, we have the pleasure of speaking with Jennifer about her journey from product development to AI consulting and how her expertise is revolutionizing industries. Thanks.
Hanh: 00:01:56
So get ready to be inspired and discover how AI can take your business to new heights. So Jennifer, welcome to the show. Hi there. Thanks for having me. Yeah, well, welcome. Thank you so much for your time. So to get things started, could you share an interesting fact or a story about yourself? That many people might not know.
Jennifer: 00:02:22
Well, maybe if you've looked at my LinkedIn profile, you might be able to tell this, but I actually didn't start out in technology at all. I went to school and got my bachelor's and master's in teaching. So I am qualified to teach, uh, grade school children and also be a reading teacher. That's my background.
Hanh: 00:02:43
Nice, nice. Okay, well, now you started out developing products at a company and then you transitioned to delivering AI power solutions as a consultant at NLP Logic. So what inspired you to make that change?
Jennifer: 00:02:59
I think the constant need to learn. I love product. I love the product mindset and building things with purpose and watching where the world is going. AI was never going to take a back seat. So I wanted to make sure that I was constantly staying up to date and working with cross functional teams. So that I'm always staying educated on the latest and greatest so that we can truly define the best solutions for our clients.
Hanh: 00:03:26
Mm hmm. That's fascinating. So it's clear that your experience in both areas has shaped your perspective in the industry. How does NLP logic ensure that each client Receive the customized solution, um, that addresses their specific pain points?
Jennifer: 00:03:48
Yeah, that's a great question. And we know that every client believes that their challenges are unique, but the reality is that most business problems share a common thread. So we listen. And we listen without solutioning. That's the very first step, but we are then able to pull from our experience. And our goal is to not reinvent a wheel. So if we have the experience in solving the problem, we are pulling from that tool chest of the past. And we're making sure that we are delivering faster and faster.
Jennifer: 00:04:19
So once you've proven the strategy and you know that these solutions work, it doesn't matter if the industry might be adjacent to the one that you're working in. Business problems happen to be business problems, so it's pretty easy for us to be able to find that common thread and common solutions to implement. Now, I will say there are times where there is the need for a custom build where we're going from the ground up. But most of the time, that's when a customer is trying to build an enterprise, you know, software as a service solution that involves the customer.
Jennifer: 00:04:51
They're unique business as well as process automation.
Hanh: 00:04:56
That's very true. And we talked a little bit before our event is that I can't imagine any aspect of, um, industries or any aspect of your personal and my personal life that is untouched by AI, right? It's infiltrating in all regards. And I actually, we've all experienced AI throughout life over the last 10 plus years, but it's always been in the background. For example, search. We've all searched on Google. Nowadays, maybe it's not so Google. It could be perplexity.
Hanh: 00:05:25
And we've all, um, also have shopped and all those recommendations, right? So it's always been in the background, but nowadays it's right next to you. It's your co pilot. It's your assistant that is truly personalized. Uh, if you know how to set things up and, and, you know, with all the advancement and the speed of change over the last weeks and months with GPT 4. 0, I feel like, wow, you know, multimodal. text, audio, and speech. It's, it's changing. And I know it's slowly, um, deploying
Hanh: 00:05:59
that, but when it's here, especially audible, that's going to help so many folks like for myself, like folks, um, the, the demographic that I'm most close to is folks, let's say with visual impairment, with audible, uh, impairment, or even that may not know how to type or don't type, type well and so forth. So I think that's awesome. So, um, so now. It's, it's clear that understanding the, um, the client's unique challenges is a top priority for the team and that you try to, uh, keep that process in place or standardize as much as possible.
Hanh: 00:06:42
Make sense? Because I think AI allows you to do that. So now, um, in doing so, how do you build strong relationships with your clients? To navigate the complexities of AI implementation because I think people are at different levels of understanding and adaptation, right? Um, not everybody's in the same place. We got people that are still hesitant, fearful and people like you and myself. Who are fully engaged. So how do you address that?
Jennifer: 00:07:16
Well, I mentioned before listening and listening without solutioning. It's really, really important to establish the relationship with the client and to establish the trusting relationship. And my actual teaching background. This is where it's helpful because through every conversation we are educators for our clients. Our job is to demystify AI. We don't want them thinking that it's just this magic wand that you can wave. It will solve any problem. And that comes with being very
Jennifer: 00:07:44
transparent with your communication. So I think with that combination of being an active listener, restating what you hear to make sure that you're taking any assumptions off the table. And then educating it as you go along, don't allow the clients to make their assumptions on what a solution may or may not bring them. You have to have the open and transparent conversations. That means being honest about the limitations that the solutions might bring. So level setting the expectations during
Jennifer: 00:08:12
the education is an absolute must. And I think for us, NLP Logix. Can say we have very strong ties to our customers and we ensure that our open communication goes both ways. We're accepting the feedback from them. If they don't happen to like what we might be telling them, then we truly are working together to get them on the right track and achieve the goals that they really ultimately want to achieve.
Hanh: 00:08:42
Mm hmm. Mm hmm. Cause I think the end of the day, it's about, um, enhancing their businesses, whether it's in terms of. Um, process, uh, workflows or getting more clients for your business, uh, for your clients, for instance, it's, it's about growing and what better time to do that right now. So can you share a success story where your AI solution significantly enhanced the client's operational efficiency?
Jennifer: 00:09:14
I would love to. Thank you for asking. Um, we have a healthcare company that hires highly skilled professionals to review cases and charts. And previously it would take one of these professionals about 45 minutes to review a chart. And now once we deployed our RPA solution, that time went from 45 minutes to just about 25 minutes. So they've been able to scale their business substantially because of the gains in the process. But that we also had another
Jennifer: 00:09:46
medical billing client. They were about they were producing about 25 to 30 different claims a day. And that went up to about 75 after we deployed the solution. So everything that we have done from an operational efficiency standpoint has really allowed our customers to expand their business.
Hanh: 00:10:07
Hmm. Awesome. Congrats. So it's not just speed. It's about accuracy. It's about, uh, growing their business with more clients, like we would discuss. So those are solutions that I tell you nowadays, it's very possible to be exponential. So, um, all right now. So what are, um, the most common challenges, uh, businesses face when integrating AI and how do you help them overcome these obstacles?
Jennifer: 00:10:40
I love that question. Um, I think mostly knowing where to start. It is seemingly Mount Everest that they're trying to climb and they aren't sure necessarily if they should sprint right out of the gate or if they should walk and start to get the landscape in the lay of the land. So it's really important for us when we're establishing relationships with customers to understand what is the North Star. So that we can try to help remove those hurdles and overcome any of the, uh, um, stigma when it comes to adopting a I. So we want to make sure that
Jennifer: 00:11:15
we're having the crawl, walk, run conversation and all in alignment to what their strategic objectives are. So if you take the a I conversation off the table, just have a business objectives conversation to start. It's always disarming for the clients to understand, okay, this is just about enhancing our business. We typically want to make money or save money. Those are the two main buckets, right? And make people happier, have a better onboarding experience and make our humans more effective at their jobs.
Jennifer: 00:11:49
Um, so when we give the clients that North star, which is just their business objectives, then when we start talking about the pain points and we start talking about the opportunities that make sense for AI to solve, then we can start showcasing them. Hey, this is some low hanging fruit. You might be able to automate a particular process within your organization and free up 20 to 25 people from having to do a mundane task. Then we can start to showcase the advantages of achieving their goals. With augmenting humans with Ai.
Jennifer: 00:12:26
So it really helps, I think, reduce those hurdles because you're laying a foundation that they can crawl and then they can walk. And then they eventually, once they're walking, they definitely want to sprint to that finish line and use all the really cool technology to help grow their business. But we put that path that plan in place a road map, if you will. And that's been working quite well, starting from the basic conversation of their business objectives.
Hanh: 00:12:54
That's awesome. You know, it makes sense because you, you have to, the, the, the business owner needs to know what are their goals for the year? What are they wanting to achieve? And then along the way, what is your workflow? How do you plan to achieve that? And then as you uncover in the conversation, Uh, this is how I do it, and here, potentially, here's a roadblock that I would love to remove. And then you explore what AI, uh, opportunities to integrate, uh, because
Hanh: 00:13:24
AI is not for everything, right? Um, it's not, but it's a lot. And when you hone it in properly, I'll tell you, it exponentially can save you, like you say, a You know, from hours maybe to, you know, like one or two as opposed to 10, let's say, um, so yeah, I think it's great. I think it's great to, um, walk on that journey with the business owner and encourage them along the way. And my, my recommendation is I start small, like once you identify your pain points, prioritize what's important for you, top one or two or three, start with
Hanh: 00:14:01
something that that's doable and it's small so that you can gain confidence.
Jennifer: 00:14:05
Exactly.
Hanh: 00:14:06
Yeah.
Jennifer: 00:14:07
It helps build and establish trust within solutions as well. When you see success with that smaller solution.
Hanh: 00:14:16
Right, right. I agree. So now, how do you ensure that your AI solutions are developed and implemented in an ethical and responsible manner?
Jennifer: 00:14:32
Everything has to be explainable and transparent. So we have extremely open communication with our clients and we are consistently monitoring all of the models that we're deploying before we put it in to production. When we're testing, when we're training, we're constantly reporting out what our findings are where we may have made adjustments, um, but we also have to educate. As well, because there are things that we might not be able to do. There are limitations.
Jennifer: 00:15:00
And so in order to ensure that we are being responsible, we have to educate the customer directly on what the limitations might be. And just that constant monitoring and making sure that it's, there's really a dip in performance and it's not just an outlier. So the model health. After the fact, after a solution is deployed to production is conversation that we constantly have with clients, even in the upfront build process. A lot of organizations believe, okay, we're doing things
Jennifer: 00:15:34
in a transparent manner. We're able to see the decisions that the model is making. We're able to explain it. And then they believe it stops there. Once we're in production. It's working. It's fine. We don't need to check in on it. But the model can degrade over time. Things might need to happen. We might need to retrain, or maybe we just got a batch of data that doesn't belong. So when we're educating our clients during the build, we're trying to help
Jennifer: 00:16:02
them understand that things can change. Today doesn't look like yesterday and it may not look like tomorrow. And so if data changes over time, the solution might need to change. And I think that takes a bit of education. Um, but for us, I think it is the cherry on top of how we are consistently remaining ethical and responsible with the use of AI.
Hanh: 00:16:24
That is the only way, right? Um, no, that's great. No, um, the model, like you were describing it, it evolves. It's never static because we're continuously fine tuning. And adding to the knowledge base, right? So I see that is, um, like you said, it never ends and it should not, right? And it's a, it's a, it's a process to include your client as part of their domain, um, expertise, right?
Jennifer: 00:16:50
Right.
Hanh: 00:16:50
Yeah. No, that's great. So how do you help clients prepare their workforce for the adoption of AI technologies? Those are tough questions.
Jennifer: 00:17:00
It is, it is. And we hear it quite a bit. Um, there's a lot of fear around it, and you always hear that word replace. Replace, we're going to be replaced. Um, and this is where the education comes in. So typically when we engage with a client, at first, we are offering up an AI education session. This is the demystification of ai. What are the appropriate uses for ai? What are the not so appropriate uses and also what are some of the out of the box things that already exist within
Jennifer: 00:17:30
their current technology stack, you know, microsoft copack copilot, how might that integrate into your life and make you a more effective human. So we're trying to have conversations with our clients right off the bat to show them that. You don't necessarily need to go this full blown custom build. Your employees aren't going to be replaced. Our goal is to make them more effective and help them achieve the strategic goals, elevate them, upskill them, reskill them so that they can go and
Jennifer: 00:18:04
do bigger, cooler things, and hopefully be more happier in the long run. So I think ensuring that our clients really understand AI is not meant to necessarily replace the human, but to make them more effective, get them excited, get their leadership bought in. And I think we have a much easier path forward in helping to take away that fear and anxiety around the unknown with AI.
Hanh: 00:18:31
So true. It helps you get back to the soul of your work as opposed to being tied up with it. Like I find myself get caught up in whether it's email or whether it's sorting through things and organizing. And that was the first thing I try to tackle on is how do I organize, whether it's my day or my task to give me back, you know, a couple hours, right? And I found out that these couple of hours I can actually do things that I enjoy. Yes. So that's how it has affected, you know, me personally.
Hanh: 00:19:03
So that's great. So now what excites you most about the potential of AI in transforming businesses across industries?
Jennifer: 00:19:15
The thing that I keep coming back to is the potential that it's going to unlock in humans where it's already unlocking the creativity. Time and space create a world in which people can be curious and they can consistently learn and they have that passion to do bigger and better things when we get bogged down with the mundane tasks. How excited are we to go and upskill ourselves? How excited are we to go and try to find the time to learn something new? So I believe that we're going
Jennifer: 00:19:51
to become much better humans. We're going to become smarter, and we will absolutely know what efficiency means. Not only in our body. business life, but in our personal life as well. So I'm really, really excited to see how we evolve as humans because we have become more effective. Thanks to AI solutions.
Hanh: 00:20:13
Mm hmm. I agree. Like personally, I feel like I have to become a better prompter for instance, and that's like fine tuning your output on going. And I feel like after thousands of trying, I'm actually pretty good. But what it does, it helps you become more, um, well, a better prompter and it, uh, increases your, uh, critical thinking, right? I mean, they go hand in hand. You can't be a good prompter without utilizing, uh, your critical thinking.
Hanh: 00:20:42
So all in all, at least personally, I really think it's enhanced me as a, an individual, a professional creativity and productivity in all regards. So I highly recommend learning, adapting, uh, but just like anything, you know, adapt it with enthusiasm, but with caution because I also see folks, um, misuse. I mean, it's, um, it's real and, um, so that's, that's kind of my attitude when I try to share it with folks is, um, Proceed with enthusiasm, but with caution and then look at it from your own personal life ways that you can improve your, I think the key is upskill, right?
Hanh: 00:21:24
That's a very common key right now. A common word. Definitely. That's, that's important. So let's talk about data, right? The feel of AI. That's what data is. Now, how do you help clients? Harness the power of their data to drive effective AI solutions.
Jennifer: 00:21:47
Great question. So we love talking to clients and geeking out on their data and many clients really have a great understanding of their data, but we really like to tell that untold story. So this is during that give us access. We want to check signal. We want to see what your data can tell us. They're going to always come to the table with what they believe the data is saying, but it's always awesome when we get to tell them the things that they didn't know about it because this is what's unlocking the different
Jennifer: 00:22:19
needs and potential for AI solutions. So we like to, again, go back to what are you trying to achieve and then map their data to see, can we actually achieve it in the current landscape? Okay. So there are plenty of times where we've actually needed to collect different pieces of data to make a solution more effective or more efficient for a client. And we wouldn't have known until we dug in and started analyzing the data and potentially running some assumptions through. Our experimentation and then we go back
Jennifer: 00:22:50
to the customer and we share with them exactly what we've done, why we did it. And again, trying to get that alignment to their core objectives and then telling them we might need something different, or this is a good crawl. Let's start here. And then let's start capturing this particular data element so that. We know what the walk is going to be. This is your kind of AI roadmap, if you will, by getting this new entry, new data introduced. So everything is a matter of what that data tells us the right
Jennifer: 00:23:24
solutions that we're going to pick because of what that data tells us. And it goes back to that road mapping so that we know what the data is going to get us to the ultimate objectives on their roadmap.
Hanh: 00:23:34
Mm hmm. That is so true. Do you find it that clients are amazed what data signifies or what it comes with, whether it's unstructured or structured? Um, that's, that's in my mind, that's still hard for them to grasp what all that data entail. What's your experience in that?
Jennifer: 00:23:51
Yeah, I agree. I think they believe, every client believes they have great data and they haven't. access to great data. Um, I don't think they realize sometimes the limitations that their data brings to the table and maybe it isn't as accessible and it isn't as understandable as they believed it to be just because they're able to get reports from it doesn't necessarily mean the data's giving the right information for the solutions that we're going to have to put in place. So I think there's always a little
Jennifer: 00:24:23
bit of that tension when we're trying to Re explained to the client, just what their data says and the limitations that it does have. And then I think it opens up their minds to the potential for other solutions as well. Cause it starts to, it's like Pandora's box. Once you start digging in, you are going to uncover so much. And then I think the clients start to realize, Oh, okay. You're not just in it to use cool technology and say, you've built
Jennifer: 00:24:56
these flashy solutions for us. You're actually coming to the table with a problem and you're telling us we have some limitations, and you might not be able to solve that problem. How do we move past this? What do we need to do? And that's where that, that teamwork and that collaboration and that trust that we established in the initial part of that relationship is really important to us at this point in time. Because if they trust us, they're going to believe us as we're leading down the journey of how
Jennifer: 00:25:22
their data might need to change. We have implemented data lakes for customers because their data was spread across the board and so many different systems and they did need a place where it could live structured and unstructured. And so we've had to say, we understand, we know what you want to achieve right now. But we'll go after the low hanging fruit. We might be able to do a couple of POCs, but now let's really focus on getting your data to a workable standpoint where you are set up for that big roadmap and being able to achieve your strategic goals.
Hanh: 00:25:56
I love that you mentioned data like there's no better tool than consolidating, cleansing and organizing and having all of it in one location in the cloud.
Jennifer: 00:26:07
Right.
Hanh: 00:26:07
And then the potential is great. You know, it is. Uh, we, we talk about how we have inoperable data, but it's, it's segregated. And it doesn't communicate, right? And I think that's one of the key benefits of AI is that you got to have an ecosystem, an ecosystem that speaks to each other and data like is a good start.
Jennifer: 00:26:29
It is.
Hanh: 00:26:29
Per view and fabric and so forth. So that's awesome. Now, measuring AI's impact. So what metrics, um, do you use to assess the success and ROI of your AI implementations?
Jennifer: 00:26:48
It is so important to understand current state. So we spend a lot of time understanding what does the current workflow look like? How long does it take the humans to perform the current task within the workflow today? What are the obstacles? This is really where the success criteria starts to be captured because we're understanding how they're measuring today. And then we dive into what does success look like in the future? How do you intend to measure this? And obviously we're going to be highly
Jennifer: 00:27:18
opinionated because we've, we've watched this happen time and time again. So we start throwing out the different measurements. If they're not measuring today, What we see and really it's if there's a cycle time, if there's a start in a finish to a process, we should be calculating how long it takes in the current state so that we can understand if we're deploying an AI or ML solution, we then know we can measure. A decrease in time. That should be the ultimate goal is to see that decrease in time. And it could also come down to accuracy.
Jennifer: 00:27:50
Maybe the time doesn't matter. So if we ask a customer, what do you do today? How are you measuring it? They could say by the accuracy. We can't make a mistake in the documents that we're processing. So we, it's a very important metric to track the KPIs on how frequently there might be an error within document processing. Okay, so we know current state, what can the error rate be for future state? What are you trying to get to? You're trying to get to that 100 percent
Jennifer: 00:28:18
perfection is 99.8 percent acceptable. So it really depends on how they're measuring things today and how they want to measure things tomorrow. So it could come in a variety of different measurements, but that's always one of the initial conversations that we're having, especially when we're going through that current state review.
Hanh: 00:28:40
Very true.. Measuring the impact of the ROI of AI, um, it's so important that allows you to justify the investments, right? Right. Um, because it's um, it's one of these things if you can't measure how do you know you're improving and if you're not improving, why are you paying for it? Right. Exactly. Yeah. No, it's so true. So let's talk about AI and customer experience.
Hanh: 00:29:11
So how can businesses leverage AI to enhance their customer engagement and satisfaction?
Jennifer: 00:29:18
I think a lot of it comes down to personalization. I think as humans, we like things to be tailored to us, our unique humans. So when you're shopping online, it's really nice when you get those handy dandy recommendations on products or services that you should be purchasing based off your prior purchase history. So I see things moving more in that direction as well. But think about where you could get recommendations and when you can get recommendations. It feels like AI is so
Jennifer: 00:29:44
accessible right now. And then if we talk about edge AI, having AI on your own personal device, think of the world that that's going to bring in the personalization of the contents that you can receive from different venues. And I also think of bringing information. To people when it's most necessary. So if you go to a call center, they're typically open Monday through Friday during normal working hours. When the majority of us are also at work, but think about being able to call on a Saturday on your day off, and you're still getting a very similar
Jennifer: 00:30:21
experience and getting the information that you need for your current situation. And you don't have to call during normal business hours. So on top of personalization, I think, you know, Accessing information more readily and I do see because I use chat GPT almost like a personal assistant or a virtual assistant at times. So I see AI being able to improve the customer experience. If you're moving towards more virtual assistants, you know, we see a lot of organizations who want to have that white glove service for their customers.
Jennifer: 00:30:57
And I think AI makes that. More tangible and takes what they believe to be great customer service. And it just brings it up a level because you're now going to bring that personalized virtual assistant to the table.
Hanh: 00:31:10
Mm hmm. Everything that you mentioned, those are key, uh, characteristics of enhancements from AI. So I think it's, it's awesome. You mentioned about accessibility, my gosh, 24 seven. You know? And, and not only, um, it helps you make decisions, but I, I think another component, uh, in terms of folks who are, let's say, 50 plus, 60s and 70s, it's empowerment. Oh, for sure. I always think of it as empowerment.
Hanh: 00:31:35
It's like you make better decisions when you are empowered.
Jennifer: 00:31:39
Agreed.
Hanh: 00:31:39
And, um, yeah. That's exciting. Yeah, that's great. Now, balancing innovation and practicality. So how do you strike a balance between pushing the boundaries of AI innovation? And then ensuring practical implementation solutions for your clients?
Jennifer: 00:32:02
Right. And I think that really comes down to, we have to listen. We have to listen to our clients and truly understand their needs. There are many times that clients will come to us and they will ask for a specific solution. And one of the first questions out of our mouths typically is why? And then what are you actually trying to achieve? And so trying to get to the root of the problem. Is really going to help you understand
Jennifer: 00:32:28
what the client is trying to achieve and again, taking it back to what is your organization trying to achieve strategically so that we can try to piece the story together. It's not that we don't want to take our clients word for it. We want to trust, but verify. And so while they might want to come to the table and say, we need to implement a gen AI solution, and we have to do it within 2024. Okay. Help us understand why, what are the benefits you're trying to get out of it?
Jennifer: 00:33:00
What are your company's objectives? And if we were to bring to the table a different solution that might get you there eventually, but we just see a much bigger need and we might be able to. Put a solution in place that doesn't take much time at all and then starts to build that trust within your workforce or your end users. Would we be able to propose such a solution? Nine times out of a 10, the customer is always going to come back to us and say, please tell us, tell us the path to walk down.
Jennifer: 00:33:30
We don't want to just use the shiny cool new toys because they are available. Sometimes it's pulling out the traditional tools that have worked for decades and that really helps get them on the path forward. So again, it goes back to listening and really understanding your client's needs.
Hanh: 00:33:46
And you certainly don't start with a solution or a product, right? You start with the goals, objectives, what the clients are trying to achieve for that window of time. How do they plan to achieve it? What workflows are they doing right now? What is not meeting their timeline or their goals for the year? And then you kind of carve out what's going to work best. Right. We discussed this, you know, it's not a solution. AI is not a solution to everything.
Hanh: 00:34:14
Right. And, um, but no, those conversations that you have, it's so important. It's patient. It's, uh, it's, uh, understanding their mindset coming in and understand their workflow and their goals. So, well, that's great. That's great. All right. Um, now fostering an AI ready culture. Another tough one. Yeah. Um, what advice do you have for businesses looking to create a culture that embraces
Hanh: 00:34:43
AI adaption and continuous learning?
Jennifer: 00:34:46
I think it's important to constantly promote the human and AI collaboration. How do we as humans interact with AI so that we become more effective? And I think it's taking away some of that fear. And replacing it with curiosity, and so I think people are then a little bit more accepting of what I might be able to do for their organization. If you stop talking about it from a is going to come in and completely replace this particular workflow. It's human and collaboration.
Jennifer: 00:35:22
I think that we have to consistently talk to our clients about.
Hanh: 00:35:28
That is so true. I mean, do you think the AI is more like a GPS? It kind of guides us, it gives us options, it uncovers information that perhaps we didn't know. So it's kind of like the GPS. But we're the driver, right? We steer it. We provided input, uh, data and so forth. Right. So it's, it's collaboration of the two. I don't see one replacing the other.
Jennifer: 00:35:56
I completely agree. And I think we're always reminding our, the executive level of the clients that we're dealing with, that they need to promote that from within. Yes, we're an outside consultancy and that could come with some credibility, but if the C levels are not on board and they're not promoting the human and AI collaboration throughout the organization, this is where we see we hit a little bit more friction when we're trying to operationalize AI solutions in production. So my advice definitely is ensure if you're going to embark upon this
Jennifer: 00:36:30
journey and you're going to augment. Your business objectives by implementing AI solutions, you have buy in from the top. And sometimes that means they need to be educated just like the rest of the workforce.
Hanh: 00:36:44
So true. If it doesn't start from the top, I'll tell you, uh, the folks under maybe using AI, but maybe hiding it, for example, and they're really not fully reaping. Um, all the benefits. So you're right. It starts from the top. It starts with a cultural, a paradigm shift, um, education and promoting it as a collaboration instead of a replacement. Right? Right. So no, that's great. Now, how do you foster collaboration
Hanh: 00:37:10
among your own team, um, team members and with your clients to drive success in your various AI projects?
Jennifer: 00:37:19
So, NLP Logix has a phrase, and we have it painted on our walls, we have it within our slide decks, and we share it with every client that we talk to. "Data science is a team sport", and that is not just our internal teams that we're calling a team. We are a team moving towards a common goal with our clients, so we embrace them. We pull them in there in our internal meetings. They're listening to our daily standups and our progress. They're watching us hit the bumps in the road and openly talk about
Jennifer: 00:37:52
what we're going to do to mitigate a risk within the projects and the solutions that we're implementing. So being completely transparent, I think, and that open communication gives you your camaraderie within your team. It's building that trust. Why would we have a very, what could be a private conversation to NLP logics directly in front of our customer when we know it might make them a little bit uncomfortable because if they're watching how we work. They're going to watch how we get through the tough parts.
Jennifer: 00:38:26
And if they have faith, they're going to come right along with us. They're going to be on this journey with us and we will navigate. We've done this before, hundreds of times, and we just want to make sure that everyone understands there will be bumps in the road. But if we're doing this together and we're being very transparent about it, we really can over, we can overcome anything. Just be direct.
Hanh: 00:38:48
That's so true. There'll be many difficult. Um, conversations, right? But there also will be some big rewards. So those difficult kinds of conversations, uh, will uncover so much. So that's great. Now, what advice would you give to entrepreneurs or professionals looking to build a career in AI solutions?
Jennifer: 00:39:16
I think being willing to embrace failure with a smile on your face, this is, these are the times when you are going to learn the most about yourself. Um, things that you like, things that you don't like, maybe in the career that you think you want to pursue. It's okay if you don't like every aspect of the role that you're seeking, find out what motivates you. What you're passionate about, if you're passionate about it, it's not going to seem like a job and it should always keep you curious and wanting to constantly learn, but learn from your failures.
Hanh: 00:39:49
Mm hmm. Mm hmm. So true. Well, we're at the end. Do you have anything else that you would like to share?
Jennifer: 00:39:56
Not that I can think of. We covered a lot today.
Hanh: 00:39:59
Yeah, we did. Thank you so much, uh, for sharing your insights and your passion for using AI to transform businesses. It's very inspiring. So as a director, Yeah. As a director of the product at NLP Logix, um, you're at the forefront of driving AI adoption. And you and your team deliver some real results for your clients. So congratulations. Um, your expertise is clear. You skillfully tailor AI solutions and you navigate adoption challenges.
Hanh: 00:40:29
Uh, and you foster a culture of innovation. So this is like a testament to your leadership in the field and your company as well. So we appreciate you taking the time to share your journey, vision to the audience and to the folks who's listening or watching, thanks for tuning in. We hope that you found this conversation as enlightening and thought provoking as we all did. Um, and. As we continue, uh, to push the boundaries of what's possible with AI,
Hanh: 00:40:58
let us remember that the true power lies within us, and it's in leveraging technology to create meaningful value and to elevate the human experience. So again, thank you so much for your attention. Take care.
Matt: 00:00:06
Work is not always fun. And I try to explain that to my kids all the time. They're like, Oh, today you seem bored. Well, yeah, today what I'm doing is boring. Um, but man have, this stuff's really cool. If there's any part of you that's nerdy and there's probably a part of all of us that do this, that is. Have some fun with it.
Hanh: 00:00:27
Hello, welcome to AI50, where your data meets innovation. It's a podcast that explores the thrilling intersections of data, AI, and the real world impact. I'm Hanh Brown, your host, and today we have the privilege of learning from a true trailblazer in the field. Matt Gordon. So in this episode, racing to data mastery, we'll discover how Matt's passion for innovation and racing has fueled his approach to leveraging data and AI for innovation. Pushing boundaries while navigating
Hanh: 00:01:02
the delicate balance of data security, privacy, and ethics. As a Microsoft Data Platform MVP and Accomplished Cloud Data Architect, Matt has been at the forefront of driving significant advantages for customers and partners. So throughout our conversation, Matt will share invaluable insights from his experiences, and He will discuss fostering a culture of collaboration and continuous improvement within his team, as well as the exciting trends shaping the future of various industries. Well, we won't stop there.
Hanh: 00:01:44
We'll also dive into the personal side of Matt's journey, exploring how he maintains well being and resilience in a fast paced environment and the valuable lessons he's learned along the way. So get ready for an engaging and insightful ride as we uncover the secrets to data mastery. And explore the essential skills and qualities needed for professionals in this field. So join me, um, on this adventure to learn how you can harness the power of data and AI to drive innovation and make a lasting impact.
Hanh: 00:02:23
So let's get started. Matt, welcome to the show.
Matt: 00:02:32
Thanks for having me.
Hanh: 00:02:34
Yeah. Well, hey, to kick things off, I'm curious to know more about the experiences and moments that have shaped your journey. Could you share an interesting fact or a story about yourself that many people might not know?
Matt: 00:02:48
Ooh, that many people might not know. Um, see, I, uh, so this seems appropriate since I'm a racing fan, which most people who connect with me online probably know, uh, the Indianapolis 500 is this week, which is arguably the biggest race in, in the world. While I've never been in that, um, I have raced at that track on, on the road course set up, not the oval set up where they run the 500 and I finished third. So I have a trophy from Indie that's out there, uh, in a different room. And probably a lot of people don't know
Matt: 00:03:25
that that was, that was a few years ago. And I tend not to show all that stuff online. So that kind of fits this week.
Hanh: 00:03:35
Yeah. Well, congratulations. So now how has your passion for racing influence your approach to your data or to your work, uh, as a cloud data and architect?
Matt: 00:03:47
Um, so I would say, so I think the thing, there's a lot of things I like about racing, you know, the, the noise, the speed, all that stuff, but the thing that I've always, since I got into driving, which. Is 19 years ago, which I'm very thankful for, very lucky. Um, the thing kind of keeps drawing me back is there is always a way to get better. There's no, there's no such thing as a perfect lap. You can, you know, Oh, I, I made a small mistake here.
Matt: 00:04:18
It cost myself a 10th of a second or even less. Um, and that's, you know, for better or worse, I bring that same attitude to work as well. And yeah, there's always a better way to do something. And it's, it's, it's kind of dovetailed really well with the, where I've ended up, you know, kind of data centric during the day, but AI has always been a big part of that. It used to be kind of a side thing for me, but that that's no longer the case at all. Cause it's all tied like this.
Matt: 00:04:46
Um, now these days, there almost are always better ways to do things, not just improvements to the processes and stuff that you're doing, but actually improvements to the tools that maybe a week or two ago. Had some gaps and now have less gaps.
Hanh: 00:04:59
Yeah. Yeah. Well, that's awesome. What you love for racing is evident and it's fascinating to see how it's shaped your professional life. So I'm curious, what are the most valuable lessons that you've learned in navigating the intersection of data and AI?
Matt: 00:05:22
So, you know, I, that phrase is interesting and I, I use it a lot too, because it is an intersection. I think I actually used it in one of my posts talking about this, but intersection may not actually be the right word. Um, the data is really, data is your foundation and we have a lot of customers that are approaching, uh, saying we need AI and in some cases it stops there. They don't, they don't know what they're asking for. They're, they're coming to Centric. Coming to me and why wanting to learn what that means.
Matt: 00:05:59
And it's because there's pressure from a board, from a CEO, from shareholders. Well, you know, whatever. And, uh, they, then when we tell them like, okay, well, here's, here's some kind of whiz bang stuff that you can do to kind of show off this stuff's really, really cool. And I go, that's great. How do we do that? Well, you know, given the scale of the data. You're talking about, there's a lot of, there's going to be a lot of data cleansing, data engineering, things like
Matt: 00:06:25
that to make sure that the AI is doing, is making, hopefully it's not making decisions, um, but make sure that it's presenting you with the right information for that, the data has got to be clean. And that they get a little less excited about that because it sounds boring. Um, but it really is necessary that you have the cool AI, like all, all the demos you're seeing this week at build and things like that. are very cool. But if you'll note, a lot of them are recorded, they're curated, and they're built on data
Matt: 00:06:57
sets that are well understood. The ones that those of us that kind of follow Microsoft stuff often see. Um, that's not necessarily the point we have to get to, uh, with customers and users, but we have to get a lot closer to that point than a lot of, you know, Customers are. So really, even though intersection makes sense, uh, data is really the foundation and the, I think the quicker that, that we all understand that, um, some of our worries about what AI may or may not do. We can temper those a bit because
Matt: 00:07:31
if we give a good information, it's likely to give good information back.
Hanh: 00:07:38
Very true. And you know, um, I always say when people ask, like, we know we need to integrate AI, what should we do? Well, the first thing I always say is, well, what are your pain points? What is it in your workflow, your organization, that you would just love to do away with? Whether it's repetitive tasks, content creation, um, customer inquiries that's, you know, coming at you, but you need to filter them, email, uh, cleansing, you know, whatever that is. But only you, uh, in your organization,
Hanh: 00:08:12
You need to identify what those pain points are and then prioritize them. Start with something simple, right? Because what you want to do is gain confidence that, uh, AI can enhance, augment these areas. I think once you can, can be proven, Oh wow, it's really helped me in this one or two areas. Let's dial it up. So I think that that way, um, they'll understand that AI is not a silver bullet for everything. Absolutely not. And it doesn't make decisions for you.
Hanh: 00:08:45
I don't think so. Absolutely not. It will uncover insights. Then you make the decision accordingly. And that's the key, though. You know, we talk about data, data visualization through power bi and so forth. Well, these are beautiful, right? They're beautiful to look at. Very impressive. But the end of the day, the business is not into creating charts. They're in create their, they have to make decisions based on those charts.
Hanh: 00:09:11
And that's what I always encourage people is that this isn't just an exercise. Um, it's a learning process, start small, gain confidence, but the end of the day, you got to make decisions.
Matt: 00:09:22
Yeah. Well, and, and we see it, you know, I think what gets lost in this is there's a lot of science for sure, but there's a bit of art and science to getting a co pilot AI assistant or something like that to do what you want it to do. And the example that I like to give in, in the talks I give now is, you know, not that long ago, probably a couple months ago, I was waiting for a friend at a bar. I was kicking around an idea for a demo for a talk. And in 10 minutes, I got co pilot to tell me that I had won the Indy 500 last year.
Matt: 00:09:54
I hadn't, I was in the stands. I saw the guy who did, it wasn't me. And the winner's check never showed up, but I got it to write a little news story about how I had done that. And I was the first Microsoft MVP to have ever won the race. And that was, that was 10 minutes of me. Messing around. And it's kind of funny, um, put that in a business context. And that's why the data you're basing this on the guardrails around that. And all those things are so important because if you, if you make an important
Matt: 00:10:25
executive call based on something that a virtual assistant told you, and somebody who was up to no good, like me, um, You know, fed it some bad information that the consequences of that can be really bad. Yeah. We've seen some in, in the news where I think air Canada lost a court case because somebody basically had messed around with their virtual assistant and got it to sell a plane ticket for a dollar and a court ruled that. Yes, it's not a real person, but it's a representative of the company that entered into an agreement, you know, and
Matt: 00:10:54
that was, I think the, the fair was 700. So air Canada lost 700 bucks. Okay. Whatever magnify that across a huge scale. And these, this is, it sounds silly, but this is all really important stuff to get right.
Hanh: 00:11:09
Yeah, it is. It is. So can you share, um, where you successfully leveraged data and AI to drive significant advantages for a customer or partner?
Matt: 00:11:26
Yeah. So obviously can't use names, um, and it would have to be very vague about this. Cause if I even mentioned like location or industry, everybody's like, Oh, okay. That's one of these three. Um, but yeah, there, there was, and it's actually kind of emblematic of, of. all of what we've talked about so far. So they were very interested in, uh, because they didn't have strong Power BI folks. That was kind of a growing part of their shop. But you know, they, they didn't
Matt: 00:11:53
have mastery of that, let's say. So they were interested in seeing the, um, kind of AI powered, you know, Capabilities of what we could do there. So, like, uh, Q and A has been in Power BI for almost four years. Um, so that's doing natural language processing under the covers. You know, you could argue that was a copilot before we called it that. But you could say, you know, what were my sales of this? On this month, uh, in this year, and it will give you kind of a basic chart and you can do all that.
Matt: 00:12:28
So we, we took that a couple of steps further with some of the knowledge that we had and we're showing them on the fly, you know, having kind of that copilot type experience, create pretty nice charts over things that was all well and good. So we showed kind of the first few and they're like, wow, this is amazing. You know, tell it to change this. So we go and do that. Oh, that's, that's awesome. Well, we didn't get too far into it before somebody said, well, you know, ask it to do this, this, and this we did, and it comes up.
Matt: 00:12:59
It looks great. Pretty fast that the data was well modeled, well understood. All, all the important stuff was done. But they're like, well, that's wrong. Well, that kind of beg, you know, we wanted to understand, like, how do you know that so fast? Like the chart came up in five seconds and somebody in the room, that's wrong. I said, well, I know that the system, we get these particular data points from upstream always inflates this particular metric because of a flaw in itself. Um, and so we, you know, we
Matt: 00:13:29
generally, before we produce the charts as humans, we clean that up. We know that it's inflated by. X amount, and we adjust for that, but the AI doesn't know that. And, you know, there were, there were people up the executive chain from these very experienced folks talking in all these kind of hype filled terms. Like, well, I'm not going to need a team in X years because the robots will do it all, right? The AI doesn't know that. And that's a very, that's a very particular use case.
Matt: 00:14:04
But that's almost every client I've ever had has something like that. There's that human experience that's like, well, we know that's wrong. Or we know that actually lags from what it says or whatever. That's very difficult to teach any sort of a virtual assistant to say, well, you need to adjust for this because. Um, so that's, you know, something like that is, is kind of the most recent example, but I like it because it also, you know, the room kind of went from, wow, this is amazing. And probably people are sitting
Matt: 00:14:32
there saying, like, well, gee, I build these, this is my day job. If it could do it in five seconds, like, what am I doing? And then you get kind of the record scratch moment where it's like, well, this is wrong, but there's really no way to tell a computer that it's wrong. It's not now. Um, And so I, it was a really interesting meeting because I think everybody started out going one way and at the end said, well, this is, these are really powerful tools, but, you know, maybe the name co pilot is
Matt: 00:15:01
good because you still need a pilot.
Hanh: 00:15:03
Exactly. You need human judgment.
Matt: 00:15:07
Exactly.
Hanh: 00:15:08
And, um, I always think AI, you know, co pilot is like a GPS. Well, you need a person to direct where it's going, right? It's not a silver bullet solution, but it certainly uncover many insights, but it needs human expertise, human judgment, uh, human experience and so forth. Yeah. So, so true. Well, those are powerful lessons and I'd like to hear more about how you've applied them, let's say into real world situations. So how do you balance pushing the
Hanh: 00:15:40
boundaries of technology, with ensuring data security, privacy, and ethics?
Matt: 00:15:50
It's um, so that's, it's always been an important part of this. So I was, um, I coauthored a book on what I like to say was Azure AI before it was cool. So, uh, I worked with some folks to author a book on cognitive services that came out, um, basically, uh, late in 2021. So there are some really good foundational things, but the world has passed probably five of those eight chapters by, um, just things have changed so much, but we felt really strongly. That we needed to include a chapter on ethics in that book, because it's so
Matt: 00:16:26
easy to get caught up in the, in the coolness of all this stuff and nerd out. And then when you take a breath, it's like, well, have we acquired that data the right way? Are we safeguarding it the right way? Did people consent for that data to be involved in this stuff? And, you know, our, our book was very focused on what the cognitive services offerings were then. So LLMs were not a part of that. And that introduces a whole other set of points to think about, let's say on, you know, we're training
Matt: 00:16:57
it on data, especially some of the, like, we're training it on data that other people created that they own. Um, and that's, I'm, I'm not a lawyer, so we probably shouldn't get too much farther into that, but you know, every, it's never the most fun part of any project that kind of dovetails these two, but it's where I said earlier, where data is the foundation of. Good AI, basically, um, security is what keeps it from going off off the rails and what keeps people out of trouble. Honestly, um, you know, some of what we work on.
Matt: 00:17:38
It's an internal system. If it gets some data, it's not supposed to. Very few people know, not a big deal. Some of what I've been able to work on over the years was very customer facing to very large groups. You get that wrong, you end up on the news or worse. And so, but it's, you know. It's all important and it's kind of, it's, it's crucial to talk through this stuff. And that's where going back to kind of the art and science a bit, those are tricky conversations to have because
Matt: 00:18:10
there are customers right now, you know, I talked to them as part of my day job. I talked to them as part of speaking at events where it's like, well, you know, we've been challenged to, to do and. AI thing this year, and our budget is X, okay, well, we can do the AI thing for that, but we can't secure the data the way we need to, we can't cleanse the data, and they're like, well, our budget is X, and those are difficult conversations to have, because sometimes, unfortunately, even though the work itself might be exciting, if it's not going to be done the proper way, you know, you kind of,
Matt: 00:18:49
kind of have to walk away from it, say, well, I, I wish you the best of luck, but in good conscience, I can't really be. I, you know, I shouldn't be a part of that because I know there's things that we should be doing that the budget doesn't allow for, and I get it. Money does not grow on trees and you have what you have. Um, but yeah, sometimes it's just not, not appropriate to carry that forward. Unfortunately, there's almost always somebody that will. And so I, I think, uh, we're going to keep seeing new stories about things like these
Matt: 00:19:23
going off, off the rails, because yeah, there's always somebody that'll cut it. Take that check to do the thing, and even when the thing isn't maybe not the most appropriate.
Hanh: 00:19:34
Well, I think that's a wonderful thing about the Microsoft AI ecosystem that it really streamlines and it's truly an ecosystem. It's not like a one off large language models, right? It's an entire ecosystem. So, and it's low code. So I think most of it, most of it, most of it. I mean, you, you know, people say it's low code as if it's like you wash your hands and you're done. Well, absolutely not.
Matt: 00:19:59
I wish. Yeah.
Hanh: 00:20:01
But, but here's the thing though, I believe it's still very doable. I don't know what the X budget entails. Um, and that's why I always say start small. Maybe you could work it within your X budget. And then as you gain confidence, you may have to X whatever exponential or times two as you gain confidence, because when you're fixed on that X, you're also going to be fixed on the. Um, the reaping the benefits of AI.
Matt: 00:20:33
Projects like that, I think, lend themselves best to a P. O. C. Your point start small, especially as quickly as the technology's evolving. Um, you know, I know, like from the announcements that build yesterday, there's demos that I that newly worked six or seven weeks ago in talks of mind that I now have to change because the way those have to work have. Shifted entirely. It won't continue at that pace, but it's good to have kind of a POC window
Matt: 00:21:00
where you can keep the budget small. You can pivot to some different tool sets or models or whatever, depending on what you're trying to do. And then at a certain point you do need to commit to what you've got and scale it. But it also helps, you know, one thing I found about these is keeping it small helps you win budget approval for the big stuff because so much of this stuff, the demo is cool. And eventually, especially when you're talking about the people that are going to kind of sign that check to let you do the big thing, they're largely not technical.
Matt: 00:21:32
So you show them something that looks like magic, even to you and I, um, to them, it looks amazing. And they're like, Oh, we can do that. And we can do that at scale for all, all our users. Yeah, we'll find money for it because that. You know, that sets us apart from competitor X that doesn't know how to, how to do any of this stuff because they didn't hire you. Um, that's, those are fun to be a part of, but yeah, it's always, it's, it's a bit of a trick sometimes to
Matt: 00:21:58
get a client to narrow their scope and say, no, actually we want less money for this because we want to take better care of you in, in the longterm. Like, we know you've come to us and said, I have this pile of cash for you to do this thing. And we're like, you know what, we don't want all that yet. Cause we're going to do it smaller, uh, but we're going to do it right. Yeah. And then you can go back, you can save part of that pile. We can go back to the people that
Matt: 00:22:19
can grant us a much larger pile and say, look at this cool thing we've done. That's going to be helpful that, that puts you in a space that, you know, other firms aren't. And by the way, we'd like to larger pile of cash to finish this work.
Hanh: 00:22:34
Yeah. No, absolutely. And the thing is, you know, we want to be integral to the whole idea of democratizing AI, uh, to all levels, small, medium, large size businesses. Uh, again, nowadays it's very doable. It's to what scale and what is the size of your pain points.
Matt: 00:22:52
Right?
Hanh: 00:22:58
So well, as you discuss great power comes with great responsibility. So can you discuss a challenging situation that you face at work? Um, and how you approach it while maintaining well being and, um, I guess, uh, a lesson that you can share with the audience.
Matt: 00:23:16
Yeah. And I don't always follow my advice as much as I should, but it's, you know, I, I've been fortunate enough to speak on these topics at a few conferences, um, some tech conferences kind of shy away from whether you call it professional development or mental health or wellness or well being or. Um, some tech conferences will not include those topics. Some do, and I'm very thankful that they do because I, I think we all need that. Um, in terms of a particular situation, there have been several times, and it's
Matt: 00:23:51
not always a lesson that I take well. Um, but I was reminded of this recently with one of my friends saying. No is a complete sentence sometimes, um, especially like we've talked about you're in this data and AI world that is so fast paced that things are changing so much. You feel like, oh man, if I take a week off, I've missed an announcement on this or I'm going to be behind on that. Um, it's, it's really important to sometimes turn down opportunities. Um, you know, whether it's, whether it's. Doing a talk, uh, whether it's doing a podcast, um, whether it's a job that
Matt: 00:24:37
you're like, well, the opportunities here could be really exciting, but I know, you know, they're in kind of a startup mentality and that's maybe not where my life is now. Those are all important things to think about. Um, and just like I said, it's weird to tell a customer, no, we don't want all of your money yet because we're going to do this right. Very similar to this. Sometimes you need to tell somebody that wants you to help with something or they want to feature you as something.
Matt: 00:25:05
Uh, no, because it just, it doesn't, it doesn't fit with where you're at and, and where you're going and maybe the right way to do certain things.
Hanh: 00:25:20
Very true. I am. It's good to ensure that your values, your goals. Expectations are aligned, right? And that's not something that's readily fall into place, uh, everywhere you go. So I think it's important. That it's mutual, um, you, your values are in alignment with what you're trying to do, especially when it comes to AI. So that's really important.
Matt: 00:25:44
Yeah. Well, and yeah, it's also good, and this is not a lesson I learned straight out of school. That's for sure. Um, networking is important. Because a lot of, especially if you're thinking about like a professional opportunity, like you're going to leave a job to go to the next job. Companies are very good at selling what they are or what they want to be. A lot of times they're selling what they want to be or what they think they are versus what
Matt: 00:26:09
they may actually be day to day. Um, if, if you have a large enough network, You can generally find out some details about the day to day that they are unwilling to share. You know, you find out if you'll say, Hey, I'm talking about going to work at XYZ. What do you know? Oh, well, I had a friend of mine that worked there for two years. And so it's like, Oh, well, they talk about work life balance and all that. It's like, well, yeah, but, but my friend that worked there said, here's actually what they did.
Matt: 00:26:41
Um, so things like that are really important. Um, it's, it's a struggle, you know, especially for me, like sometimes at an event, like you don't want to come out of your shell, you're just there to learn stuff and, and you don't want to talk to people, but that's really where your career starts to take the next step. And it gets you into better opportunities and also keeps you out of ones that you shouldn't be in, because you, you may know somebody that. It's going to give you that bit of knowledge where you're like, okay,
Matt: 00:27:10
actually, I, I should say no here, where on his face, it doesn't seem like it.
Hanh: 00:27:16
So true. Well, what exciting trends in data and AI do you think will shape the future of various industries?
Matt: 00:27:31
All of them. Uh.
Hanh: 00:27:33
Yeah. Is there one that's not affected?
Matt: 00:27:37
That's the thing, you know, the, the kind of the overarching AI session that I do right now is more focused on kind of data professionals, the tools they use and the environments they're in, and where AI can help them and where maybe somebody is going to say, Oh, you can do this this way, but it's not the best way, whether it's AI powered or whatever the buzzword is, wait, because it's not there. Um, wait, yeah. In terms of trends, um, This stuff is going to change for anybody in technology, especially data pros. It is going to change
Matt: 00:28:14
the way that you work. It's already changed the way I work. Um, it's, it's probably for the worst change the way people attend meetings. I've been part of more than one meeting this year where you ask somebody something and they're like, Oh, I'm sorry. I was multitasking over here. Uh, cause I know I'm going to get the summary from co pilot after. After we're done and it's like, well, okay. Uh, but being present in the meeting makes it much better meeting for, for the rest of us.
Matt: 00:28:44
Um, yeah, it's all going to change the way we work. I think for me, probably the trend to keep an eye on for data professionals like me and for AI practitioners to understand is that data engineering is critically important. Um, that's, that's the skill, not that makes all this go. Cool. But you really need skilled engineers to get the data cleanse, to get it moved around position the way it needs to be for the AI coolness to take it from there and, and do it's it's stuff.
Matt: 00:29:21
So I don't know if that's a career trend or, or what, but yeah, not that data engineering, it's always been important, but I think for this stuff, it's really, really important. And if it's, you know, if I'm somebody just getting into data work, I'm trying to figure out like, do I want to be a. Um, DBA, do I want to be a report dev or something like that? Um, all those are still valid and will be for a very, very, very long time. But I see data engineering, maybe those types of rules almost being the first ones to kind of, Come along for the ride
Matt: 00:29:52
with, with all your prompt engineers and ML folks and, and all that, um, because none of that can do what it does well enough without good data.
Hanh: 00:30:06
So true. So how do you stay informed and adapt to this rapidly evolving landscape? I mean, we talked a couple of the same. Yeah, it's hard. Within one week or. Speed of advancement. So how do you stay on top of all that? And how do you learn and execute and gain trust and share that with your partners?
Matt: 00:30:32
Yeah, it's uh, it's really difficult. You know, I'm I'm very fortunate. Um, you know, I've I've been a Microsoft MVP for six years. So with that comes a network where a lot of times I know what's coming. And I can not only prepare myself for it and build content, things like that. I'll be doing that later today. Actually some, some blogs that I know stuff will be announced at bill later this week. And I'm kind of putting, you know, finishing things on, on that.
Matt: 00:31:03
So, um, people can read it. And so I don't break my NDA by putting it out before I'm supposed to. Um, so I'm a little bit ahead of the game in that way. And I'm very fortunate to be there, but what I would say is the best way to keep abreast of this stuff. Is, find the community that's interested in what you're interested in. Mm-Hmm. . Um, you know, for me being, being a SQL server, DBA is my first data job. You know, the, the Microsoft ecosystem has always been what I'm a part of.
Matt: 00:31:38
Now, I've broadened beyond that as I've gotten older. Um, but it's still like, that's the community that I call home. And I think particularly in kind of the AI arms race, I've been very fortunate to be there because Microsoft's made a lot of smart investments and maybe are a bit ahead of the curve and certainly I can argue that, um, but it's been a good place to be, but a lot of that knowledge just comes from connecting with people online, whether it's people I know in real life or not. And reading what they're talking
Matt: 00:32:10
about, reading the blogs that they're reading, uh, reading the blogs that they're writing. Um, that's kind of the best way, but there is no silver bullet. Like I, I wish I could say, Oh, there's an account you can follow on X that just, they post all the best stuff and you just go read them and you'll be up to speed. Um, I have yet to find one. It would be great. Um, but yeah, it's really just plugging in, you know, fighting your, Local user groups, like a lot of local user groups that kind of are
Matt: 00:32:43
still foundationally Microsoft data. We do an AI session every month and a lot of the other groups are starting to do that because stuff isn't data over here and AI here, it's like that. Um, and, and the interest is twofold too. So even the people that are like, well, I'm a, I'm a DBA, but I still want to know about this stuff. So I'm going to come, come to the meeting and maybe once or twice a year, you'll have a topic for me on. On the data side, but I'm always learning something on the AI side. So it's, you know, find
Matt: 00:33:13
your local user group. Um, I know in the Microsoft world, if you Google or Bing search, uh, I think Azure tech groups, uh, you'll find my group, you'll find hundreds of others all over the world. Um, I, so that's, that's where I'd start. And then it's, it's almost, you know, find the people that lead those groups, the people that speak at those groups and connect with them on LinkedIn. Uh, maybe Twitter X, it's not what it was. It can still be useful for stuff like this. And then once you're linked to them,
Matt: 00:33:46
look at the people that they follow, look at the people that they retweet and repost and all that stuff. Connect with them. And that's, then you kind of start seeing what's flying around because that's really what it is. There's so information, so much information flying around that just kind of get in, get in a good space with good people and try to consume what you can. But, Try to limit your screen time too. Cause it's not good for us. And I say that as somebody who's really, really bad at that, but, um, yeah, you
Matt: 00:34:18
can, you can scroll for hours, just don't.
Hanh: 00:34:20
And, and you know, how I look at that is my gosh. Um, find a reliable source of information and you know, stick with that and engage and learn and also contribute, but you're right about limiting your, Up to date with everything. Cause they can, it's very unhealthy at times.
Matt: 00:34:40
It's not possible.
Hanh: 00:34:41
Yeah, it's not. And you always feel like you're behind if you're trying to do that daily.
Matt: 00:34:46
Yeah. And I feel like as much good information as LinkedIn has right now, and it does, I've seen a lot of the technical information that used to be on Twitter, especially for like Microsoft data and things like that is now on both. Like it hasn't left Twitter entirely, but LinkedIn is a, is a better source. But LinkedIn, you also see the kind of. Uh, inflation of titles and things like that. And you'll see people that will say, like, AI, you know, yeah, everybody's a guru, you know?
Matt: 00:35:14
Oh, yeah. It's like, I know AI A to Z. It's like, well, maybe, maybe you did for six hours a week ago, but now you don't.
Hanh: 00:35:22
True. True. And well, here's an example of networking event. We met where did we meet? At the Fabric, right?
Matt: 00:35:34
Yeah. Yeah. Fabric Conference, uh, Vegas, and they're doing one in Europe this fall. So for, Folks that might be listening to this saying, well, Vegas sounds great, but it's several thousand miles for me. There will be one over there. I think it's late September in Stockholm. Um, yeah. And that's, that's a funny one because I wasn't talking about Fabric at all. Um, I did kind of at the Microsoft booth and some of the, some of my non presentation things, but I was
Matt: 00:36:00
there talking about AI And all that. So, um, if you've looked at a conference that has fabric in the name and you're like, well, I don't work with that. There's tons of other good sessions there. Um, it's not just fabric, even though they've called it that.
Hanh: 00:36:19
You know, um, in the realm of data, ingesting data, uh, privacy, ethics, transparency, that is a great start purview purview and fabric. You, you gotta start there so that you can gain confidence before you Utilize AI, right? So to me, that's just huge. And that's like a different episode.
Matt: 00:36:43
Yeah, it is. Um, but yeah, going back to what you talked about, where it's kind of low code, no code. Um, it's been really fascinating to see Microsoft's investment in that. You know, I know, like I started talking about AI topics back seven, almost exactly seven years ago. And then even like I was using logic apps to call a cognitive services API, but there was no code involved. And, um, yeah, I wish I could have seen the future then because I was just like, well, this is cool.
Matt: 00:37:12
And this is obviously not out of the goodness of their heart because they want you to consume and spend money and all that. But it's like, well, this is really interesting that you've got it next to the documentation on how to write. Grownup code and call this stuff. You've got a low code experience to do that, to see where it's gone, um, is, is pretty fascinating, honestly, and you can still do all the, all the grownup code stuff and you have to at certain levels, but it's much more accessible. It's kind of, it's that drum
Matt: 00:37:41
that I've beat for seven years. I I've given a lot of sessions about, Hey, I want you to learn that this stuff is out there. That it's not hard to use in part. Um, and it's been cool to see Microsoft come along for that ride. And, and yeah, some of the stuff you can do is obviously way beyond what I was doing seven years ago. Um, but yeah, it's, it's really neat to see because it does allow people maybe that are technical, but aren't devs. They can, they can do this stuff. You don't have to go learn C
Matt: 00:38:14
sharp or Python or whatever. Arguably you should learn Python for other reasons. Going back to what I was saying about data engineers, but, um, you don't have to, to play with this stuff and you don't have to, to. Operationalize this stuff too.
Hanh: 00:38:30
Yeah, I agree. I agree. You know, I heard from Jensen, um, in one of the interviews, he said the, the most popular language isn't, you know, SQL or C plus plus or, or Python. It's English.
Matt: 00:38:44
Yeah.
Hanh: 00:38:45
Yeah. And there's a lot of truth to that. Yeah.
Matt: 00:38:48
Yup. Yup.
Hanh: 00:38:49
Yeah. So now how do you approach working with diverse clients and ensure that those solutions are tailored to their needs?
Matt: 00:39:04
That, that's an interesting question. Um, I think the best way, the best way that I can explain that an old boss of mine, um, who was fantastic, uh, used to use a phrase called listening between the lines because, and I'm not sure how you mean the question, but for me. Diversity of client could be things you see, it could be things you can't. It could be things in their, in their background, in their experiences, whatever. Um, but especially for a consultant, like your technical knowledge matters.
Matt: 00:39:41
Your ability to listen and converse and understand matters more. Um, the, the tech changes, which is not to say you don't have to be a technical expert to be a good data consultant. I, I'd like to think you do. Um, you have to, you have to be able to put yourself in people's shoes and going back to what you've said a few times, like understanding the pain points and sometimes what they're saying is the pain point isn't, it's actually something else and it's kind of your job to guide that conversation from. Okay.
Matt: 00:40:23
Yep. That's definitely a pain point, but what's that rooted from, you know, where, where downstream, is that an issue or is that something that they're bringing to the table? Something from their background and they're kind of hyper focused on something that really isn't the pain point for the business. It's a point of annoyance for them, which doesn't make it any less important, but it's our job to kind of pull all that out. Right. And understand like, well, this is very
Matt: 00:40:46
frustrating for this team or this person for the business that's down here. And actually, the bigger issue is a business wide issue. And that's up here. And then walking away from that and having everybody think that they were listened to because they were and that their issue will be taken care of. Maybe not in the priority order that they wanted. Um, but you don't, you know, having been on both sides of this, It's very frustrating to talk to a consultant and walk away and feel
Matt: 00:41:20
like they didn't hear what I said. They, they came in here to sell me something. Um, and I think, you know, especially in, in the Microsoft world right now, it's fabric, all the things, right. And fabric's really, really cool. But you do run across some people that are just, that fabrics, the hammer for every nail and they don't take the time to say, well, maybe that's not a nail at all. Maybe it's a screw. I actually need a screwdriver. Like the hammer will, it'll nail a screwdriver in there
Matt: 00:41:50
eventually, but it'll mangle it. You won't be able to, you won't be able to do anything else with it. Um, so it's just, for me, it all comes back to listening and I was thankful to have a couple of really good bosses and mentors that brought that home because, you know, when I was younger, you got a college, you think, you know, everything, um, as I, you know, you start to get into this world, you're just kind of telling, it's like, well, what you did is dumb and you need to do this and you may be right, but you have to be right the right way, um, just cause you won the argument.
Matt: 00:42:23
They may say, well, that guy's really smart, but he's a jerk and he doesn't listen to us at all, so we're not going to continue working with him. Um, so, so you, you won the battle, but lost the war, which is never good.
Hanh: 00:42:35
Yeah, that's true. And you know, I gotta tell you, I'm kind of surprised when I talk to, um, prospective clients when asking about what are your pain points, what problem is you're trying to solve? I'm really surprised how long it takes them to answer. And they struggle with that. Well, here's the thing. I mean, how I look at it, if, you know, if you've got a business, obviously you're, you've got goals to achieve and along the way, um, you have your workflow, your process,
Hanh: 00:43:00
how you achieve your goals, right? And what are some of those oppositions, which in my mind are your pain points. So let's, you know, lay it out, prioritize low, medium, high, and focus on the low ones, perhaps that might be more achievable to assume that AI is a solution. Well, it isn't. Certainly not when you don't know what your, where your heartache is, that you're trying to, you know, get better or increase productivity and so forth. So those are like internal questions that the company has to answer prior to
Hanh: 00:43:43
even exploring how AI is going to help. Again, it's not a silver bullet solution. So, um, You know, but those conversations I got to tell you is it's a paradigm shift for folks. It's a huge paradigm shift and you want to be respectful. You want to guide them along paradigm shift. Um, how do, how do I say this? You can try to influence that, but nobody's got time to be waiting for people to change their paradigm shift. You know what I mean?
Matt: 00:44:10
No, no. And right. That's the, yeah, that it, how many more use cases.
Hanh: 00:44:19
How many more use cases do you need to see that AI can impact your day to day life and your work life and so forth? So, so it's a fine balance.
Matt: 00:44:31
It is, and it's really, it's funny for, you know, for like person to person interactions. Sometimes it is about driving interest in this stuff for all my corporate and kind of customer or prospect interactions, it's trying to get the enthusiasm under control of it, right? There's all this external pressure. Well, this firm that we compete with says they have AI that does whatever. Well, we need that too. It's like, well, actually what they're saying, they're full of it. That's not, that's not
Matt: 00:45:01
at all what it's doing. It's doing, you know, this, this, and this wrong. Let's try to get this to go right for you so you can kind of rightly claim, uh, superiority over what their solution was, but sometimes people don't want to hear it, right? Cause it's like it moves fast and you get executives under pressure and like, you know, I can think obviously won't name names, but I can think of of a customer that we were having kind of a. We were kind of laying out a project schedule, uh, for moving some data
Matt: 00:45:35
assets of theirs to the cloud and somebody piped in and said, well, at the recent board meeting, they said, we need to be, we need to have an AI solution implemented by December. They are on very old, largely out of support, um, Windows and SQL and all that. It's a big jump. So it's not just a paradigm shift kind of for us. It's a culture shift for places sometimes and a skill shift.
Hanh: 00:46:06
Yeah,
Matt: 00:46:06
You're trying to get all of it, right? They're very comfortable in, in this on prem world with versions of SQL that are, that have some years on them. And, um, you know, the jump to cloud based stuff of that, and then putting AI things over it, the terms you have to learn, the things you have to understand. It's massive. Um, you know, can we get it all done in six months? Sure. But, um, there's got to be a tremendous organizational commitment to that.
Matt: 00:46:33
And for some organizations, it's a, it's a, it's a struggle to understand that because they think we're slowing them down just cause and really we're slowing them down. It's like, you're not ready. You're going to jump into this, uh, you know, the wrong way, have spent a lot of money and not really not gotten value out of it. Um, it's not, it may feel like a race, but it's, it isn't as much as I think companies, especially small and midsize are feeling. There's time to do it right.
Matt: 00:47:02
Still, we, we need to move quickly, but there's time to do it right.
Hanh: 00:47:05
No, I agree. I agree. So now how do you, um, how do you approach working with diverse clients and ensure that their needs and your expectations are met? Um, and stay within the boundaries of ethical. So we're at the end of our call. Thank you so much for your time. So is there anything else that you would like to share with the folks who are interested in getting into AI and data? And I guess, what is the most impact you think that AI and, um,
Hanh: 00:47:46
and data can serve businesses? And what attitude should be people take on?
Matt: 00:47:52
Don't be scared of it. It's, it's, it's how I like to summarize the session that I've got currently. Don't be scared of it. Engage with it. Find the way that you want to do that. It is, like we said earlier, it's not possible to be an expert on all this stuff. Um, and I think especially if you're, if you're like me, if you're a. Data person, find the ways that it can kind of enhance your job or, or enhance your skill sets. So you can go to that next interview
Matt: 00:48:17
and say, not only am I a data X, um, I also understand vectors and, and things like that, or whatever technical or not technical part of AI, you kind of want to add on to your skill sets. You know, I guess as far as advice, I'd separate that into business and personal. For businesses, concentrate on finding the pain point. Uh, don't necessarily create in AI something to check a box. That's not going to be probably a solution that grows well. It's probably not going to be a solution that ages well.
Matt: 00:48:56
You're probably not going to get a lot of value out of whatever you've built. Um, no matter the quality of the people that have built it, because you haven't really thought through what you want, you've just tried to tick a box. Now, having said that, I understand that sometimes for incentives, bonuses, whatever the box has to be ticked and that's okay. And if that's the spot you're in build. The best thing you can tick that box, but then don't stop thinking about what, what it should actually be, because there's a lot of maturation
Matt: 00:49:29
that needs to go on around this. And that's where I'd like to think people like me can help. Cause you're coming in from external, you're bringing experiences from other places and you say, well, I, I hear you. Let's talk about what I saw over here and maybe this fits you better for personal. You know, I would say, look at Try to engage with it in a way that's interesting to you and interesting opportunities will come out of that. I mean, I started working with this stuff cause I wanted to be talked about on a soccer podcast.
Matt: 00:50:00
It worked, but that, you know, I had no idea that would lead to the opportunities that I've had. So, you know, start there. And if you're still, if you're still like, well, listen, I need to, I need to work with this stuff. It's interesting. I don't know where to start. Try to think about something that helps people. You know, we were talking pre show about a friend of mine, you know, who's, who's been dealing with ALS for two years. And uh, you'll see more on my
Matt: 00:50:25
social media, um, over the next weeks and months about fundraising and ways we can help him. But without people thinking about how AI can benefit accessibility for people who have challenges with a wide variety of things, whether it's movement, vision, speech, all those things. Um, if you're having trouble kind of plugging in, like. Well, I need something to inspire me to really get into this stuff. Try to help people. Um, I that's, that's the most, most inspirational thing I can think of.
Matt: 00:50:57
And for all the cool things we can do for businesses here that are important, most important is impacting somebody's life like that.
Hanh: 00:51:07
So true. And it is, um, very possible nowadays to use AI to help folks, like you said, ALS. Um, my, my demographic is 50 plus, for instance, it could be mobility. It could be, be my eye, sort of speak right now that, uh, the AI can help, uh, read the environment of the user and explain where you, where your abouts are and cognitive decline. People that may have limited ability to speak. Or even speak different languages all together. So there's so many opportunities to
Hanh: 00:51:39
solve problems and help enhance lives. So, yeah, I think that's a great way to end it. Use AI to solve problems. And proceed with enthusiasm, but with caution. Well, thank you. Thank you so much, Matt, for sharing your wealth of knowledge, experiences. So many insights with us, uh, from leveraging data, uh, and AI to drive, uh, significant advantages, and also fostering a culture of innovation, uh, so you exemplify what it means to be a trailblazer in this field,
Hanh: 00:52:15
and your perspective is, um, uh, on maintaining your well being, resilience, and importance of, uh, continuous learning is a reminder to all of us that when, uh, as we reflect on meaningful collaborations and difficult situations and our accomplishments, um, use AI as an inspiration.
Matt: 00:52:40
Right. And, and have fun. Yeah. Work is not always fun. And I try to explain that to my kids all the time. They're like, Oh, today you seem bored. Well, yeah, today what I'm doing Is boring. Um, but man have, this stuff's really cool. If there's any part of you that's nerdy. And there's probably a part of all of us that do this. That is have some fun with it.
Hanh: 00:53:02
Yeah, that's so true. And the road to data mastery is an evolution is continuous opportunities, growth, opposition, adaptation. But the end of the day, it makes real impact. Oh, yeah, that is very exciting. So the folks that are listening, stay curious, be resilient and. Don't stop learning. You got to foster a lifelong learning attitude. I'm approaching 60 and I'm still learning and I'm encouraging my older siblings to learn how to use
Hanh: 00:53:33
AI to enhance their financial, their Medicare understanding and so forth. And of course dealing with health, uh, you know, healthy aging. So, um, so all those are, are very good. We'd like to hear your thoughts, the audience about this episode. So continue with the conversation, give us feedback, questions, share some personal experience, reach out to Matt or I on social media, uh, on Spotify, YouTube channel, LinkedIn, join our online community. Uh, and connect with like minded AI enthusiasts.
Hanh: 00:54:13
And then until next time, I'm Hanh Brown signing off from AI50, where your data meets innovation. Keep innovating, keep growing, and we'll see you on the next episode.
Hanh: 00:00:00
Hello, I'm Hanh Brown. Welcome to AI50, where your data meets innovation. At AI50, we skillfully deploy cutting edge AI technology to create large language model apps. These apps are tailored specifically for the needs and preferences of the 50 plus demographic. Our team of experts works, uh, diligently to understand the unique requirements and interests of this age group. And by leveraging the power of AI, we develop solutions that cater to their specific needs.
Hanh: 00:00:38
We believe that technology should be accessible to everyone regardless of age. So our goal is to empower the 50 plus demographic. With tools that enhance their daily lives and keep them connected to the world around them. So, today's topic is data driven policy and innovation with AI, where we'll go into the intersection of data, technology, and public policy. So our special guest today is Daniel Castro. He's the director of the Center for Data Innovation.
Hanh: 00:01:15
a leading think tank studying how data and technology create new opportunities for people and businesses. Daniel's work focuses on the impact of emerging technologies and helping policy makers develop rules supporting responsible innovation. So Daniel bridges the gap between policy makers, tech companies, and business leaders. And the public to help everyone understand the benefits and challenges of AI and data analytics. He champions responsible innovation, believing new technology should benefit
Hanh: 00:01:50
society while addressing potential risks. So, in our discussion, Daniel will share his unique perspective on data driven innovation and the future of technology policy. We'll explore his groundbreaking work at the Center for Data Innovation and his insights on fostering a responsible, inclusive future. So Daniel, welcome to the show.
Daniel: 00:02:15
Thanks so much for having me on.
Hanh: 00:02:17
Yeah. Thank you. Thank you so much. So I'm from Michigan and where are you calling from?
Daniel: 00:02:23
I'm calling from North Carolina, Winston Salem.
Hanh: 00:02:25
Okay. Nice. Nice. I know we talked a little bit before the show. We're, we're seeing some great weather here. So I think we both can relate to the same, all the activities that's going on right now. So I, I thank you so much for your time. So to start things off, could you share with us something about yourself that many people might not know? It could be a unique experience or a
Hanh: 00:02:48
hidden talent or an interesting fact that helped us understand what has shaped your journey, and perspective.
Daniel: 00:03:00
Yeah, it's a great question. I wish I had more hidden talents or talents in general. A unique fact about me is I'm both an American and I'm Colombian. My father was Colombian, so I grew up in a dual national household. I think having a global perspective on issues, especially around, uh, technology and innovation, something that's really useful because you have to realize that there's, um, more than one way of understanding how a technology is going to be used. Um, different countries have different
Daniel: 00:03:29
perspectives on these issues. Uh, different demographics have different perspectives on these issues. I think, you know, having that experience of growing up in a household, you know, multicultural household, you know, gives you. It gives you new experiences and new ways of looking at things that is useful whenever you're confronted with new ideas. Um, sometimes you know that you should challenge those ideas and you should challenge conventional wisdom. Um, because, you know, you've seen it challenged in your own life.
Hanh: 00:03:57
Well, thank you. Thank you for sharing that. So your work at the Center for Data Innovation is deeply rooted in advocating for data driven innovation and shaping public policy. So can you share with us how your personal journey, your values and beliefs have influenced your approach to these critical issues?
Daniel: 00:04:19
Yeah. So, you know, I grew up as someone who, um, loved, uh, technology from, you know, early stages. I was excited when we got our first, uh, computer in the household. Um, I, you know, uh, enjoyed programming, um, as a child, you know, even before it was kind of cooler to be a software engineer, to do programming, right. The way it is now, I think much more kind of respected as a profession. Um, and so, you know, I always thought technology is something that was useful and beneficial for the world
Daniel: 00:04:46
and something that was, that was good. Um, and I think that has shaped a lot of the way I look at, um, technology and technology policy and where I interact with this because I understand that one, um, deeply understanding technology helps you understand how policy impacts the opportunities there. Um, so you, you know, the, if you have a very superficial. Knowledge of what technology can do, um, both its potential and its limitations. You can't, can't, uh, you know, create effective laws and regulations around it. Um, and so, you know, seeing technology
Daniel: 00:05:19
and innovation as a force for good. I think changes the way, you know, we encounter, you know, all the new innovations that we see in the world. Um, if you, if you look at it as a force for good, when you see these changes, you're generally optimistic about what it means. It doesn't mean you have to be naive about recognizing that there could be trade offs and there could be challenges. Um, but, you know, generally recognizing that, uh, historically, technology has been a force for good, whether we're talking about, you know, You know,
Daniel: 00:05:48
the printing press, gas lighting, um, and heating, you know, uh, railroads, automobiles, the internet, you know, computers today, and now AI, you know, these technologies had just a tremendously positive impact. Um, you know, the industrial revolution, I think about what it meant for, you know, the, the average life, Um, workers and and, you know, what their standard of living became, and obviously there were major challenges with improving workers rights. So we went through it throughout history. But if you look at this
Daniel: 00:06:15
trajectory, it's been positive. So, you know, when I think about kind of, you know, when I approach new technologies, that's one of the biggest issues, you know, I'm looking at is, you know, is this continuing to be a force for good? And we have a deep history of recognizing that. Um, when it comes to data, though, I'd say, you know, the other part of this is, you know, I, um, I think that, you know, the famous maxim, you can't manage what you can't measure is really important. And data really starts empowering us
Daniel: 00:06:40
to make, you know, smarter decisions, better decisions, faster decisions. Um, and, you know, just whether it's, you know, in our individual lives, you know, deciding things like, you know, wearing a smart watch or a Fitbit and, and, you know, figuring out, okay, I'm going to, you know, exercise differently because I see this information or eat differently or, you know, improve my health, um, using data, um, you know, at the city level to, to, you know, better manage, uh, municipality or deliver services to citizens or at the organizational level. You know, we were talking about, you
Daniel: 00:07:13
know, companies that are really innovative because they can do more with data. I think that concept of, you know, you can't manage what you can't measure, it's hugely important and undercuts a lot of, you know, how I look at, um, policy as well.
Hanh: 00:07:26
Great insight. And what a great time right now to convey that message, right? With AI and the speed of advancement and the hype, the fear, and those are very real, but there's also opportunities for embracing innovation. So that's great. So now, throughout your career, you've navigated. Some complex landscape of data policy and technological advancements. So what have been, what have been some of the most valuable lessons that you've learned along the way?
Daniel: 00:07:59
Well, I think one is that, you know, progress is really hard, that, um, you know, uh, there's so many barriers to innovation, and that, you know, the point at which a technology, um, or innovation, um, You know, the potential is realized. You know, you can see how it would be beneficial. And then the point where it's actually widely deployed in the world and generating those benefits, there's often a huge gap there. Um, I think it's easy to look at, you know, some technologies, you know, smartphones, for example, and we
Daniel: 00:08:28
see this rapid, um, adoption cycle. I think a lot of people who study, uh, innovation technology, they might be familiar with the, the S curve of innovation, right? It starts kind of slow. And it rapidly accelerates and goes up quickly. And we've seen that, um, kind of curve be compressed over time. So if you think about something like, you know, radio, you know, what it took to go from 0 percent to, you know, nearly full 100 percent adoption, right? That was maybe, you know, 40
Daniel: 00:08:54
years television, um, you know, a little bit more compressed, uh, computers, it gets a little shorter. And then you get to something like smartphones. And you're talking about only a few years, right? It gets so much smaller. Then you have things like AI, where you had chat GPT. If you look at that as an app, you know, one of the shortest adoption cycles in history of only a few months, where you had, you know, millions, a hundred million users.
Daniel: 00:09:18
That, you know, that makes it, I think, look to the average person that, Um, change is happening so much faster now. Um, and in some areas, you know, some of these, you know, very consumer oriented places where we're just talking about adopting software. Yes, change happens fast when we talk about some of these, you know, bigger areas of life. You think about healthcare being transformed to be more digital. That takes decades, right? We've been investing billions of dollars in the United States, for example, just to
Daniel: 00:09:48
get hospitals and primary care physicians to use electronic health records. Um, the technology has been around since the 80s, and we were just talking about basically computers and digital records, but actually doing this so that it's useful for, uh, the patient so that people's data is protected, um, so that, you know, providers have an incentive to adopt it and deploy it effectively and responsibly to make sure it doesn't interfere with quality of care. All of those things has taken a tremendous amount of time, and now that we even are rolling it out, now they're focused
Daniel: 00:10:19
on, okay, now that the technology is there, how do we make sure that we're using it effectively to do things like reduce adverse medical events? How do we make sure that, you know, for example, when a doctor is, Um, giving a prescription if it's going to interact with another prescription that that's identified automatically by the computer and that when alerts are being sent to the doctors, we're not sending too many alerts. So they just dismiss them, you know, getting to that whole usability side of technology.
Daniel: 00:10:45
So, you know, the lesson here again is just, you know, that progress can be so hard. It takes, I think, a lot longer than we expected and expect in most cases. So many people, I think, predicted self driving cars by 2020. Uh, you know, it's 2024. Uh, we do have, you know, some self driving cars on the road and very limited deployment, but we're still a long way from actually getting it fully out there. I think that's the, the lesson that we have to learn here.
Hanh: 00:11:10
I agree. I feel like when it, AI first came out for the general population, There was a lot of hype. There was not a full understanding and the speed of change was daily. And not all of it was, in my mind, AI, so to speak, right? But now 2024, I think people are in execution mode. And as you execute everything that you're describing, privacy, security, transparency are huge. And in my mind, in order to do that successfully, obviously
Hanh: 00:11:42
data is the heart of it. But you, you also want to cultivate. AI ecosystem because without that, you are really not reaping the benefits of AI.
Daniel: 00:11:54
That's right. And I think one of the things that's so important is when we look at these innovations, I mean, Chad, GPT was released as a proof of concept more than anything, right? It wasn't released originally as, you know, here's a service everyone should subscribe to, was really just showing, you know, the potential. You know, Dolly, same similar thing of to do image generation, and so. You know, it's one of those areas where it's, it's easy to be a critic, right? It's easy to go in and look at a,
Daniel: 00:12:20
a basically a beta product and say, look at all the ways it can be used badly or all the mistakes that makes. Um, and you know, it's true and it's kind of fine. And you know, there's, there's something, I think just innately human and us kind of, uh, poking holes at a few ideas, um, and being somewhat skeptical. Um, but there's also so many positive examples of how it's useful and how it's an improvement. Um, and I think it's important that, you know, we both, you know, put on that critical, you know, lens and
Daniel: 00:12:51
look and say, okay, how do we make sure that as we're widely deploying this, we address those risks, but also recognize that, you know, we need to not just make sure things don't go wrong, but also make sure things go right. How do we actually make sure the technology It dances and is used widely for the, the beneficial purposes that, that are possibly out there.
Hanh: 00:13:13
Mm hmm. I agree with you. Conversations like this, in my mind, it puts it out there for others to be a part of that conversation, right? Because everybody's concerns are very legit and they need to hear conversations like this to ensure that, hey, it's adaptation, there's change, there's lifelong learning, there's evolution. And that comes with kind of a, you know, rattle your current scenario. So you really have to step out of that and adapt this lifelong learning in the age of AI.
Hanh: 00:13:46
Because I don't know how you're going to effectively live without it now.
Daniel: 00:13:50
That's right. I mean, you know, it is. increasingly integrated into our lives. You know, if you have a phone, it will be automatically deployed. If you have a computer or a web browser, if you're using, you know, Microsoft Office or any of these apps, um, it will be, it will be part of us. Um, and I think one of the interesting things is, you know, where AI is so beneficial is how it can Um, allow us to, you know, interact with devices and information in an entirely natural way. You know, it's conversational now.
Daniel: 00:14:23
When we talk about, you know, before it was always, you know, have to teach people all these digital skills. And really what that meant was teach them, teach them to figure out how to work with a computer instead of teaching the computer how to work with humans, right? And so now anyone, you know, anyone who. Who can speak, who can sign, who can, you know, um, just express an emotion through their face or body language, you know, can communicate with these AI, uh, enabled systems, and I think that opens up so many possibilities for so many people. You know, um, who might otherwise
Daniel: 00:14:55
never really be able to sit down on the computer and maybe do research the way that, um, you know, people who are, are fully able there who have, you know, um, certain capabilities can do, maybe you're not literate and you want to interact with this. AI is just reducing so many barriers to, I think, creativity and jobs and interactivity. And I think that's amazing.
Hanh: 00:15:19
That's, you're spot on. And it really democratizes, it levels. the playing field. I don't care where you are in the world. You now have access. I call it enterprise even, right? Small businesses, whether it's 10 people to 10, 000 people, you really have access to the same tools for people. Let's say that's near and dear for me. It's like older adults, you know, the language barrier, the let's say disabilities and so forth. So now there's ways That you can have a conversation with your
Hanh: 00:15:52
phone, your chat application. And all of this is due to the recent GPT4o recent release, multi modal integration with their APIs and so forth. So it's exciting times, you know. It really levels the playing field for everybody. All ages, right?
Daniel: 00:16:12
That's right.
Hanh: 00:16:13
Yeah.
Daniel: 00:16:14
That's right. And there's, there's not that learning curve that I think, you know, we had before where, you know, you had, you had to kind of wait your turn, right? Because you had to have people coming in and showing you so many of the people that are adopting this technology now, they didn't have anyone teach it. They just tried it. And once they tried it, they realized they didn't really need a teacher. They could learn just by exploring. So I think one of the really interesting things here is that,
Daniel: 00:16:41
um, you know, anyone who's curious about this can really start now. There's no, there's no barrier to starting to use some of these technologies today for many people.
Hanh: 00:16:52
I echo that. So at the Center for Data Innovation, It's been involved in many projects and initiatives, so can you share a story of one that you're particularly proud of and why it holds significance for you?
Daniel: 00:17:07
Yeah. So one of our early projects was, um, thinking about open data. Um, you know, we, I started the center around 2014, uh, I guess 2012. And so one of the questions we had was, you know, um, President Obama had. created on his, uh, one of his first executives orders was around opening up government, um, having more transparency in government, having government, um, be more digital and work for citizens. But it was an executive order. And you know, our question, um, that we
Daniel: 00:17:37
kind of posed originally was, you know, might President Obama Be the last open government, um, open data president. And, and, you know, how can we make sure that doesn't happen? How can we make sure that, you know, this idea, which started with this administration, um, and had bipartisan support, was fully institutionalized? And so, you know, we looked at what would it take to, to really move forward and take that, um, executive order and turn it into legislation. And, um, through numerous conversations, um, on the Hill, Um, with, um, any
Daniel: 00:18:12
companies who are doing really interesting work around open data, academics, nonprofits, um, we worked, uh, together with a whole, um, coalition to build up, I think, broad support for what became the Open Government Data Act, um, which became, uh, passed law, um, actually signed by President Trump, um, you know, many years later, so you think about the, the time it takes from, you know, ideas, let's take this idea and, and really You know, formally, um, codify this and law and getting it to something that has now been implemented. And and now agencies have this
Daniel: 00:18:43
responsibility of publishing their enterprise data sets. So they say these are all the data sets we have. Um, they are making, you know, there's now standards around making them available. We have chiefs data officers who are focused on making this data available. And there's just been so much thought into thinking through how government agencies at the federal level, you know, create value through their data and make sure that it's put to useful purpose. And now we've seen that idea, of course, at the state and local level as well.
Daniel: 00:19:14
We've seen many businesses embrace open data. I think it's something that's really useful. Um, and we're also seeing, I think, this, you know, um, the spirit, um, reflected in all the innovation around Ai. As you mentioned, AI is, you know, strong and useful when it can be trained on, um, large data sets. And a lot of this data is coming from government. And there's just huge opportunities to continue to make progress in this space. So that's an area, you know,
Daniel: 00:19:39
that we started initial work on. And I'm, you know, delighted to see that it kind of made its way all the way through. Um, and, you know, hope, hope to see a future other ideas like this, where, you know, um, there's just so much that I think government can do hand in hand with industry and academia and nonprofits, um, to advance, you know, opportunities to, to leverage data and to make, you know, data driven decisions.
Hanh: 00:20:05
Awesome initiative. Now, one of the key challenges in promoting data driven innovation is balancing its potential benefits with the need to address public concerns and mitigate risk. So, how do you approach this delicate balance in your work?
Daniel: 00:20:21
So, I think the most important thing is not to let fear dominate. Um, I think some people are probably familiar with the, um, you know, the Gartner hype cycle for new technologies where, you know, it's a, um, at the beginning you have a technology come out and, um, not many people know about it and it kind of reaches this kind of peak where, um, you, you hear a lot of claims that maybe aren't true. And then finally, you know, there's, they, they call it the tropical disillusionment and then things kind of let go out. Right.
Daniel: 00:20:46
And so there's a lot of technologies that I think are overhyped. Um, on the, uh, kind of the, the counter side to that is what I would say. There's a technology panic cycle as well, where at the early stages of technology. Um, first there's just a few adopters who are, you know, kind of the innovators and they're excited about it, but at some point. You know, fears about new technology outpace understanding of it. And I think we see that happen again and again with many new technologies. And we actually have done some
Daniel: 00:21:13
reports looking historically at various technologies and how they went through these cycles. Um, even things that, you know, I mean, now we look back on, you know, motor vehicles. They had these red flag laws where they, um, some jurisdiction said, um, because cars are so dangerous, the solution is going to be, um, before you drive a car, you just have someone walking in front of the car waving a red flag. Um, that's, you know, not a scalable solution, right? Imagine if every vehicle had someone
Daniel: 00:21:38
walking in front of it, waving a flag. Um, we, you know, there were concerns about, um, you know, the printing press. And when we started moving from the printing press to Um, pulp fiction books, people were saying, well, do we really want anyone to be able to publish their ideas? Do we want anyone to have access to pamphlets? What would you know, those the kind of pulp fiction books due to the minds of youth, you know, they're going to be reading um, just you know, these uh, pure sci fi and fiction
Daniel: 00:22:03
things instead of the, you know, uh, esteemed, you know, historic, uh, English writers, for example. Um, so, you know, we've all, we've seen so many of the same fears, you know, fears about children, fears about impact on society, um, fears about, you know, the harmful effects, you know, people concerned about, um, you know, uh, when gas was used for lighting the noxious fumes in people's homes and what that would do to their health. All of these same fears that we have about technology, um, you know, radio waves in our brain and what that
Daniel: 00:22:34
might impact some very similar things. And so I think it's really important that we don't let fear dominate. It's also important that we be guided by evidence. So, you know, the point isn't to say that, you know, some technology might not be harmful or some technology might not have problem. It can, and we should always investigate that and look at that with an open mind, but we can't be motivated primarily by fear, um, because when we see fear being the dominant emotion, we tend to end up with, you know, bad laws
Daniel: 00:23:06
and regulations that hold us back. And in this case, particularly I think around AI, There's just so much opportunity and promise. We don't want to see that held back. We don't want to see, you know, the opportunities to use AI to, you know, find a new medical, uh, cure held back by 10 years for someone who needs that. We don't want to see AI that can be used to address loneliness or provide, you know, opportunities for people to age in place. We don't want to see that delayed by 10 years because that will affect so
Daniel: 00:23:35
many, you know, people who could use that, you know, Those benefits now. And so I think we have to, you know, continue to iterate and evolve and track risk and challenges, but not let the perfect be the enemy of the good. In these cases, look at opportunities where the technology is often not perfect, but maybe it's better than what we have today. And so, you know, use that as a metric for deciding, you know, when we move forward and when we slow things down.
Hanh: 00:24:01
Yeah. And you know, I love that what you said, don't let fear dominate, because let's say if we do. We might not be driving cars or flying right now, we'll be using horse buggies and so forth. So we really need to adapt innovation, you know, with enthusiasm and caution. And I think the key is be a part of the conversation and learn and grow and entrust in AI. And I always recommend for folks when trying to use AI. Is that start small, you know,
Hanh: 00:24:32
something that perhaps it's so repetitive, uh, such a nuisance that they would just love to not deal with. So start small and gain confidence and then you can go further from that.
Daniel: 00:24:47
That's a, that's a really great suggestion. Uh, and I wholeheartedly agree. I think there's, um, these opportunities to use AI to do something, um, that you also don't like to do. Right. And, you know, That's one of those things where if you use it for in ways that make your life better, you know, That's you know, it's a win and it's always going to be a win. One of the things I use it for is Um, I don't uh, I like to Have help writing messages to people to make
Daniel: 00:25:18
sure I phrase things, you know, kindly appropriately Um, and I love using the technology To just quickly, instantaneously run through an email and say, is this the best way to say this? And you get that answer. And it's, it's incredibly useful.
Hanh: 00:25:38
And you know, I think what AI has helped me, for instance, like I would ask it a couple of questions, but what it uncovered for me is a whole wealth of knowledge that I didn't even know what to ask. Do you, you know what I mean by that? Yeah. Um, So it really, it doesn't cause you to become lazy or dependent on it. What it does for me at least, it improves my critical thinking that I didn't have before. Right. So I think it's wonderful.
Hanh: 00:26:05
So now as a leader in the field of data policy, I'm sure there are times when That you had to navigate challenges to build trust, perhaps somebody that didn't trust you, the policy or the data that you were using, and you had to take an unpopular stance on an issue. So can you discuss a situation like that where you face this type of challenge and what did you do? How did you approach it?
Daniel: 00:26:30
Yeah. So there was, um, I think early on when, especially when I was focused on, on data policy and data driven innovation. And, you know, at the time. This isn't something that many people were thinking about. You know, this is kind of pre the data science boom and big data boom. Um, and whenever people would want to talk about data, they want to talk about privacy and one of the important points that I was trying to emphasize is that we need to go beyond the privacy conversation around policy around data.
Daniel: 00:26:59
We need to be thinking about data. Um, not only, yes, how do we protect data, but also, are we collecting enough data? Are, is there more data that we should be collecting? Is there better data that we can be collecting? Who is being left out of the data collection? Um, how are we making sure that the data is used well? And also, you know, really emphasizing this point that in many cases, there are trade offs between privacy and innovation. And that is something that, um, a
Daniel: 00:27:22
lot of people who are advocating for privacy Did not want to acknowledge, did not want to, um, you know, uh, have that part of the debate because nobody wants to be against innovation. They weren't necessarily against innovation. They were just for privacy. Um, and you know, just I, I would freely admit that sometimes being pro innovation means there's trade offs with privacy on. I'm kind of saying you might get less privacy. Um, but that was a very unpopular opinion because it was, you know, um,
Daniel: 00:27:52
you know, you, you, in some ways I was making the argument that effectively some groups were against innovation. Um, and so, you know, I, I think what's important there is that, um, Um, in this debate, in this conversation about, you know, where policy should go on these technologies, um, we get really clear on what it is exactly that we want, because in many cases, um, you know, people were pro privacy, but they're also pro health care, right? You know, they're also pro education. Um, and so what we, I think, should be able to agree on Is that, you
Daniel: 00:28:30
know, if the goal is, for example, to improve education, public education through data analytics, through better understanding of how students learn, um, that should be the goal. And we should focus very practically on how do we get there. And you know.
Hanh: 00:28:47
It's not one or the other, right? You don't have to choose one or the other. You can collaborate with all key stakeholders of what you're doing to achieve a common goal. So it's another attitude shift as opposed to, you know, something that's so absolute. Well, perhaps it isn't in this case. Perhaps it's more of a, a shift paradigm shift so that you can move towards a goal that you can still have privacy and achieve. Oh. Your health goals and
Hanh: 00:29:15
education goals and so forth.
Daniel: 00:29:18
And recognize that, you know, at the end of the day, many people have different values and choices and we can't pick just one for everyone. You want to give people as much choice as possible. people. Some people, for example, You know, when they have a rare disease, they opt in to sharing their data as much as possible because they want to see any progress that can be made in that area. You know, people with, um, you know, children that have childhood diseases, chronic diseases,
Daniel: 00:29:43
they want to see that progress. They're willing to make those tradeoffs, you know, in other cases. You know, there might be a, a non serious medical condition that is very private that somebody doesn't want to share. And that sharing looks different. And so I think we have to recognize that giving people as much choice and opportunity is really important. And there's not kind of a, there's not a one size fits all solution, right? It doesn't, you know, people are usually very unhappy when, you know, whether it's an advocacy group or
Daniel: 00:30:12
the government or a company saying, this is the way you must handle data. Give people more choice and then we get more options for everyone.
Hanh: 00:30:21
Optionality and it's personal. Right. And what I hear that's right is, you know, and nowadays with the advancements of ai, you can do all that. You don't have to choose one or the other. You can achieve privacy, transparency, and achieve your, your health goals, whether you are. A practitioner or a hospital. So now in your work, I'm sure you collaborate with many folks, stakeholders, like policymakers, industry leaders, and academics to drive progress in the data privacy.
Hanh: 00:30:58
So how do you foster these connections and facilitate productive conversations, because they have conflicting goals, for instance.
Daniel: 00:31:08
That's right. You know, I think it's, um, in, in most policy, it's a debate, right? It's a debate of, of facts and, um, evidence and persuasion. Um, sometimes it's a debate about values and goals. And I think first, the first stop is figuring out what are you actually debating? Are you debating And so, you know, that's I think the first step. Um, and then you figure out, you know, do we have a common common
Daniel: 00:31:35
interest and how can we work together on many of these areas? And I think that's why, you know, there's there's a lot of talk. I'll always in the news about, you know, divided government and the partisan government and Um, but when you look at so much of the legislation that comes out of Congress, um, around tech policy, around data policy, it is very bipartisan. You know, we see stakeholders from all sides come together and say, you know, yes, we want to use data to advance health care. Yes, we want to collect
Daniel: 00:32:01
better data around the census. Yes, we want to have better, um, you know, data about, um, Uh, even global warming and climate change because it affects our coastal communities. And that is, you know, the coast affects everyone, um, red states, blue states. And so I think there's so much work in this space that it really truly is, uh, bipartisan. And so I think just focusing on, you know, again, um, where can, you know, data have a positive impact? How can data be used for good? Uh, there's a lot of, a lot of interest
Daniel: 00:32:31
and collaboration across the board.
Hanh: 00:32:35
So true. Now, data driven innovation. Has the potential to address some of the society's most pressing challenges, health, education, government, like we discussed. So what are some of the most promising opportunities do you see?
Daniel: 00:32:50
Yeah, I mean, so education I think is one of the most important, um, and I think one of the most exciting opportunities. We don't have personalized education in the United States, um, especially in the public. Uh, school system. And what I mean by that is, you know, everyone learns at different rates. Everyone comes to education with different skills and abilities, different interests. And, you know, I think back to when I was in, uh, school, you know, you had a large classroom, um, you had one teacher and
Daniel: 00:33:15
they were teaching to the middle, right? They were teaching, um, to kind of the average student in the class. If you were head, you were probably a little bored. If you were behind, you were probably a little confused, and those differences get bigger and bigger every year, and that's a problem. Um, and so with AI and data, I think we have so many opportunities to deliver the type of education that each person needs. Somebody is, you know, going faster on math. Great.
Daniel: 00:33:45
Let them, let them zip ahead. They will learn more, they will stay engaged, and they will enjoy school because they're being challenged and they have these opportunities. If somebody's, you know, doing, uh, great in reading and language arts, allow them to accelerate in those areas. Um, and then, you know, the areas where people need more work. You know, that's where the educators can spend more time doing one on one work with them doing enrichment. Um, and also, I mean, that's at the individual level.
Daniel: 00:34:13
Then you think about, you know, at the school level and just how we manage schools and just the need for better data to figure out, okay, you know, are there problems going on the school? Are there, you know, Are there health issues going on at the school? Um, you know, where are the buses? You know, just logistics that, you know, data can help with that. And then you start thinking kind of bigger picture, what kind of, you know, all these different school systems have various types of interventions, whether it's, you know, uh, drug interventions, gangs,
Daniel: 00:34:39
you know, uh, special STEM programs. The question's always, are those programs effective? And the only way to know that is by looking over time, um, usually, you know, sometimes it's, you know, 5 to 10 years and seeing, okay, you know, where have these students ended up in the workforce? How are they doing? Are they thriving in society? And you have to have good data to do that. You have to have not only these kind of educational systems, this longitudinal data systems that are about the schools. You also have to have
Daniel: 00:35:10
it about the workforce. And so many states have started to build these, they didn't build them so they were interoperable. They didn't build them to really track this over time. And that's one thing that I think we're starting to think about. I think that's a huge opportunity to really improve our workforce and our students and how we learn.
Hanh: 00:35:30
I think. The education system needs to have a course, AI integration. If you can pick up a phone, if you have a computer, a laptop, and if you start integrating your day to day usage of this, that student or that school system needs to have a dedicated course in teaching students how to integrate, how to use it wisely, as opposed to seeing it as cheating. There's nothing wrong with growing, developing, opening your mind. And if you are ahead, that's great. But let's say if you're behind, well, here
Hanh: 00:36:04
is a tool that you can utilize offline outside of the classroom and so forth. So the attitude ought to be embraced as an enhancement augmentation, as opposed to like, you're so bad for using it. You must be cheating.
Daniel: 00:36:21
Exactly. And I just think about, you know, these tools that, as you mentioned, you know, the new release of ChaiCPT, it's multimodal, it can see things. And think about a student that's struggling with, how do I solve this math problem? You can point your phone at it, and now you have a personal tutor. That you know, students didn't have access to this speaks to you. This is across income levels. As long as people have access to a phone, that's just incredibly powerful.
Daniel: 00:36:45
But we have to figure out how do we actually get this widely deployed? So students know how to use it. As you said that they're trained on the appropriate ways to use it. So it's augmenting their education. So it's helping them learn better. It's not just a kind of a cheat code for getting through school where they're not actually learning. Want to make sure that they're actually using it to, to get a better education. I think that possibility is certainly there.
Hanh: 00:37:09
And that's going to take a huge paradigm shift for the administrators, the superintendents to create a dedicated course on AI and how that needs to be integrated in the school and home life. They intersect, right?
Daniel: 00:37:24
That's right.
Hanh: 00:37:25
Because I still hear, you know, my kids are not, they're graduating from college and so forth, but like, I still hear from, you know, elementary, middle, and high school. It's still a bad thing. It's, it's perceived to be cheating. So you kind of have to hide it.
Daniel: 00:37:40
That's right. And that needs to change. And then I think those perceptions will change. And some of it will be generational because at some point, maybe students, they're going to be using this at home. They're going to be using this, you know, instead of Google.
Hanh: 00:37:53
Yes.
Daniel: 00:37:54
And so there's not going to be a way of kind of taking it away from them.
Hanh: 00:37:57
So, data technology is constantly evolving. So how do you stay informed and how do the center of data innovation remains at the forefront the development?
Daniel: 00:38:10
A lot of reading and a lot of talking to experts. I think that's one of the most important things in technology is that you actually understand, as I said, kind of deeply how these things work. I remember when I was working on blockchain, for example, you know, I had to go in and really, you know, deeply look at, okay, how exactly, you know, are these algorithms working? What goes into it? The same with machine learning, um, and AI. You have to study the algorithms.
Daniel: 00:38:34
You, it's not enough to know kind of vaguely, this is how it's working. You need to understand really what's happening under the hood, um, I think to make effective policy. Now that everyone needs to do that, But for the work that we do in policy, I think we have to have that strong connection. Um, and I think Congress is getting better at this, too. There's been a number of, um, fellows that have been placed through, um, AAAS, um, the American Academy for Science, um, that has brought in AI experts and placed them in congressional offices.
Daniel: 00:39:06
So that as some of these, you know, policy makers are thinking about legislation, they have someone in house who is an actual, um, you know, computer scientists who can provide them that expertise so that as they're writing policy, it actually maps to where the technology is.
Hanh: 00:39:24
Very true. So the center of data innovation produce numerous reports over the years. Can you share an example of one that you believe has had a particularly significant impact on shaping data and policy?
Daniel: 00:39:41
Yeah, so one of our earlier reports was on Um, what we call data poverty or the data divide. And this is a concept that I think has, um, gotten a lot more recognition, especially in the age of AI, where people are concerned about bias. But basically, we made the argument that, um, for many individuals and groups, the biggest problem for them is not that too much data is being collected about them, which would be kind of the privacy concern, but that too little data is being collected about them. And for that reason, they might
Daniel: 00:40:08
be left behind as we see data driven innovation advancing. Thanks for listening. And so, for example, you can think about, um, health care, for example, where certain populations aren't included traditionally in medical research. Um, they're not the core representatives in clinical trials, for example. Um, you can think about many areas where there are data gaps, where, for example, maybe a wealthy neighborhood has air quality sensors and a poor neighborhood doesn't. And so, you know, when you, um, can
Daniel: 00:40:37
use an app to figure out whether or not you should go bicycling if you're in a wealthy neighborhood. You can do that if you're in the poor neighborhood. You can't. Um, there's so many areas like that where there is these data divides and conceptually, you know, we've had this long tradition in the United States and globally of thinking about the digital divide where people didn't have access to the Internet or computers or digital literacy. And the argument that we've made is
Daniel: 00:41:00
that there's also this data divide, um, and that it's something that we should recognize and address through policy to help close that gap. And it's something that I think has increasingly gotten attention. We've seen, um, a lot of work focused at the global level and trying to, um, collect data from all parts of the world, thinking about things like language gaps and data sets, thinking about, um, Um, how well represented different groups are in data sets. The Census Bureau has been rethinking, for example, it's
Daniel: 00:41:28
different demographic categories. We've seen new thinking in terms of surveys the government does to make sure that, um, for example, in long term care facilities, are they asking, you know, good questions to figure out that there might be unique differences between older adults, that it's not just, are you older, but what languages do you speak? Um, you know, what's your relationship status? What's your sexuality questions that Um, so just thinking through those data questions. It's usually important.
Daniel: 00:42:00
And so I think that report and some of the subsequent ones we've done on that topic have had a lot of impact on this conversation.
Hanh: 00:42:06
That's great initiative. No data policy issues often transcend borders and require a global perspective. So how do you maintain this broader view while also addressing regional and local concerns?
Daniel: 00:42:23
Yeah. So you're right. I mean, so much of data is global. And one of the, um, points we've made in a recent report is that with big data, especially, you know, these larger and larger data sets, um, it's no longer possible to, um, just expect, um, One organization, um, one company, one country to collect all the data about a particular topic. That was really the old model of thinking. It used to be, you know, if you wanted to have, um, you know, World Health Organization or something, maybe they're
Daniel: 00:42:50
going to collect all the data on malaria. Right. We're moving to a world where they're going to be lots of different partners that have data and what we need to be thinking about is how do we build global data infrastructure so that data collected, um, you know, and, uh, South Africa and Iran and Colombia and the United States and Australia. They're collecting data about the same topic, the same theme, you know, that that data is interoperable, that's in a similar data format, and that it can be shared, and that we have these, you know,
Daniel: 00:43:20
federated data networks, um, and that's a policy problem, that's a technology problem, that's a data standards problem, that's a skills problem, um, and it's really hard to think about how do you bring all that data governance together, but that's what we have to be thinking about, how data transcends borders, and that For it to be useful and valuable, it should transcend borders that we don't want data localized. We don't want it restricted on where it can be used. We want it to be global. Um, so that's, uh, I think that's one of
Daniel: 00:43:46
the most important issues that we work on. Do a lot of work on kind of cross border data flows, thinking about data as part of trade policy as well. Um, so just lots of opportunities to really push policymakers to think about data in new ways.
Hanh: 00:44:02
Well, thank you so much. We covered so many points. So we're at the tail end. Is there anything else that you would like to add?
Daniel: 00:44:09
Um, you know, we, we covered a lot. I, I just want to say thank you for this conversation. It's, I think, so important that we have, you know, so much of this technology available to everyone because benefits, um, are things that I'm very optimistic about and I, I think have great potential.
Hanh: 00:44:25
I echo that. Well, thank you for joining us in this insightful discussion on data driven policy and innovation with AI. So, today's talk has shed light on the crucial role that data and technology play in shaping our society and driving progress. So, throughout our conversation, we explore the fascinating intersection of data, AI, and AI. Public policy. We went into the challenges and opportunities that arise when leveraging these powerful tools for societal benefit.
Hanh: 00:45:01
Our discussion highlighted the need for ethical innovation in AI and data analytics. So as we create and use these technologies, we must focus on being clear, responsible, and beneficial to people in society. And today's insights have shown us that. The amazing possibilities of data driven innovation, and that we can use AI and data to solve huge problems, boost economic development, and enhance people's well being in significant ways. So we hope that this conversation has motivated you to reflect
Hanh: 00:45:40
on the impact of data. And AI in our future. So I encourage you to keep learning about this exciting field and participating in discussions like this so that we can advance and improve and make change and good change for the future. So thank you for being a part of this enlightening discussion and keep innovating and striving towards a better, more data driven world. Thank you for your attention. Well, thank you.
Daniel: 00:46:13
That was fun. Thank you so much.
Hanh: 00:46:14
Yeah.
Daniel: 00:46:15
Thanks for having me.
Hanh: 00:00:00
Hello. Welcome to AI50, where your data meets innovation. At AI50, we skillfully deploy cutting edge AI technology. To create a large language model apps tailored specifically for the needs and preferences of the, uh, 50 plus demographic. So our mission is to harness the power of data and innovation to revolutionize the way this demographic interacts with technology. So today's topic is shaping the future of AI investments, and we have an
Hanh: 00:00:38
exceptional guest joining us today. Deedy Das, who is the principal at Menlo Ventures and a founding member of Gleam. His journey is nothing short of remarkable. As a leader in AI investments. DD has been at the forefront of shaping the future of AI and enterprise technology. So his deep technical expertise and strategic vision have undoubtedly left an indelible mark in the industry. So in a world where AI is rapidly transforming every aspect of our lives. Deedy's insights are so invaluable.
Hanh: 00:01:19
He's witnessed first hand the power of AI in revolutionizing knowledge management through his work at Glean. And now, as an investor, he's helping to fuel the next generation of AI powered startups. So Deedy's story is one of passion. Perseverance and unrelenting pursuit of innovation. It's a testament to the incredible potential of AI and the visionary minds like Deedy, who are driving its progress. So as we discuss and go into Deedy's journey and explore the frontiers of AI investments, We know that you, our
Hanh: 00:01:56
AI audience, will be captivated by his unique perspective and a wealth of knowledge he brings to the table. So get ready to be inspired, challenged, and enlightened by one of the sharpest minds in the industry. So, Deedy, welcome to the show.
Deedy: 00:02:18
Thank you for that lovely introduction. It's a pleasure to be here.
Hanh: 00:02:22
Yeah. Well, thank you so much. Um, yeah. So to start things off, could you share with us something about yourself, uh, that many people might not know, or, um, it could be a unique experience, a hidden talent or an interesting fact that help us understand what has shaped your journey and perspective.
Deedy: 00:02:43
I think there's a couple. I think the one I. I think people ask about most often is because I grew up in multiple countries, I spent You know, age three to 10, I was in America. I was in the Bay area cause my family moved here. And then from 10 to 18, I grew up in India. I often get asked, uh, how that experience was like and how that's shaped me. But one of the funniest quirks of that experience is there's a A bunch of people who do this as
Deedy: 00:03:13
well, I tend to code switch accents. So I have two accents. And then when I'm talking to people in America or Americans, I would speak in this accent, but when I'm speaking to someone from India, I would speak in my Indian accent, which is a nice quirk of having literally grown up in both places.
Hanh: 00:03:32
I can relate. I have an accent too, , except I speak Eng English with an accent for getting my S's and so forth. Well, that's exciting and, and thank you. And I'm excited to learn more about your journey. Now, your career path has taken you from engineering to product management and, and now to venture capital. So can you share with us what experiences or. Individuals have had the most significant impact on shaping your journey, let's say during your
Hanh: 00:03:58
time at Glean and Menlo Ventures.
Deedy: 00:04:05
Yeah, of course. I think I wanted to actually start with somebody who shaped my journey at Google that also, and then I can talk about one person at Glean and Menlo as well, even though it's only been several months for me at Menlo. The person at Google that was most instrumental in shaping my journey was maybe my first manager. His name was Eyal. He's an Israeli guy. He rose very quickly in the organization. He was extremely talented. Um, I still remember some anecdotes that
Deedy: 00:04:34
he used to say, which is I asked to ask him, Hey, how do you, how do you work so hard and how, how are you so effective? Um, and he would say, Man, Google is the easiest job I've ever had. You should have seen how hard my job was in the military when we were actually trying to save lives. Uh, I did that for six years. Search, that's kind of a low stakes problem. And with that anecdote aside, what he used to really say that really inspired me is at that time, I had a lot of doubts about whether.
Deedy: 00:05:08
I should be doing engineering long term, like what was this career going to look like for me, you know, 10, 20, 30 years from now? And I asked him, like, hey, you know, this product management thing is, is, is really hot. A lot of people seem to be doing it. And from a personality perspective, I think I'd be pretty good at it. Like, I enjoy talking to people. I, I, I like thinking about product and doing engineering. What should I do? And his answer was really simple.
Deedy: 00:05:35
He's like, most PMs can't do engineering. If you're an engineer, engineer who can do product, stay an engineer. Don't lose that skill. That's a hard skill. You never want to let that go away. And that's some advice that really stuck with me because I was seriously considering switching at that point. And I decided not to, which, you know, served me really well because when, and then I'll tie this together. When I joined Glean, there's no way I could have got a job at a, at a company with just five people at
Deedy: 00:06:00
the time when I was interviewing. Um, if I was in product, the only hiring need was engineer. So that opportunity wouldn't have even worked. So when I joined Glean, then brings me to the next person who was really, um, a big shaper of the way I think and, and, and my career, and that was the CEO and the founder, Arvind, Arvind is, you know, obviously a tenure Valley veteran, uh, started, uh, He was one of the first distinguished engineers at Google, where he reported to Larry, where his title was to lead speed at Google.
Deedy: 00:06:34
Very, very impressive guy. And then he started Glean. But if you speak to Arvind, he was just unlike any buddy of power that I would think. He's such a simple man. And all he would say is, Deedy, I don't do this for money. I do this because I love it. And, and I'd ask him questions like, Hey, what do you do on weekends, Arvind? Like, how do you relax? And And he would say, this is relaxing. I build product. That's what I like to do.
Deedy: 00:07:03
And I just love that passion. He wouldn't spend on much. He was a very, he lived within, very within his means. He just didn't care about the glitz and the glamour. He really cared about the job and was a very first principles thinker about execution. Anyway, lastly, I'll say at Menlo, even though it's been a very short period of time, One of the people who really inspires me at Menlo is somebody I work very closely with. He's, his name is Tim Tully.
Deedy: 00:07:30
He was used to be the ex CTO of a company called Splunk, which I think is a 25 billion public company right now. And what I love about Tim is, you know, Tim is about You know, pretty late in his career. He's he's in his late forties. I imagine. And for somebody of that age, I know I just grew up thinking that people of that age are a certain way from like that, but Tim just has this, this glitz in his eyes. He just loves technology. And I, I, I see him ask him, what do you do for fun?
Deedy: 00:08:02
And he's like, Man, this new thing came out and I just started coding on it. And it just has this like childlike curiosity, which I emulate, you know, I always say when I'm older, if I lose the childlike curiosity, it's game over. Um, that's sort of, I know they're really inspirational.
Hanh: 00:08:19
That is awesome. That it's just wonderful to learn how those crucial moments and mentors have influenced your direction. And. Inform your view in the industry. And now I like to know what your views are. People are approaching 60 because that's where I'm at.
Deedy: 00:08:36
You don't, you don't look like you're approaching 40 even.
Hanh: 00:08:40
Cause when you said, you know, he's in his forties late in his career. I'm like, wow, to me, 40 is not. Nearly late, almost 60. And I feel like, you know, thriving for learning. I mean, nowadays with the advancement of AI, you gotta, you gotta keep learning. You have to have an open mind, a life learning attitude and keeping up with the pace. It's challenging because every day is new and well, an example of. This, uh, Monday with the GPT 4. 0 release and how this transform
Hanh: 00:09:11
multimodal and so forth. And to be honest, I'm still kind of, I don't know, in candy land, just hearing all these advancement is so excited for it. So yeah. Okay. Well, as a leader, we often face challenging decisions that can have far reaching consequences. Can you share a story about a difficult choice you had to make while leading? The development of Glean or investing in AI, and what lessons you took away from that experience?
Deedy: 00:09:44
I think the most, maybe this is a cop out answer, but it's a recurring series of challenging decisions, which all are pretty similar in my opinion. What I've observed at Glean is What's happened in at least some part of the tech industry is if you look at these big tech companies, like, I mean, especially Google and Facebook, because I've worked there, I don't know as much about Microsoft and Amazon as deeply, but Google and Facebook for a very long period of time became a money printing machine. And because of that, a lot of the talent that grew their careers have
Deedy: 00:10:22
become quite senior have become. Quote unquote experts in their field. In my opinion, many of them haven't actually driven anything. They have sort of ridden the wave, which would have gone up anyway and did incremental work that isn't really that challenging. And in that culture, what was promoted was really an attitude of just being nice. And if you were to succeed at Google and Facebook, I think like the biggest way to succeed is just making everyone happy around you. Don't rock the boat.
Deedy: 00:10:56
This is what they would say a lot. I Google it. Don't rock the boat. Everything's going well. Metrics will move 1 to 2 percent every year. That's all you need to do. At a startup, that just doesn't work. No, different mindset. It's a very different mindset. What I realized is, you know, while we were building Glean Assistant or Glean in general, is you just need this idea of radical candor when you're making decisions and you
Deedy: 00:11:23
have to remove ego from the process. And that's not something that, you know, even initially I found that a little bit challenging, but there were a lot of hard decisions you had to make, even for people and colleagues that you work with that you really like, where you just have to be honest and sometimes say, you know what, like, I like you, but to make the correct decision, I cannot take the average of the five ideas of the colleagues I like. I need, we all need to figure out what is the best thing and what works. And you have to put your ego aside to make those decisions.
Deedy: 00:11:58
So there were multiple, multiple small decisions, you know, on a weekly basis where you really needed to dig deep. And it's really hard to do in practice where in a meeting you're sort of zoning out, like multiple people are talking, you're context switching, someone brings up something that they're doing, and you don't want, you don't want to go like, Hey, early morning, that idea, let's not do that. That's a bad idea. It's a waste of time. We're going to go the wrong direction. You have to be there always on always
Deedy: 00:12:23
being somewhat confrontational, honestly, in order to make that product succeed and to make the good decisions to make it succeed. And. A lot of that I also learned in, um, more, uh, it was sort of driven into me when I was working at Google Israel because I feel like Israelis just have that culture of, they always tell you they're very straightforward and candid. And, uh, without being personal about it. So I really learned how to do that there. And that sort of drove me to, those are the kinds of decisions you have to make
Deedy: 00:12:58
it in, in order to make the products.
Hanh: 00:13:01
And, you know, to add to that with a startup, the mindset is innovate, disrupt, incorporate a place like Google. It's conformance. Not to rock the boat. So they're completely in misalignment, but it's, it's wonderful to have folks like you that experienced both and a very understanding and adaptive. So that's great. And I appreciate hearing the stories, the journey, and it shows how dealing with complicated choices and, and, um, the role that you were in and the insights that you've gained.
Hanh: 00:13:35
Improves leadership and investment skills, which we'll get to next. So that's great. Now the AI and infrastructure sectors constantly evolving with new breakthroughs and trends emerging at rapid pace. So how do you stay on top of these developments and how do you leverage the knowledge in your role as principal at Menlo Ventures?
Deedy: 00:13:59
I think. Every investor has a different way of doing this. Most investors are, are not technical. And one of the reasons Menlo hired me is because I think they realized that actually having, especially in this era of technology, understanding the technology is pretty critical to making good investment. You know, we see all the time how. There's so many unicorn companies that sort of collapse and, you know, a lot of people are left wondering, okay, how did this company get
Deedy: 00:14:34
to a billion plus valuation if it can just collapse the next day? I thought a billion plus minute. Doing something. And when you dig into it, you realize there's multiple reasons. And that's a whole topic, but a big part of that reason is people are investing on credentials. They're not investing on technology because they oftentimes don't understand the technology. So if you look like you're a published person on Google scholar, you worked at deep mind, you went to Stanford
Deedy: 00:14:58
for your PhD, you're probably going to raise a lot of money, whether or not you're doing something meaningful. So anyway, long winded. Road to say, how do I stay on top of these things? It's pretty simple stuff. You know, every day I enjoy it. So I think that's really key to it. But every day I'll, I'll do at least an hour or two of just reading on hacker news, tech meme are some of the common ones I go to, I spend a lot of time on Twitter reading, but you need to create Twitter for
Deedy: 00:15:27
you to get real value out of it. Um, and then the most valuable thing for me, uh, the two other valuable things for me, I should say that one is you. I've noticed in startup world, there's such a dissonance today between what people are saying and what the actual thing does. And so actually playing with something often gives you, even running, even let's say GPT 4. 0, running five different queries on GPT 4. 0 will tell you way more than reading a hundred tweets about it.
Deedy: 00:15:57
Because all of those hundred tweets are going to say the same thing. They're going to take the announcement, they're going to be like, wow, this is the future, this is amazing. And you're not actually going to know what really changed. So that's one. And the second one is, I think, I think a lot of investors do this and we have to is you, you have to keep talking to other. Industry experts who have a different vantage point. Um, and I don't think of experts as necessarily, Hey, 20 years of
Deedy: 00:16:22
experience, senior director at now. I mean, you can talk to people with 25 years, we're 25 years old, and they will tell you so much more about a company close to the metal and just talking to them and understanding, Hey, how are you thinking about things? Why do you think this in probing also really helps, um, shape your, your vision. You need to hear multiple different views on things. For you to understand what is, what is actually closest to the truth.
Hanh: 00:16:46
Being close to the consumers, the ultimate users, right. And truly solving pain points and looking at it from their perspective, rather than just being product focused. I think I see that often. What's that?
Deedy: 00:17:00
I love that you mentioned that I have a story, the recent story that I can share with you about, about that. You know, like we're, we're in a little Silicon Valley bubble and everyone's always talking about the same things and AI and tech and all this stuff. It's great. I recently was with a friend of mine and I was telling him how, how, you know, crazy I was about all this stuff coming out. And it's sort of like, you know, half of the stuff you said, I don't even know what it is. Can you, can you show me?
Deedy: 00:17:25
And so we sat on a, on a couch and we watched a bunch of YouTube, a bunch of videos, And it was so interesting to me to see that I was drawn to the videos that were technically interesting to me. These are demo videos like OpenAI, Google, whatever. Um, UDO, just a bunch of AI tools. And the ones that he was drawn to were so different. Um, and that sort of made me realize. Like, yeah, consumers, as you said, users think very different from who are always, you know, in the middle and we're, we're, we're going to be
Deedy: 00:17:57
influenced by what people think about the technology more than your actual consumer. So it's, that's another thing that you have to be wary about.
Hanh: 00:18:06
I agree. I tell my team is that we're not in the business of producing products. We're in the business of solving, solving problems. For the demographic 50 plus, I don't care how old you are, but when you're working on this, you have to wear that hat 50 plus. That is, that is where you are, you know, and it's so, it's so important because, um, to understand and to come up with products that are usable in that demographic, it's not just product focus. You really have to understand
Hanh: 00:18:33
their behaviors, their, where they, they shine, where they decline. Right? There's cognition. There's visibility. There's ability to understand the instructions. There's so many, um, nuances. So it's very important to be consumer focused rather than product focused. And, you know, we can't explain enough, right? That's, that's a huge topic in itself.
Deedy: 00:18:58
Exactly.
Hanh: 00:18:59
Yeah. So building high performance team is very important for success of any organization, especially in a fast paced world of startups and venture capital. So what strategies have you found to be most effective in assembling and leading exceptional teams?
Deedy: 00:19:18
There's a couple that I want to talk about. One is, and this is something I, I learned from, from Glean and from, from Arvind, when you're building a team from scratch and you don't have a brand, uh, associated with it, there's an element of. You cannot apply the same hiring principles as a corporate would. Um, their needs are very different. When you're building a team, it, there's a snowball effect of reputation. So the first people that you hire, not only have to either be extremely exceptional at what they do, but
Deedy: 00:19:54
also they have to be almost, I would say an inspirational or, or a connector in their network. I'll give you one example. We could have hired one of 50, say new grads from Berkeley when we started hiring new grads, but Arvin had a very interesting insight. He's like, you always want to hire. The TAs from the, from the most popular classes, hire that TA next year, you get 20 more people who want to work at your company because they follow what he does because they're, they look up to him. And instead, if you hire the best person
Deedy: 00:20:26
in the class, who's just not well known, great, you got one good person, but the next year you might not get, you know, 20 more people banging on your door. So that's, that's one. The second thing is, is a bit more, uh, you know, I would say strategic about how you pitch what you're trying to hire for. And. When, uh, when we were hiring at Glean, there's some strategies you just don't want. One thing is you never start with comp. When you start talking about how much you get paid, you're already,
Deedy: 00:20:58
you're hiring the wrong kind of person, or you're hiring, even the right person gets distracted by that and starts making bad decisions. Then they start paying me, oh, but they're not paying me, oh, but I should get paid more. That's not what you, the mindset you want. That conversation comes after they develop conviction in what you're trying to do. So the first order of business is you need them to buy into what the vision and of what you're trying to build is. And you need to be, second thing is you need to be very honest with them.
Deedy: 00:21:25
At Glean I was always very honest about, Hey. You want to work, uh, you want to have a good work life balance at this job, you're just probably not going to get it. I don't know how to say it, you can make it work, I'm not, not everyone at Glean works like 80 hours a week or anything. There's people who work 40 50 hours a week, they're very intense for that 40 hours that they work. But, let's just say it's not going to be an easy job. And if you want an easy job, You know, frankly, I'll be up front,
Deedy: 00:21:52
like, you should go somewhere else. And that in itself is, it's funny because not only does it select for people who actually care about the other stuff that you're looking for, but even the people who might want work life balance are sort of, they feel threatened and they're like, no, I can do it. I feel like that's a challenge that I can take. And so they, they lean in even more. They actually appreciate that, that candor instead of you trying to dance around it and say, Hey, you're going to get work life balance and
Deedy: 00:22:19
you're going to build awesome stuff. And you're going to. You know, you're not going to get all of those. So those are some tactics that I found that are useful.
Hanh: 00:22:27
Yeah. And you know, I think, I think to start out with, I think it's wonderful if you can have that honest conversation with full conviction of your values and your goals so that they are aligned. It's easier to know a front when they're not aligned as opposed to finding out six months into it. Right. I feel that that's some fundamental. In hiring and keeping a team, and I want to add back to the TA example that you cited. That's exactly what I told my son.
Hanh: 00:22:58
He's computer engineering at Michigan, who graduated now, is working at Microsoft. When we had that COVID situation, everybody is going to class behind a screen. He was wondering, what can I do, right? I mean, we don't go anywhere, we don't do anything. So he applied to be a TA. And he loved it. You know, he never realized that the value and the fun. Well, it was during COVID, right? You have to do the best that you, you can behind a screen, but he loved it.
Hanh: 00:23:25
He learned so much. And then the point that you made about the networking and so forth. So he's over at Microsoft now and the people that he helped, Proctor classes, Want to do the same thing. So now the company that he's with open up for multiple qualified students. So it's true. It's so true. So great advice.
Deedy: 00:23:47
Exactly. I work like a charm.
Hanh: 00:23:49
Yeah. So, you know, in the world of technology and investing, pivots and adaptation is so important to stay ahead. So can you discuss a time when you had to shift your approach to a project or investment? Like, you mentioned unstructured, pinecone, or anthropic. And what insights you gain from that experience?
Deedy: 00:24:13
Let me talk about the Glean example first because I have more knowledge of that. In late 2022, we were at a pretty critical juncture at Glean where large language models were clearly powerful and extremely interesting and cool. And they went very far to solve the mission sort of that Glean was going after, which Um, to organize it's Google's mission, but for work. So to organize all your information at work and give it to you when you want it. At that time, because a lot of our leadership was ex Google search people,
Deedy: 00:24:51
when you present them with this alternate view of the world, Their first knee jerk reaction is, as expected, we've been working on search for 20 years, and if you give me a penny for every time I heard this new technology will disrupt search, I would have a lot of money. And so when they came to this idea of LLMs, the first reaction was, yeah, I don't know about it. It's like, it's cool. We're doing search. This is just not our business. And I think that was a moment where, It was interesting, it's an interesting
Deedy: 00:25:25
time was interesting for me and some other people at the company because not only do you have to dig deep within yourself and find your own conviction in order to fight this battle, because you're like, Oh, these guys are probably right, like they've been working at Google for they built search that they're, they're not dumb. And so you first have to dig deep for your own conviction. And then you have to strategically make sure you can convince. And it was a challenge. It took about a month, maybe more of
Deedy: 00:25:51
many people and many examples and demos and building stuff and demonstrating what it could do before it sort of was greenlit by the company as, Hey, we should do this next product. And looking back on it now, now the product is, you know, a significant part of, of Glean's revenue. And it was one of the best decisions that they could have made, but it wouldn't have happened if you're not constantly willing to fight the fight and willing to question things at the right moment. Menlo is similar. I've only, again, I've only
Deedy: 00:26:25
been a part of some of these and they say it all the time. Menlo's existed for 48 years. It's one of the oldest venture firms in the valley. It's running on its 16th fund right now. Most venture funds, I think the data says that most venture, 65 percent of venture funds never return capital. So if you've done it 16 times, you've clearly done something right. Um, when you do it for that long in venture, there's. And these are, this is advice coming from people who've done this for 20 plus years.
Deedy: 00:26:58
And I'm just telling you what they tell me is you can always have to reinvent yourself. If you're not reinventing yourself, you're not ahead of the curve. If you're not thinking deeply about, hey, what am I doing differently that the industry isn't, then you're just going to follow whatever everybody else is doing. You have no actual alpha on the industry. So we constantly think about our approach, whether it's the kind of checks we write, the volume of checks we write, the, the, the size of checks, the kind of companies we invest in,
Deedy: 00:27:25
um, what stage we want to invest in. All of that stuff you constantly have to think about and say, can we do better here? Can we do something more interesting here? And the Anthropic example is such a good example of that, which is such a non-traditional deal for. Um, Menlo to do, and it was, you know, an SPV structure into Anthropic that did a huge round that, that, that, you know, is keeping it running now. So I think that's a, an example of innovation is, is everywhere.
Hanh: 00:27:58
That's very exciting and, you know, balancing risks and practical consideration is an ongoing challenge. Now, how do you go, how do you approach balance when investing in or developing cutting edge technologies?
Deedy: 00:28:15
It's different for when you're operating and versus when you're investing. Um, when you're operating, I think risk mitigation is, you know, You know, it's, it's a little bit easier, I think, because it's resource constrained a half the time. Um, you, when you're operating a business or a startup, especially at small scale, you want to remain focused. You also want to try something new. The philosophy we always had was sort of 70, 20, 10, just 70 percent is the core work. 20 percent is some new work.
Deedy: 00:28:54
And 10 percent is completely experimental stuff. I think that framework broadly generally works and that already balances out the risks. It balances out the risks because you're only focusing on one thing at a time. And that is what you need to do. So that's, that's how it works when you're operating. You can't really, and then as you do that focus, the way you balance out different kinds of risk is more strategic and you'd have to get into the details. Like how do you.
Deedy: 00:29:19
Solve for market risk. How do you solve for tech risk? How do you solve for all these other types of risk in the business? And you need to, as a startup, just slowly eliminate all of this risk so you can make something successful as an investor. It's a little bit different. Um, managing risk involves number one, understanding the reward. Which means doing diligence and really understanding a space as best as you can. It's going to be imperfect talking to people, talking to experts, really diving deep into the
Deedy: 00:29:45
numbers and, um, the technology. And so you need to understand the risk, the reward to understand how the risk plays into it. But unfortunately, the hardest part of investing is you don't control. The risk is completely dependent on how much you pay. Like if you pay less than there's, there's no risk. So, but the price is completely dictated by the market. So if the market is frothy and people are overpaying for stuff. It's a tough place to be
Deedy: 00:30:13
because what are your options? You can sit out of every single deal because people are overpaying, but then you're not doing your job or you can participate and overpay, but that price is just not dictated by you. So all you can do is say, maybe I have an asymmetric or a different view of the reward. So I think the overpaid price is okay, but that's about it. Um, I, I think that's what makes it harder. You have much less control as an investor than you do as a startup, um,
Deedy: 00:30:44
founder, because as a startup founder, you can kind of move that, stir that ship in a lot of different ways. Um, as an investor. You're kind of at the behest of the market.
Hanh: 00:30:55
Great insight. So now, what do you see as the most significant opportunities and challenges facing AI over the next, let's say, 5, 10 years? And how do you incorporate these considerations into your investment decisions?
Deedy: 00:31:10
There's several. I'll talk, I'll start A lot of the generative AI products that we see today are quite impressive to demo, but they are not reliable. So we know this, they're non deterministic and non reliable, and that's a problem that if we can solve, I don't know how, but if we can solve it, it makes it way more effective. Number two is, I think, In this sort of hype cycle or a frothy cycle, there is a lot of people building with AI tools that are not focusing on product from first principles.
Deedy: 00:31:46
As a result, a lot of products that we see have really poor retention and they might be nice and hot right now, but Who knows whether people will continue to use those products in six months, unless you fundamentally think about first principles. How do I build a good product? And that does nothing to do with AI. That has basic product principles. That's number two. Number three, I think is we are at a point where so much of the next generation of power of what AI can do is bound by compute.
Deedy: 00:32:22
Um, when you're bound by compute, There's only only a couple of different options you have. Either you can make chips better and more efficient, more throughput, faster. Um, and that takes time, or you can figure out ways to make the, uh, underlying algorithms more efficient. Now, historically, if you look at it, typically it's been the latter. Sometimes there's, uh, innovations and algorithms, but almost always like the innovation is driven subtly through an increase in computation. I'll, I'll forgo as an
Deedy: 00:32:52
example, when they thought go. Yeah, the technique was really cool, but you couldn't have even done that 20 years ago. You just would not have the computational power to do. So that's, that's the third. I think about that a lot. And fourth is, um, less about the macro industry, more about like specific investing, which is a lot of people have great ideas, but they're, they don't think that, or they don't think that much about how their right to win in a market. And I always like to say.
Deedy: 00:33:27
I love ideas that are unsexy because if you're trying to work on something that's a really sexy idea, you have to also convince me that you, a small startup with three people are working on something that Google and Facebook and OpenAI and all these companies are not working on. So that's a challenging question and it's not like you're building a product, you're building a technology and these guys have talent, they have money, they have GPUs. What are you going to build that they can't build? What is your core insight? That they're not going to do already.
Deedy: 00:33:57
So those are a couple of things that I think about when I'm thinking about my investing thesis. And a lot of the companies I end up really liking are companies that look, they have a pretty strong play in AI as a startup, but their underlying technology is actually way more. And if by chance AI stops being important or stops being as hot, or it's captured by other players, I think the risk is generally mitigated because these guys can do so many other things. So a lot of focus on that sort of strategic thinking, but ultimately I think
Deedy: 00:34:31
the biggest advice is team as an investor. The most, most important thing at early stage is team. There are just some people who can, as they say, like run through walls, hire great people. And for them, it's almost. Unimportant what they're working on, they usually succeed no matter, no matter what.
Hanh: 00:34:49
Let me ask you about the team dynamic and hiring people, you know, with this AI ecosystem and agents. Okay. How many people, I guess the question is what impact you think that will have in the workforce? Let's say we used to think about five, 10 people, startups and so forth. How many people do you think we really need now? With the ability to create AI agents.
Deedy: 00:35:15
It's an interesting question. I think a lot of functions I generally think are getting automated and that doesn't mean people lose their jobs overnight. Uh, and sometimes it doesn't mean anyone loses their job. If the company can afford the people, then you're just getting more work out of the same people. But how does that change what we do? Let me just jump in. Be specific on certain things that I've seen, um, and TBD, how this all plays out, but for sales and outbounding,
Deedy: 00:35:45
there are tools that completely replace that of varying quality. Some of them do it really, really well, where they can just, they pick your ideal customer profile, the kind of target persona you want to reach out to, and then they will handle emailing them, responses, everything to when the meeting is on your calendar at whatever time you have. That is a huge time saver. There's a similar sort of tool for recruiting. You can do the same thing for recruiting candidates. Uh, get them, get them in the door.
Deedy: 00:36:17
No need to send emails anymore. There's a lot of work going on when it comes to doing engineering. So, tons of coding agents of various forms that can do interesting things. Like, there's some variants of coding agents which is like, just put this in your GitHub repository and we will automatically find issues and we'll go and fix them for you. And that's just work you wouldn't have even thought of. So that's like a different kind of, uh, extension. And then of course there's Copilot
Deedy: 00:36:44
tools where you're trying to develop and as you're developing it sort of helps you write code. Um, it helps you review code, helps you test code, various forms of that. Um, there are even voice outbounding tools or survey tools that help you. You know, do that better tons and tons of summarization tools, which help you take a lot of information and put it and make it really, really, um, digestible and easy to digest. Glean, obviously I'm biased, but I think that is a huge one because even at Glean, we would sort of get jaded when you work
Deedy: 00:37:18
at a company for a long time and you forget how, how cool the product you built is because you're always in it. And we'd have, we had a customer one time tell us. You just don't understand that most of my job as a senior person was being in these slack channels and answering the same questions. Day in and day out people ask me the same stuff. Big company, Hey, what do I do here? How do I fix this? How do I do that? And I would always be redirecting
Deedy: 00:37:43
them to a wiki and telling them, Hey, look at this answer. And I'd feel like a bad person for doing it. Because I wasn't just giving them the answer and then when Glean showed up and Glean Assistant showed up We would literally deploy these bots in a bunch of slack channels Say for HR or IT or even generic stuff and he's like my job is 80 percent lighter I just don't have to do that anymore. It goes it searches through the information and it tells them the answer Without me having to do
Deedy: 00:38:09
anything, there's completely autonomous. So I think there's a lot of power in what these things can bring. And I think it's incremental. So we're not going to see a change overnight. But yeah, I mean, it's already true that there are businesses of 10 people, 15 people who can make hundreds and millions of dollars and operate efficiently, which is not really possible like 25 years ago.
Hanh: 00:38:33
Yeah, that's true. So these AI agents augments your workflow. But it's like a GPS. It still needs a driver. And that's you.
Deedy: 00:38:44
Yes and no. I think there comes a time when it can, it can work autonomously. I don't think we're necessarily there yet for each task. I mean, take the outbounding tool too. Like, yeah, you have to drive it and say, Hey, these are the kind of people I'm interested in. Once you do that, then for the next month, two months, you don't really have to do anything. You just have to take the meeting. And so that's almost fully automated. So yeah, some driver, cause you
Deedy: 00:39:07
need to give it some direction, but yeah, a little sometimes.
Hanh: 00:39:12
That's great. You mentioned earlier about, I think it was topic one or point one that you were making about the products are not reliable or sustainable. What do you think that's due? Okay. Due to what?
Deedy: 00:39:26
Oh, well, that's just due to the inherent, um, way that large language models work. There's a lot of, uh, interesting research. Work on this, which is by design, it is trained on a large set of data and it is meant to be probabilistic in nature when it generates new text. And because of that probabilistic nature, it sort of imitates, um, I guess the core of the question is if it didn't have that probabilistic nature, it would also be less useful for many tasks. So, if you tuned it to hard determinism,
Deedy: 00:40:02
you would lose all the creativity, and it's very difficult to understand what kind of tasks are creativity focused tasks and what kind of tasks are. It's not a clean line. There's tasks where you answer a question and based on how it reads the information, there's a little bit of creativity, quote unquote, involved in understanding what the answer is. And determinism won't work there. But there are other tasks where you really want it to always work the same exact way every single time. And I think that's the sort of trade off
Deedy: 00:40:30
in large language models is hard for, just on a technical level, to get at.
Hanh: 00:40:37
Very true.
Deedy: 00:40:39
Induce it as well, but um, yeah, that's kind of where we're at.
Hanh: 00:40:43
Well, that's great. So, as AI continues to advance and become more integrated into our daily lives and businesses, an issue comes up is ethical consideration, which is so crucial. So what specific ethical challenges did you encounter at some point or anticipate facing in AI development and deployment? And how do you, let's say, contemplate in navigating these complexities as a tech leader?
Deedy: 00:41:13
They're tough. I mean, I'll give you a list of ethical considerations that are just really tough to wrestle with. One of them is. You're training on all this people's work. Maybe that's legal. Maybe that's not in some domains. It definitely is not in some domains it is, but you can't prove it. So that mean for how law works in this case, artists are very annoyed at this when it comes to music generation, uh, artists are annoyed when it comes to image generation, text, I think
Deedy: 00:41:40
less annoyed, but you know, for books and stuff, it's very clear that these large language models train on books. You can kind of trivially trivially figure that out. But. Again, you just can't pinpoint and say you definitely train on copyright material. So, that's an ethical consideration in that I don't know how to navigate, frankly. Here's another one. The second thing is, say this is a minutiae of things, but OpenAI released this amazing voice feature with 4.
Deedy: 00:42:13
Once that API releases, a lot of people are going to be using that voice feature to make phone calls to other people. And I think by law, if I'm not wrong, it is not. Legal to make a phone call with an AI without disclosing that you are actually an AI But we know that everyone's not gonna follow that it's not really gonna be cut down on and ethically That's just pretty wrong and you can't do it similar considerations on recording tools There's a whole suite of hardware stuff that just kind of always on recording Not all of them ask for consent of every single
Deedy: 00:42:47
user or every single person in the room. That's an ethical consideration.
Hanh: 00:42:52
You mean transcription? Transcription, yeah. That's true.
Deedy: 00:42:57
And the last one I think is the one, I think it's a borderline ethical, but it's also an ecosystem consideration. And let me put it this way, the reason I Sometimes care less about the ethical considerations because I feel helpless. I'm like, what am I going to do? This is just the way it is. I'm not in a position where I'm a regulator or I'm a law enforcer where I can make a difference here. Um, I'm investing in the space. Like that's just not something I can really focus on if it's something egregiously wrong.
Deedy: 00:43:24
I'm not, we're not going to invest in it, but I can't fix bad actors. So that's why I think about it less. The one I think about a lot. Is the ecosystem dynamic that the what happens to the ecosystem with these AI tools? And what I mean by that is the web ecosystem used because there was a feedback You would create a website people would go search they'd find your website. You'd get paid some ad ad revenue And you have incentive to create more websites, there's more people will create more websites and the ecosystem
Deedy: 00:43:53
is nice and flourishing and always has content and people can find content and Google can make money, everyone's happy. Now, with Gen AI, because it's trained on, you know, content up to a certain point in time and then just shown to you, the people who are making the content just don't get paid out. When the people don't get paid out, there's Dying incentive for anyone to contribute anything of value. We see this in journalism already, like, right? You know, in journalism, everyone just writes click baity articles because no
Deedy: 00:44:22
one will read the actual other stuff. So, what does that mean for all of the content in the next ten years? Like, who writes that? What did all of the information, all the news, all the stuff we want to know about the world, who's gonna write that? Why do they have any economic incentive to do that? That's a huge question. Um, and that's kind of a more existential question and people have answers that I think are just not, you know, Great. Like some people say, Oh, people will just, I don't know, tweet about it
Deedy: 00:44:49
or post about it, but no, they're not going to post about what's happening in, you know, a war in Mongolia, that's a journalist job. They have no incentive and no economic incentive to do that because no one's going to get paid them for their work. And if some AI is going to train on it and, and spit it out, that's a problem for the ecosystem. So. Those are the cuts. That's one I really, really worry about. Um, but yeah, there are, there are plenty of it.
Hanh: 00:45:14
Yeah. You know, great power comes great responsibilities, right? And, um, it's not always a clean cut, but I think, I guess just like anything, you know, you embrace it with caution.
Deedy: 00:45:27
Yup. I mean, what are the options you have?
Hanh: 00:45:30
Yeah. So even some of the most successful leaders face setbacks and failures, failures, and So, can you share an example of a significant challenge that you encounter and, and I guess how did you overcome that and what lessons did you take away from that experience?
Deedy: 00:45:49
Um, I would say one of the most significant challenges, uh, in, in my career was at the later stage of, of Google. I had a, um, a boss that was frankly just bad. Um, he was egotistical, power hungry, less concerned about solving the problems and, and driving, uh, the product. He was more concerned about control. So naturally this led to some tension and. I can't say I walked away from that with some amazing revelation of how I should deal with conflict. But what I can say is I, I realized
Deedy: 00:46:37
at that point, you know, I was going through some, some tougher times at that point, I was talking to a lot of friends and people, I realized the most liberating thing Is to not care. You have principles, you have values, you have what drives you. And I think what really drove it home for me was when I was talking to, you know, a mentor of mine and they said, what's the worst that can happen? He'll fire you. Are you going to be really that sad if you were fired for standing up for your values?
Deedy: 00:47:11
No, I'm like, no, I'm not going to be sad at all. In fact, I will be sad if I stay, stand up for my values. Cause then I'm like, what am I doing? I think what I'd say is, what I took away from that is, you should know when to fight the fight. You don't always, think, sometimes people disagree, you're, most of the time you're probably trying to make sure. Everything is nice and happy and people are under control, but when there's a time when your values are coming to question and the way you
Deedy: 00:47:39
operate come into question, yeah, you need to fight the fight because you will feel much worse if you don't. And then if you're not standing up for the things that you, so I think that's what I took away from from that.
Hanh: 00:47:52
Yeah. And you know, it's so true as you navigate in the later years. Whether it's professional or personal, we all develop that core of conduct. It's, it's that solid rock that over the years of experience that have formed and shape and where you are right now. And it's your core of conduct and that does not deviate, you know? So I, I agree with you. That's so important. So now I'm sure there have been many difficult decisions that perhaps That you made that are against popular opinion,
Hanh: 00:48:22
aside from your ex boss from Google. So can you share with us a situation where you face this challenge, whether it's Glean, Menlo, or any other physicians, and how would you navigate it, and what would you do to overcome that?
Deedy: 00:48:39
Multiple times. I mean, I think the hardest, hardest time is. I think some of it is personality dependent. Sometimes I'm generally a more of a debater persona. So I generally don't hesitate to express my opinion. If I disagree, I think there's an art to it. Like you don't, you don't disagree and then attack the person you disagree and try to arrive at a solution together. Can't say I'm perfect at that, but
Deedy: 00:49:00
I try to do that at most times. The hardest times I think are when you're, when you disagree with someone you respect immensely and you're like, this guy has every right to be right. Like he's done this longer than I have. He knows more than I do, but I just don't buy it. Like, I just don't understand what he's trying to say. And I think in those situations, what I, what I try to do is it's really, I guess, not that fascinating advice is you have to lead with respect. My view is.
Deedy: 00:49:32
If you know the person has way more power or you respect the person it's not even about power It's that person if you respect the person he has more control over this and more experience Then your first approach has to be look I may be wrong But i'm telling you this because this is what I feel at the end if you disagree with me Your, your opinion goes, and I always leave it, I'm like, look, your opinion goes at the end, I'm just telling you what I think and why, but your opinion goes, and here's why I think what I think, so let's talk about that, here's what
Deedy: 00:49:59
evidence I have, here's the data I have, here's as much, do the research, like do the work, nobody likes to be somebody. You know, a lot of these people are busy and they don't have the time for you, honestly, a lot of the time. So when you are going to disagree with, with, uh, with them on something, do the research, do the work, bring it up. And then, you know, it comes to a point where they actually respect you for that. And they're like, you know, I'm really glad. I get this all the time where a lot of people are like, You know what?
Deedy: 00:50:30
This is why we hired you, man. Like, you, you disagree, and I, I think you have a fair point. And so, that's, that's, I, I try to nurture that a lot. And there's a healthy balance. Again, you have to know when to disagree. You can't disagree every day. Then you just become a disagreeable person.
Hanh: 00:50:45
Yeah.
Deedy: 00:50:46
You know this is a battle I don't want to fight. I don't care about, this is the one I do care about. And then you say, the ones I care about, I'm going to express respect.
Hanh: 00:50:54
That's great. Communicate so that the two lines stay open, right? Because it's based on respect.
Deedy: 00:51:02
Yeah.
Hanh: 00:51:02
That's awesome.
Deedy: 00:51:03
And in addition, I'll say I also really believe strongly in bonding. Like the fundamental reason why people get into conflict is because they don't know each other. And so you need a little bit of that bonding. You need to know like, hey, where is this person coming from in life? To really understand and have empathy when you're dealing with them. And then you're like, okay, I get it. Look, we disagree, but I, I still, I still think you're awesome. Like, so.
Hanh: 00:51:27
You know, I agree with that, you know, and, and I think it's unfortunate sometimes, at least just me. I don't see it enough where people invest in the time to understand the story behind it, because everybody has a situation. Everybody has, whether it's a bad day, bad scenario, uh, whatever they come to That perhaps that you are in alignment. It could be in the actual scope, the topic, personality, or just the history and the luggage that they come with. And it takes, like you say, time to invest, to explore, to understand with empathy.
Hanh: 00:52:01
Maybe it's me. I don't see enough of it. Do you?
Deedy: 00:52:05
I don't. I don't. And I like this quote that one of my friends always tells me. It's like, Everyone has a struggle that you don't see. Exactly. And, and they're not going to tell you about it sometimes, but just like, just leading with knowing that everyone has that. Their stuff just makes a little bit nicer.
Hanh: 00:52:21
I agree. So now for those who are starting out in their tech industry, what advice would you offer based on your experiences as an engineer, manager, and venture capital principal?
Deedy: 00:52:33
I would say don't be too swayed by what's the hot thing right now. So learn it, know it, but. Know that, like, things come in waves and your incremental alpha is knowing what, knowing something that other people don't, not knowing something like hundred people do. Um, so focus on your curiosity first. Um, I would say learn how to love the craft and always stick to that guiding principle because work doesn't become work when you just love the craft. So those two things I advise. And then the third thing I would say is.
Deedy: 00:53:10
You know, those are easy things to say, but in reality, you know, everyone has to recruit and get a job and do all these things. Generally, I would say that don't be idealistic about how a career works. And I see a lot of this. I see a lot of people who say things like, Hey, You don't need to go to college to get a job and they're right you don't but I mean you also don't need to There's a lot of things you don't need to do to to get somewhere But they help and they help a lot and I think what's more important to me is I like to tell Especially like
Deedy: 00:53:46
my brother is in college right now Like I like to tell my brother and kids that that I advise I'm like, hey, man, like look It's great to be idealistic, it's great to be curious, it's great to lean into what you like, and you should always do that. But then always have your reality hat on, which is, this is just how it works. And don't let the, don't lie to yourself about how things work. Like, I'll give you an example, like, people lie to themselves all the time. Stanford, if you go to Stanford, you are going to get, have it easier to get a job and to start a company.
Deedy: 00:54:16
That's just how the world works. I think most people know that. But very, once in a while, they're like, Oh, actually, it doesn't matter. I can go to, you know, Cornell and I can do the same. You can do the same. Be honest. Stanford helps. And I think having that reality check and knowing this is just how things work. Right now, and this is how I like to operate, that in itself will go a really long way in, in your career.
Hanh: 00:54:42
Very true. Many years ago, when my kids were in college, they all graduated now. I always advise them, the branded school is always nice. Is it mandatory? Well, I think what matters more is that what you do with what you know, As opposed to a branded school and just bank on that, you know, and to me, knowledge, your, your thrive, your execution, your heart, your conviction, and a branded school is always nice. No, those are great advice. So thank you.
Hanh: 00:55:16
So now we're getting to the end, another question. So as a decision maker, our personal philosophies and values. So what core principles have you or have shaped your approach to your roles at startups and your principle at Menlo Ventures?
Deedy: 00:55:39
The values that really matter to me, I've thought about this a lot in my just general in my life is there's both personal and professional. I don't think they're different values. And there's two. Um, there's only two. Um, the other ones are like common. Everyone has those, but the two that matter most to me are humility, which I think no matter what, where you are, what you do, what you achieve. You need to be humble like you haven't done it all because every next battle is a separate battle
Deedy: 00:56:07
And you don't have any right to win that one unless you're humble. The second one is curiosity Um, I just think that you know for me that's like why I do Whatever I do. I don't seek any title or I don't really care about the title Money and status and I don't have like very rich, like expensive hobbies. What I really care is like, I'm a curious person. I like to read and learn about things and, um, as, as much as I can make an impact in the, in the way that I, that I can. So I think humility and curiosity will
Deedy: 00:56:40
always be sort of my core driving values and everything else comes from that. So yeah, you have like the honesty and you have like be, be disciplined and be hardworking and put in the effort. All of these things come from that, but I think those are, that's maintained that sort of throughout.
Hanh: 00:56:59
That's wonderful. So we're at the end now and I appreciate your time so much. Would you like to add anything else before we wrap up?
Deedy: 00:57:09
No, I, I think the only thing I, I I'd like to say is. When it comes to, uh, like the, the, the advice question got me thinking is when it comes to approaching a new thing, an industry or whatever, trust your gut, you know, trust your gut, what you, what do you think that's different from other people and follow that. And I can give you so many examples. Of people who have just trusted their gut long enough And those are the ones who are the most tremendously successful. Everyone else told them don't do that. That's a stupid decision Why
Deedy: 00:57:46
are you starting this company? Why are you spending all your time in this dumb project that doesn't work? Just trust your gut like that's fine And I don't believe in this. Oh all your friends if your friends are haters, then they're not your friends No, sometimes your friends will be like that. Sometimes i'm like that people are like that. Um, and that's okay, right? And that's okay It's your job to be like I hear you but not I'm going to do it anyway. And that's, I think how most people
Deedy: 00:58:11
should, people should have the confidence to just trust their gut on things.
Hanh: 00:58:17
Well, I want to thank Deedy for joining us today and sharing his incredible insights and experiences from the world of AI and infrastructure from his early days as an engineer to current, his current role as principal at Menlo Ventures. His journey is a testament to a power of curiosity, adaptability, and strategic thinking. In his stories he shared today and lessons on building high performing teams, navigating difficult situations, and staying ahead of industry, industry trends are so invaluable for anyone looking
Hanh: 00:58:50
to make their mark in the tech world. And as we discussed, it's clear throughout our conversation that his passion for innovation, combined with his deep technical expertise and leadership skills. It's made him a driving force in shaping the future of enterprise technology. So we're excited. Can't wait to see what groundbreaking startups and technologies that will help bring to life next. And to the audience, thank you so much for tuning in. And don't forget to follow AI50 LinkedIn page.
Hanh: 00:59:26
Subscribe to our podcast and YouTube channel for more engaging discussions. About tech venture leaders, aging products for the 50 plus demographic. Thank you for your attention.
Deedy: 00:59:40
Thanks, Hanh.
Hanh: 00:59:41
Thank you. Yeah.
Hanh: 00:00:05
Cloud computing can help long term care facilities with remote monitoring, predictive analytics, and secure data management. Technology can also improve patient outcomes, operations, and costs with collaboration and productivity tools.
Narrator: 00:00:27
Get ready to embark on a thrilling AI adventure with AI50Connect, your ultimate guide to harnessing the power of artificial intelligence for business success. At AI50, we're on a mission to transform data into game changing innovations. In today's exciting episode, Enhancing Long Term Care Through Technology, your host and AI trailblazer, Hanh Brown, explores the transformative potential of technology in revolutionizing elderly care. Hanh breaks down the complexities of IOT, AI, blockchain, and mixed reality,
Narrator: 00:01:02
revealing how these cutting edge tools can help long term care professionals overcome challenges and deliver exceptional care. With AI50's state of the art LLM apps, Businesses across diverse industries can unlock the full potential of AI. Tailoring solutions to their unique needs and preferences. We dive deep into the ways technology can reshape health care, commerce and daily life for people of all generations, including seniors. Buckle up for a journey filled with captivating stories, groundbreaking innovations, and enlightening
Narrator: 00:01:35
conversations with industry pioneers. We'll navigate the ethical and societal implications of AI advancements, showcasing how they can drive positive change and propel business growth. Whether you're an entrepreneur seeking to leverage AI for your venture, a business owner looking to serve more clients, or simply fascinated by AI's transformative power, join Hanh on this mind expanding expedition. Get set for engaging storytelling, expert insights, and real world applications that showcase AI's vast potential. Let's embark on this
Narrator: 00:02:11
thrilling ride together.
Hanh: 00:02:19
Hello, and welcome to our podcast on how technology can enhance long term care. I'm your host, Hanh Brown, and today we'll be exploring the challenges and opportunities in this critical industry. With the aging population and increasing demand for quality care, It's more important than ever to find innovative solutions that can improve patient outcomes and support caregivers. The long term care industry faces numerous challenges, including an aging population, increasing costs, and a shortage of skilled caregivers. In fact, according to the U.
Hanh: 00:02:59
S. Census Bureau, the number of Americans age 65 and older is projected to nearly double, from 52 million. In 2018 to 95 million by 2060, this demographic shift puts immense pressure on long term care facilities to provide high quality care while managing limited resources. Technology has the potential to revolutionize long term care by improving patient outcomes, reducing costs, and supporting caregivers. For example, a study by the University of Missouri found that the use of
Hanh: 00:03:37
telehealth technology in long term care facilities reduced hospitalizations by 20 percent and emergency room visits by 25%. These findings demonstrate the tangible benefits that technology can bring to long term care. In this episode, we'll be discussing how various technologies, such as the Internet of Things, IoT, artificial intelligence, AI, blockchain, and mixed reality can revolutionize long term care. We'll look at real world examples of how these technologies are being used in healthcare settings and explore the potential benefits of these technologies.
Hanh: 00:04:17
They can bring to patients, caregivers, and long term care facilities. As we dive into this topic, our focus is on educating and informing you about the possibilities that technology offers in the long term care space. By understanding these opportunities, you can make informed decisions about how to incorporate technology into your care practices and improve the lives of those you serve. Throughout the episode, we'll break down complex concepts into simple, relatable terms and provide examples to help you better understand
Hanh: 00:04:53
the ideas we're discussing. We'll also offer guidance on how to assess your needs, identify appropriate technologies, And develop a road map for implementation. So whether you're a long term care provider, a caregiver, or someone with a personal interest in this topic, I invite you to join me on this exciting journey. Let's explore how technology can transform long term care and make a positive impact on the lives of countless individuals. Let's talk about cloud computing and how it can revolutionize long term care. Cloud platforms offer a powerful set of
Hanh: 00:05:34
tools and services with key components like IoT, or the Internet of Things. Imagine using IoT devices to monitor patients health and safety in real time. Caregivers can receive automated alerts, and long term care facilities can even enable predictive maintenance for medical equipment. By implementing IoT solutions, long term care facilities can improve patient outcomes, reduce costs, and enhance operational efficiency. Isn't that amazing? To get started, care providers can implement IoT devices, configure
Hanh: 00:06:16
cloud based IoT solutions, and develop custom applications. For instance, a care facility could deploy sensors to monitor patients vital signs, like heart rate and blood pressure. If any abnormalities are detected, the system can send automated alerts to caregivers. This real time monitoring helps prevent adverse events and ensures timely interventions. Another essential aspect of cloud computing is AI, or artificial intelligence. AI can be used to create predictive
Hanh: 00:06:51
analytics models for personalized care plans, cognitive services for enhanced patient engagement, and machine learning algorithms for early detection of health issues. By leveraging AI, long term care providers can offer more personalized care, improve patient satisfaction, and proactively manage healthcare needs. To implement AI solutions, long term care facilities can start by identifying specific use cases, preparing relevant data, and training and deploying AI models. For example, an AI powered chatbot
Hanh: 00:07:26
could be developed to engage with patients, answer their questions, and provide personalized recommendations based on their health profile. This improves patient engagement and reduces the workload on caregivers. Let's talk about blockchain technology. It offers a secure and transparent way to manage patient records. Streamline supply chain management for medical supplies and automate billing and claims processing using smart contracts. By utilizing blockchain technology, long term care providers can enhance data security, reduce fraud, and
Hanh: 00:08:11
improve operational efficiency. To leverage blockchain, long term care facilities can define specific use cases, select an appropriate blockchain platform, and develop and deploy smart contracts. For example, a blockchain based system could be used to securely store and share patient records across different care settings. This enables seamless care coordination and reduces the risk of data breaches. Now let's dive a bit deeper into how IoT, AI, and blockchain work within a cloud computing platform. IoT devices, like sensors and
Hanh: 00:08:54
wearables, collect real time data about patients health and activities. This data is then sent to a cloud based IoT hub, which securely processes and analyzes the information. By using machine learning algorithms, the IoT solution can detect patterns and anomalies in patient data, enabling early intervention and preventive care. Imagine a long term care facility that uses IoT sensors to monitor residents mobility and fall risk. If a resident's gait or balance starts to deteriorate, the system can alert caregivers to provide additional
Hanh: 00:09:33
support and prevent potential falls. This proactive approach not only improves patient safety, but also reduces the burden on caregivers. AI takes this a step further by enabling predictive analytics in personalized care plans. By analyzing vast amounts of patient data, AI models can identify risk factors and predict potential health issues before they occur. This allows long term care facilities to allocate resources more effectively and provide targeted interventions for each patient.
Hanh: 00:10:10
While implementing these technologies may seem daunting, the benefits they offer are significant. By embracing IOT, AI, and blockchain, long term care providers can transform the way they deliver care, improve patient outcomes, and streamline their operations. However, it's essential to approach the adoption of these technologies strategically, starting with clear use cases, preparing the necessary infrastructure and data, and providing adequate training to staff members. In the next section, we'll explore how cloud based productivity tools can
Hanh: 00:10:48
further support long term care by enabling secure communication and collaboration, streamlining workflows, and providing valuable insights through data analytics. Stay tuned as we continue our journey into the world of technology and long term care. All right, let's dive into how cloud based productivity tools can take long term care to the next level. These tools are like superheroes, enabling secure communication, streamlining workflows, and providing valuable insights. First up, we have cloud based
Hanh: 00:11:30
collaboration platforms that are like virtual meeting rooms for caregivers. With these platforms, they can securely message each other about patient care, share documents and images, and even conduct virtual meetings to discuss treatment plans. It's like having a care coordination headquarters at your fingertips. But what about patients and families? No problem. They can join virtual meetings for consultations, getting updates on their loved one's care, and asking questions from the comfort of their own homes.
Hanh: 00:12:07
It's like bringing the care facility to them without the travel costs and hassle. Let's talk about low code application development platforms, which are like custom built toolkits for long term care facilities. With these platforms, you can create applications tailored to your specific needs. Like medication tracking or patient intake forms. It's like having a digital assistant that streamlines your processes and reduces errors. Workflow automation tools are like
Hanh: 00:12:45
magic wands for repetitive tasks. They can send notifications when a patient's medication is due or trigger supply reorders when inventory runs low. It's like having a tireless assistant working 24 7 to keep everything running smoothly. And let's not forget about data analytics and visualization tools, which are like crystal balls for gaining valuable insights. By connecting these tools to your electronic health record, EHR systems, and IoT devices, you can gain valuable insights into patient
Hanh: 00:13:24
health trends, resource utilization, and operational efficiency. It's like having a data driven, decision making superpower. But how do you implement these tools? Start by identifying specific use cases, designing custom applications and workflows, and training your staff. It's like giving your team a toolkit and a roadmap to success. Now, let's talk about comprehensive healthcare technology platforms, which are like all in one control centers for long term care facilities. These platforms have modules for
Hanh: 00:14:05
patient and resident management, Resource and facility management, and financial management, and billing. It's like having a central hub that keeps everything organized and running smoothly. With these platforms, you can maintain comprehensive patient profiles, track care plans and assessments, and manage medications and allergies. It's like having a digital care assistant that ensures patients receive the appropriate care and support. And when it comes to resource and facility management, these platforms are like master schedulers.
Hanh: 00:14:45
They can help you manage staff shifts, track equipment maintenance, and manage room assignments. It's like having a digital facilities manager that optimizes your resources and improves operational efficiency. Finally, the financial management and billing module in these platforms is like a digital accountant. Thanks. It can track patient billing and payments, manage insurance claims and reimbursements, and generate financial reports. It's like having a financial wizard
Hanh: 00:15:21
that reduces errors, improves cash flow, and ensures compliance. To implement a comprehensive healthcare technology platform, start by assessing your current systems and processes, identifying areas for improvement, and developing a plan. It's like creating a roadmap to a more efficient and effective long term care facility. But the real magic of cloud based tools is their ability to integrate with other healthcare systems, like EHRs and medical devices. This integration allows for
Hanh: 00:15:55
seamless data exchange and collaboration among caregivers. Improving the continuity and quality of care. It's like having a digital bridge that connects all the pieces of the care puzzle. Imagine a patient being discharged from the hospital and admitted to your long term care facility. With cloud based collaboration tools and low code application development platforms, caregivers can easily access the patient's medical history, medication list, and treatment plan
Hanh: 00:16:27
from the hospital's EHR system. For It's like having a digital care package that ensures smooth transitions and consistent care. And the best part, cloud based tools can be customized to fit the specific needs and workflows of your long term care facility. It's like having a tailored suit that fits your organization perfectly. By leveraging the various cloud based tools available, you can transform the way you operate, improving patient care, streamlining workflows, and driving better outcomes.
Hanh: 00:17:05
But remember, it's important to approach implementation strategically. With a clear understanding of your facility's needs and goals, and a plan for training and support. To help long term care facilities translate these insights into action, here's a high level roadmap for technology implementation. One, assess your current technology infrastructure and identify gaps or opportunities for improvement. Engage stakeholders, staff, patients, families to gather input and build buy in. Three.
Hanh: 00:17:47
Develop a clear vision and strategy for technology adoption aligned with your facility's goals and priorities. Identify and prioritize specific use cases and technologies to implement. Select technology partners and solutions that meet your needs and budget. Plan and execute a phased implementation, starting with pilot projects and gradually scaling up. Provide ongoing training, support, and communication to ensure successful adoption and optimization. Monitor and measure the impact of the technology on key performance
Hanh: 00:18:27
indicators and patient outcomes. Continuously iterate and improve based on feedback and results. It's like having a roadmap and a guide to ensure a successful journey. So, there you have it. Cloud based tools are like a superhero suite for long term care facilities, enabling secure communication, streamlining workflows, And providing valuable insights in the next section, we'll explore how cutting edge technologies like mixed reality can take things even further, enabling immersive training experiences and providing
Hanh: 00:19:05
assisted reality for patient care. Get ready to soar to new heights in long term care. Let's talk about how cutting edge technologies like Mixed Reality can revolutionize patient care and improve outcomes in long term care facilities. These comprehensive solutions are like secret weapons, offering tools for personalized patient engagement, care team collaboration, and advanced data analytics. Let's dive into personalized patient engagement. With these technologies, you can create
Hanh: 00:19:47
tailored care plans, remotely monitor patients, and even conduct virtual visits. It's like having a digital concierge for each patient, ensuring they receive the attention and support they need. To get started, care providers can implement personalized patient engagement solutions and configure the tools. This involves setting up patient portals where patients and their families can access health information and communicate with care teams. It's like giving them a backstage pass to their own care journey. Let's talk about care team collaboration.
Hanh: 00:20:32
These technologies make it easy for caregivers to securely message each other. Integrate with EHR systems for seamless data sharing, and even conduct virtual meetings. It's like having a digital roundtable where everyone can come together to make the best decisions for each patient. To enable this collaboration, care providers can set up the collaboration tools within their chosen platform. This means configuring secure messaging channels, Integrating with existing EHR systems and training staff on how to use these tools effectively.
Hanh: 00:21:10
It's like giving your team a superpower for communication and coordination. But wait, there's more. Advanced data analytics capabilities are also available. By integrating data from various sources, like IoT devices and EHR systems, and providing advanced analytics tools for population health management and predictive modeling, facilities can gain valuable insights. It's like having a crystal ball that helps you identify trends, predict patient needs, and make data driven decisions. To get started with data analytics,
Hanh: 00:21:46
long term care facilities can implement data interoperability solutions and configure the analytics tools. But don't forget the importance of training staff members on how to use these tools for data driven decision making. It's like giving them a superpower for continuous improvement. These cutting edge technologies also offer other valuable features, like remote patient monitoring and medication management. It's like having a digital guardian angel watching over your patients, ensuring they receive the right care at the right time.
Hanh: 00:22:24
And when it comes to security and compliance, these solutions have got you covered. With robust security features like identity and access management, data encryption, and threat detection, you can safeguard patient information and maintain trust in your patients. It's like having a digital fortress protecting your facility from cyber threats and regulatory pitfalls. To ensure the safety and confidentiality of patient information, long term care facilities must implement robust data privacy and security measures
Hanh: 00:22:59
when adopting these technologies. This includes using secure cloud platforms that comply with health care regulations such as HIPAA and GDPR, implementing strong access controls and authentication mechanisms, encrypting sensitive data both in transit and at rest, and regularly monitoring for and responding to potential security breaches or anomalies. Facilities should also provide thorough training to staff on data privacy best practices and develop clear policies and procedures for handling and sharing patient information. By prioritizing data privacy and security,
Hanh: 00:23:34
long term care facilities can build trust with patients and families, mitigate the risk of costly data breaches, and ensure compliance with regulatory requirements. Implementing these technologies does require careful planning and execution, though. It's important to assess your current needs and goals, develop a clear roadmap, and ensure that staff members are adequately trained and supported throughout the implementation process. But trust me, the benefits are worth it. Consider, for instance, the success story of Sunny Hills Long Term Care Facility.
Hanh: 00:24:13
By implementing a cloud based EHR system and IoT enabled remote monitoring, they were able to reduce hospital readmissions by 30 percent and improve patient satisfaction scores by 25%. Or take the case of Greenfield Manor, which used AI powered predictive analytics. To identify high risk patients and intervene early, resulting in a 20 percent reduction in adverse events and a 15 percent decrease in overall health care costs. These real world examples demonstrate the tangible impact that these technologies
Hanh: 00:24:52
can have on patient outcomes, operational efficiency, and financial performance. Now, let's talk about the power of interoperability and data exchange. These technologies enable long term care facilities to connect and share data with other health care providers, like hospitals, clinics, and pharmacies. It's like having a digital bridge that ensures continuity of care and prevents gaps in treatment. Imagine if a long term care resident is hospitalized. With these technologies, the facility can securely share the
Hanh: 00:25:33
resident's medical records and care plan with the hospital staff. It's like giving them a digital care package to ensure appropriate care and avoid duplicating tests or treatments. Interoperability also allows for better care coordination and collaboration among different healthcare providers. With these technologies, long term care facilities can participate in virtual care teams. In case conferences, bringing together experts from various disciplines to develop comprehensive care plans for patients.
Hanh: 00:26:08
It's like having a digital dream team for each patient. Studies have shown that improved care coordination and interoperability can lead to better patient outcomes, reduce hospital readmissions, and lower healthcare costs. It's like having a triple win for patients, facilities, and the healthcare system as a whole. Of course, adopting these technologies isn't without its challenges. Change can be hard, especially for staff members who are comfortable with existing processes and technologies.
Hanh: 00:26:41
But by prioritizing change management and employee engagement and involving front line staff in the planning and implementation process, facilities can overcome resistance and build buy in. Ensuring interoperability with existing systems and data sources can also be a challenge, requiring significant technical expertise and resources. It's crucial to involve front line staff, patients, and families in the technology selection and implementation process. By engaging these stakeholders early on, long term care facilities can ensure that the chosen solutions align with
Hanh: 00:27:16
their needs, preferences, and workflows. This could involve conducting surveys, focus groups, or pilot tests to gather feedback and insights, and incorporating this input into the design and configuration of the technology. By fostering a sense of ownership and buy in among staff, patients, and families, facilities can drive greater adoption and satisfaction with the new tools. Ongoing training, support, and communication are also essential to help these stakeholders adapt to and make the most of the technology over time. But by working closely with technology
Hanh: 00:27:57
partners or healthcare IT consultants. Facilities can navigate these issues and develop custom integrations that work for their unique needs. And let's not forget about budget constraints, especially for smaller facilities with limited resources. But by prioritizing investments based on specific needs and goals and exploring financing options or grants, facilities can find ways to make these technologies a reality. So there you have it, folks. Cutting edge technologies like mixed reality and advanced analytics platforms
Hanh: 00:28:38
are like secret weapons for long term care facilities, offering personalized patient engagement, care team collaboration, advanced data analytics, and so much more. By leveraging these tools and prioritizing interoperability and data exchange, facilities can provide higher quality care to the residents. and drive better outcomes, but the journey doesn't stop there. In the next section, we'll explore how mixed reality devices can take long term care to the next level by enabling immersive training experiences and providing
Hanh: 00:29:16
assisted reality for patient care. Mixed reality devices are cutting edge technologies that can revolutionize long term care. They offer immersive experiences for training and education, as well as assisted reality for patient care. Let's dive into how these devices can enhance caregiver skills and improve patient outcomes. One of the most promising applications of mixed reality in long term care is enhanced training and education for caregivers. With mixed reality, caregivers can
Hanh: 00:29:56
experience immersive and interactive learning simulations that closely mimic real world scenarios. This can help improve their skills, confidence, and decision making abilities. For example, mixed reality can be used to create realistic simulations of patient care situations, such as responding to a fall or managing a medical emergency. Caregivers can practice these scenarios in a safe, controlled environment, receiving real time feedback and guidance. This can help them develop muscle memory and improve their response times in real world situations.
Hanh: 00:30:33
Mixed reality can also facilitate remote collaboration and knowledge sharing among caregivers. For instance, experienced caregivers can use mixed reality to provide real time guidance and support to novice caregivers, even if they are in different locations. This can help ensure that best practices are consistently followed and that caregivers have access to expert knowledge when needed. To get started with mixed reality training and education, long term care facilities can partner with developers to create custom training
Hanh: 00:31:08
modules that meet their specific needs. They can also procure mixed reality devices and provide training to staff members on how to use them effectively. By investing in mixed reality training, care facilities can improve caregiver competency, reduce training costs, and enhance patient safety. Another exciting application of mixed reality in long term care is assisted reality for patient care. With Mixed Reality, caregivers can access real time patient data, medical information, and guided procedures, all while keeping
Hanh: 00:31:46
their hands free to provide care. This can help improve accuracy, reduce errors, and enhance patient outcomes. For example, Mixed Reality can be used to provide real time, step by step guidance for complex medical procedures. such as wound care or catheter insertion. Caregivers can see visual overlays and instructions, ensuring that they follow best practices and minimize the risk of complications. Mixed reality can also display patient vital signs, medication information, and other critical data, allowing caregivers to make informed decisions quickly.
Hanh: 00:32:26
In addition, mixed reality can enable remote expert consultation and support for patient care. For instance, if a caregiver encounters a complex or unusual situation, they can use mixed reality to connect with a remote specialist and receive real time guidance and advice. This can help improve patient outcomes, especially in rural or underserved areas where access to specialists may be limited. To implement mixed reality for patient care, long term care facilities should start by identifying specific
Hanh: 00:32:58
use cases and developing custom applications that meet their needs. They can then deploy mixed reality devices to caregivers. and provide training on how to use them effectively. It's important to ensure that mixed reality applications are user friendly, reliable, and secure, and that they integrate seamlessly with existing systems and workflows. While mixed reality offers significant potential benefits for long term care, It's important to recognize that implementing this technology
Hanh: 00:33:32
requires a significant investment of time, resources, and expertise. Long term care facilities should carefully consider their budget, infrastructure, and staffing needs before embarking on a mixed reality implementation. It's also important to ensure that mixed reality applications are designed with the needs of caregivers and patients in mind. This may involve conducting user research, gathering feedback, and iterating on designs to ensure that they are intuitive, accessible, and effective. Care facilities should also consider the potential impact of mixed reality
Hanh: 00:34:10
on patient privacy and consent, and develop clear policies and procedures to ensure that patient rights are protected. While the benefits of mixed reality in long term care are significant. There are also some challenges and considerations to keep in mind. One of the main barriers to adoption is the cost of the technology. Mixed reality devices can be expensive in long-term care facilities may need to invest in multiple units to fully realize the benefits. Another consideration is the technical requirements for
Hanh: 00:34:46
implementing mixed reality. The devices require a reliable and fast internet connection, as well as compatible software and applications. Long term care facilities may need to upgrade their IT infrastructure and train staff members to use the technology effectively. User adoption is also a critical factor in the success of mixed reality implementation. Some caregivers and patients may be hesitant to use the technology, either due to a lack of familiarity or concerns about privacy and security.
Hanh: 00:35:23
It's essential to provide adequate training and support to help users feel comfortable and confident with the devices. Despite these challenges, the potential benefits of mixed reality for long term care are significant. By enabling immersive training experiences and providing assisted reality for patient care, mixed reality can help improve caregiver skills, reduce errors, and enhance patient outcomes. As the technology continues to evolve and become more accessible, we can expect to see more long term care
Hanh: 00:35:56
facilities adopting mixed reality and other cutting edge solutions. Throughout this podcast, we've explored how various technologies can enhance long term care. Cloud computing can help long term care facilities with remote monitoring, predictive analytics, and secure data management. Technology can also improve patient outcomes, operations, and costs with collaboration and productivity tools. We've covered a lot of ground in this episode, and I hope you're as excited as I am about the possibilities that these
Hanh: 00:36:37
technologies offer for long term care. We've talked about how cutting edge solutions can enable personalized patient engagement, care team collaboration, and advanced data analytics. It's like having a digital tool kit that can transform the way you deliver care and support your patients. But we didn't stop there. We also looked at how mixed reality devices can enable immersive training and assisted reality for patient care. Imagine training your staff in real scenarios without moving from the facility or giving guidance and support
Hanh: 00:37:15
to caregivers as they help patients. It's like having a digital assistant that can enhance the skills and knowledge of your team. Of course, implementing these technologies isn't something you can do overnight. It's important to carefully evaluate your needs and goals and develop a strategic plan that takes into account your unique challenges and opportunities. But by taking a thoughtful approach and leveraging the power of these tools, you can drive transformative change in your long term care facility. Now, I want to take a moment to
Hanh: 00:37:49
emphasize something really important. Technology is amazing, but it's not a magic wand that can solve all the challenges of long term care. At the end of the day, the heart of this field is the human touch and the compassion that caregivers bring to their work. Technology should be seen as a tool to enhance and support that vital work, not replace it. So, If you're thinking about exploring these technologies for your long term care facility, where should you start? Well, the first step is to take
Hanh: 00:38:25
a good, hard look at your current technology infrastructure. Are there areas where you could leverage these tools to improve patient care and operational efficiency? Maybe you could start with a small pilot project, like using IoT sensors to prevent falls or implementing a chat bot to engage with patients. It's all about figuring out what works best for your facility and your patients. Another key step is to reach out to technology partners or healthcare technology consultants who can provide guidance and support
Hanh: 00:39:05
as you navigate this journey. They can help you develop a roadmap for adoption, train your staff, and integrate these technologies with your existing systems. Because let's face it, implementing new technologies can be a daunting task. But with the right support and expertise, you can make it happen. Finally, I can't stress enough how important it is to stay informed and engage with the latest developments and best practices in healthcare technology, attend industry conferences, join online communities, and
Hanh: 00:39:39
subscribe to relevant publications. The more you know, the better equipped you'll be to make informed decisions and stay ahead of the curve. So, there you have it folks. Technology offers a world of possibilities for long term care facilities, but it's up to you to take the first step by approaching this journey with a clear understanding of your needs, a strategic plan for implementation, and a commitment to putting your patients and staff first. You can harness the power of these tools to drive meaningful change and improve outcomes.
Hanh: 00:40:18
Now, I want to leave you with a strong call to action. If you're a long term care professional who wants to leverage the power of technology to enhance patient care and operational efficiency, here are three concrete steps you can take today. One, schedule a meeting with your leadership team to discuss the potential benefits Of implementing cutting edge technologies in your facility. Use the insights and examples from this podcast. To make a compelling case for investment and prioritization to
Hanh: 00:40:55
reach out to technology partners or healthcare technology consultants to request a demo or consultation. They can provide you with more specific guidance on how these technologies can address your unique challenges and opportunities and help you develop a tailored implementation plan. Three, start a pilot project to test the feasibility and impact of a specific technology in your facility. This could be as simple as using a low code platform to digitize a manual process, or as ambitious as implementing mixed reality for caregiver training.
Hanh: 00:41:34
The key is to start small, gather feedback and data, and build momentum for larger scale adoption. Thank you By taking these steps, you'll be well on your way to harnessing the power of technology and driving meaningful change in your long term care facility. Remember, the journey of a thousand miles begins with a single step. So don't wait. Take action today. And as always, if you have any questions, comments, or success stories to share, please don't hesitate to reach out. We'd love to hear from you and feature
Hanh: 00:42:06
your experiences in a future episode. So once again, thank you for tuning in and remember, when it comes to leveraging technology to enhance long term care, the sky's the limit. Together, we can build a brighter, more innovative future for our patients, our staff, and our industry as a whole. As we wrap up this episode, I want to thank you for tuning in and engaging with this important topic. If you found this information valuable, please share it with your colleagues and peers. And if you have any questions
Hanh: 00:42:41
or ideas for future episodes, Don't hesitate to reach out. We're all in this together and by sharing our knowledge and experiences, we can make a real difference in the lives of those we serve. Imagine in the story of Margaret, an 85 year old resident with dementia who had been prone to wandering and falls. By equipping her with a wearable IOT device that tracked her location and alerted staff when she was at risk, the facility was able to ensure her safety and provide timely assistance. The technology not only prevented
Hanh: 00:43:17
potential accidents, but also gave Margaret's family peace of mind, knowing that she was being monitored and cared for around the clock. Or consider the experience of John, a long term care nurse who had been struggling with the overwhelming demands of his job. By adopting a mobile app that streamlined medication management and documentation, John was able to save time, reduce errors, and focus more on patient care. The technology not only made his work more efficient, but also boosted his job satisfaction and sense of purpose. Knowing that he was providing the
Hanh: 00:43:54
best possible care to his residents. So until next time, keep exploring, keep innovating, and keep putting your patients first, because at the end of the day, that's what it's all about. Thanks for listening and have a great day.
Narrator: 00:44:14
Wow. What a mind blowing journey into the world of AI and long term care. Hanh hopes this episode of AI50 Connect has sparked your imagination and inspired you to explore how AI can revolutionize your business and help you deliver exceptional care to your clients. Remember, AI is not just a trendy catchphrase. It's a transformative tool that empowers you to make data driven decisions, uncover hidden opportunities, and streamline your business processes. With AI50 as your trusted
Narrator: 00:44:44
partner, you can harness the full potential of AI to elevate your business to unprecedented heights. Visit our website, AI50, AI to explore our cutting edge AI solutions designed for businesses of all sizes. While you're there, be sure to subscribe to our newsletter and stay up to date with the latest AI trends, insights, and success stories. Don't forget to hit that subscribe button on AI50 connect on your favorite podcast platform and leave us a glowing review. Your feedback is crucial in helping us create content that
Narrator: 00:45:20
tackles your most pressing AI questions and concerns head on. Connect with us on LinkedIn, Tik TOK, Twitter, and YouTube for a treasure trove of AI related content designed to keep you at the forefront of the AI revolution. And when you're ready to embark on your own AI journey, reach out to us at AI50.ai, our team of experts, is here to guide you every step of the way. Thank you for joining Hanh on this mind expanding AI adventure. Remember, with AI50, you're not just keeping up with change, you're leading the charge.
Narrator: 00:45:53
Until next time, keep innovating, growing, and transforming lives through the power of AI.
Hanh: 00:00:06
Investing in education and workforce development programs that prepare people for the jobs of the future while also supporting those who may be displaced by automation. It means creating policies and regulations that protect individual privacy, prevent algorithmic bias, and hold technology companies accountable for the impact of their products. And it means fostering a culture of interdisciplinary collaboration and public engagement. Where diverse voices and perspectives are heard and valued.
Narrator: 00:00:44
Welcome to AI50 Connect, your gateway to the fascinating world of artificial intelligence and its transformative journey from the 1950s to the present day. At AI50, we're passionate about exploring AI's incredible potential to reshape industries and tackle societal challenges. In today's captivating episode, innovating responsibly in the age of AI, your host and AI luminary, Hanh Brown, takes you on a journey through AI's remarkable evolution. From its early beginnings to its current status as a mainstream phenomenon, Hanh
Narrator: 00:01:18
breaks down the complex history of AI, highlighting the peaks of innovation and the challenges of AI winters. With AI50's cutting edge insights, businesses, entrepreneurs, and individuals can navigate the exciting possibilities and ethical complexities that AI presents. We go beyond the technical jargon to explore AI's potential to revolutionize healthcare, finance, and healthcare. Transportation and creative fields. Each episode is a thought provoking expedition filled with real world examples, expert insights and conversations with trailblazers.
Narrator: 00:01:53
We dive into the ethical considerations, societal impacts, and the need for responsible AI development to ensure that these advancements benefit humanity equitably. Whether you're an AI enthusiast, business leader, or simply curious about the future, join Hanh on this enlightening exploration. Get ready for engaging storytelling, in depth analysis, and a glimpse into a future where AI is not just a tool, but a transformative force shaping our world. Let's embark on this exciting journey together.
Hanh: 00:02:32
Hello and welcome to Innovating Responsibly in the Age of AI. I'm your host, Hanh Brown, and I'm thrilled to have you join me on this exciting journey as we explore the fascinating world of artificial intelligence. AI has come a long way since its inception in the 1950s. What began as a niche field of study has now become a ubiquitous presence in our daily lives. From the early days of the Dartmouth conference and the Turing test to the development of machine learning
Hanh: 00:03:03
algorithms and breakthroughs in natural language processing, AI has experienced a remarkable evolution. But the path of AI hasn't always been smooth. There have been periods of great enthusiasm and progress, as well as times of disappointment and stagnation, often referred to as AI winters. But Despite these ups and downs, AI has persevered and continues to push the boundaries of what's possible. In recent years, we've witnessed AI's transition from an experimental technology to a mainstream phenomenon.
Hanh: 00:03:40
Gone are the days when AI was confined to the realm of science fiction and research labs. Today, AI is everywhere, from the virtual assistants in our phones to the recommendation systems that shape our online experiences. The integration of AI into various industries has been nothing short of remarkable in health care. AI is assisting doctors in diagnosing diseases and predicting treatment outcomes in finance. AI is detecting fraud and optimizing investment strategies
Hanh: 00:04:14
and in transportation. AI is paving the way for autonomous vehicles that could revolutionize the way we travel. But as AI becomes more prevalent, it's crucial that we pause and reflect on its implications. How do we ensure that AI is developed and deployed responsibly? What ethical considerations must we address as AI grows more sophisticated? And how can we harness the power of AI to create a better future for all? These are just a few of the questions we'll be exploring in this episode.
Hanh: 00:04:47
We will dive deep into a specific aspect of AI, from its technical advancements to its societal impact. But this episode isn't just about passively absorbing information. I want to engage with you, the listener, and hear your thoughts and perspectives. Throughout each episode, I'll be posing questions and inviting you to join the conversation via my newsletter, Spotify, or LinkedIn, whether you're an AI enthusiast, a skeptic, or somewhere in between. Your voice matters in shaping the future of this transformative technology.
Hanh: 00:05:26
So let's get on this journey together. Throughout the conversation, we'll explore how AI is surpassing human abilities in complex tasks. Like image recognition and strategic decision making. We'll delve into the creative side of AI, from generating art to composing music. We'll examine the exponential growth in computational power that's fueling AI's progress and consider the ethical and safety implications of this rapid advancement. But we won't stop there. We'll also look at how AI is being
Hanh: 00:05:59
integrated into our daily lives, from personalized education to emotional support, We'll discuss the potential for AI to transform entire industries and address global challenges like climate change and healthcare access. And we'll grapple with the difficult questions surrounding job displacement, privacy, and the responsible governance of AI. Throughout it all, we'll be guided by a sense of curiosity, humility, and a commitment to creating a future in which AI benefits all of humanity. Because as much as AI is a technological
Hanh: 00:06:34
marvel, it's also a profound opportunity to reflect on what it means to be human and what kind of world we want to build. So whether you're a tech enthusiast, a business leader, a policymaker, Or simply someone who wants to better understand the world around you. This episode is for you. Join me on this exciting journey as we explore the frontiers of AI and chart a course towards a brighter, more innovative future. But before we dive in, I want to know what comes to mind when you hear the term artificial intelligence?
Hanh: 00:07:15
What are your hopes and fears about this technology and what questions do you hope to have answered through this podcast? Take a moment to reflect and let's start this conversation together. Let's dive deeper into the rapid advancements in AI capabilities and what they mean for our future. One of the most striking developments in recent years has been AI's ability to surpass human performance in a wide range of complex tasks. Take image recognition, for example. AI powered systems can now analyze images and videos with a level
Hanh: 00:07:59
of accuracy that rivals or even exceeds that of human experts. This has profound implications for fields like healthcare, where AI is being used to assist doctors in diagnosing diseases and analyzing medical imaging. But AI's capabilities don't stop there. In the realm of Natural Language Processing, or NLP, AI has made remarkable strides in understanding, interpreting, and generating human language. From machine translation to sentiment analysis, AI is revolutionizing the way we interact with text based data. And with the development of advanced
Hanh: 00:08:36
language models like GPT 4, AI is even able to produce human like text that can be difficult to distinguish from content written by humans. Of course, we can't talk about AI's capabilities without mentioning its prowess in strategic decision making. In recent years, AI has achieved landmark victories against human champions in complex games like Go and Chess. But these aren't just parlor tricks. The ability of AI systems, like AlphaGo and AlphaZero, to analyze vast amounts of data, recognize patterns, and make split second decisions has
Hanh: 00:09:18
far reaching implications for fields like finance, logistics, and beyond. Perhaps most exciting, however, is AI's potential in the realm of creativity. Once thought to be the exclusive domain of human intelligence, AI is now being used to generate original works of art, compose music, and even write literary works. From GANs that produce stunning visual art, to AI powered systems that can write coherent short stories. The boundaries between human and machine creativity are becoming increasingly blurred, but as we marvel at these advancements, it's important to pause
Hanh: 00:09:59
and consider their implications. What does it mean for AI to surpass human abilities in certain domains? How do we ensure that these powerful technologies are developed and deployed responsibly? And what role should humans play as AI becomes increasingly autonomous? These are not easy questions to answer, but they are crucial ones. As we continue to push the boundaries of what's possible with AI, we must also grapple with the ethical and societal implications of these advancements. We must ensure that AI is developed in
Hanh: 00:10:34
a way that is transparent, accountable, and aligned with human values. And we must work to create a future in which the benefits of AI are shared broadly, rather than concentrated in the hands of a few. One thing is clear, the rapid advancements in AI capabilities are just the beginning. As we continue to make progress in areas like computational power and algorithmic design, the possibilities for AI will only continue to grow. But with great power comes great responsibility. As we unlock new frontiers in AI.
Hanh: 00:11:15
We must also commit to doing so in a way that is responsible, ethical, and grounded in a deep respect for human life and flourishing. So as we explore these exciting developments, I want to challenge you to think critically about their implications. How do you envision AI augmenting, or even replacing, human capabilities in various domains? What benefits do you see? And what risks concern you? And how can we work together to ensure that the development of AI remains a force for good in the world?
Hanh: 00:11:50
Next, we'll be diving into the exponential growth in computational power that is fueling these advancements and what it means for the future of AI. We'll explore the concept of Moore's Law. The role of cloud computing and distributed systems and the hardware and software innovations that are enabling AI to scale like never before. So stay tuned and join me as we continue on this journey to understand and shape the future of artificial intelligence. Let's dive into one of the key factors driving these advancements. The exponential growth
Hanh: 00:12:35
in computational power. To truly grasp the scale of modern AI models, it's important to understand the vast amounts of data they're trained on. We're talking about data sets that contain trillions of words, images, and other data points. To put this into perspective, if a human were to attempt to read and process the same amount of information, It would take them several lifetimes, but for AI, processing these massive data sets is just the beginning. So, how is this level of data processing even possible?
Hanh: 00:13:14
The answer lies in the remarkable progress we've made in computing power over the past few decades. You may have heard of Moore's Law, the observation that the number of transistors on a microchip tends to double every two years. Leading to exponential growth in computational power. While the exact rate of this growth has slowed in recent years, the overall trend continues, and it's had a profound impact on the development of AI. But it's not just raw computing power that's driving AI forward.
Hanh: 00:13:47
Advancements in hardware and software architectures have also played a crucial role. The development of specialized chips, like GPUs and TPUs, has enabled faster and more efficient processing of the complex mathematical operations required for AI. In innovations in software frameworks and libraries, such Such as TensorFlow and PyTorch have made it easier for researchers and developers to build and train AI models. Another key factor in the growth of AI has been the rise of cloud computing and distributed systems.
Hanh: 00:14:26
By harnessing the power of vast networks of computers, researchers can now train AI models on a scale that was once unimaginable. This has democratized access to AI. for joining me. Making it possible for organizations of all sizes to leverage these powerful technologies. But as we marvel at the exponential growth in computational power, it's important to consider the implications of this progress. On one hand, the increasing affordability and accessibility of
Hanh: 00:14:57
AI is opening up new possibilities for innovation and problem solving. From healthcare and education to climate change and beyond, AI has the potential to help us tackle some of the world's most pressing challenges. On the other hand, the concentration of AI power in the hands of a few large tech companies raises important questions about fairness, transparency, and accountability. As AI becomes more integral to our lives, It's crucial that we ensure its development and deployment are guided by strong ethical principles
Hanh: 00:15:32
and a commitment to the public good. There are also environmental considerations to keep in mind. The training of large AI models requires significant amounts of energy contributing to carbon emissions and climate change. As we continue to push the boundaries of what's possible with AI, we must also work to develop more efficient and sustainable computing practices. So what does the future hold for the computational power driving AI? Some experts predict that we're on the cusp of a new era of quantum computing, which could unlock even greater
Hanh: 00:16:08
possibilities for AI and other fields. Others point to the development of neuromorphic computing. which seeks to replicate the structure and function of the human brain in computer chips. Regardless of the specific path forward, one thing is clear. The exponential growth in computational power is transforming the landscape of AI, and with it, the world as we know it. As we navigate this rapidly evolving terrain, it's up to us to ensure that the development of AI remains grounded in human values In a
Hanh: 00:16:44
commitment to the greater good. So I want to hear from you. How do you think the growth in computational power will shape the future of AI? What opportunities and challenges do you see on the horizon? And how can we work together to ensure that the benefits of AI are shared broadly while mitigating its risks and negative impacts? Next section, we'll be exploring the integration of AI into our daily lives. From personalized education and health advice to autonomous
Hanh: 00:17:20
vehicles and smart infrastructure. We'll consider the ways in which AI is already transforming industries and lifestyles and the even greater changes that may lie ahead. So join me as we continue our journey to understand and shape the future of artificial intelligence. Let's explore how these advancements are translating into tangible applications in our daily lives. AI is no longer just a theoretical concept or a tool confined to research labs. It's becoming increasingly integrated into the products and services we
Hanh: 00:18:04
use every day, often in ways that are so seamless we hardly even notice. Let's start with one of the most prominent examples, AI as our personal and professional assistance. Imagine having a tutor that can adapt to your unique learning style, pace, and goals. That's the promise of AI powered educational platforms, which use machine learning algorithms to create personalized learning experiences. From language learning apps like Duolingo to math tutoring systems like Thinkster Math, AI is transforming the
Hanh: 00:18:38
way we acquire knowledge and skills. But AI's potential as a personal assistant extends far beyond education. In the realm of health and wellness, AI powered tools can provide tailored advice and coaching, helping individuals make informed decisions about their diet, exercise, and lifestyle habits. And for those seeking emotional support, AI chatbots and virtual therapists are emerging as a complement to traditional mental health services. Offering a safe and confidential space to process emotions and develop coping strategies.
Hanh: 00:19:18
Of course, we can't talk about AI assistants without mentioning the likes of Sayuri, Alexa, and Google Assistant. These virtual helpers have become ubiquitous in recent years, offering a wide range of services from setting reminders and managing schedules to controlling smart home devices and even providing comic relief. As natural language processing continues to improve, the line between human and AI conversation is becoming increasingly blurred. But the integration of AI into our daily lives goes far beyond personal assistance.
Hanh: 00:19:55
In the realm of transportation, autonomous vehicles are poised to revolutionize the way we get from point A to point B. While fully self driving cars are still a work in progress, AI is already being used to optimize traffic flow, reduce accidents, and make our roads safer and more efficient. Similarly, in the energy sector, AI is enabling the development of smart grids that can balance supply and demand in real time, reducing waste and improving the reliability of our power systems. And in manufacturing and supply chain management, AI is streamlining,
Hanh: 00:20:33
skirmishing production processes, improving quality control, and optimizing inventory management. Even in the realm of scientific discovery, AI is playing an increasingly important role. From analyzing vast amounts of data in fields like genomics and astronomy to predicting the structures of proteins and designing new materials, AI is accelerating the pace of research and innovation in ways that were once unimaginable. But as we marvel at the many ways in which AI is transforming our daily
Hanh: 00:21:05
lives, it's important to consider the implications of this integration. How do we ensure that AI powered systems Are designed and deployed in a way that is fair, transparent, and accountable? How do we protect individual privacy and prevent the misuse of personal data? And how do we ensure that the benefits of AI are shared broadly, rather than exacerbating existing inequalities? These are complex questions that will require ongoing dialogue and collaboration among technologists and researchers. Policymakers, ethicists, and the broader public.
Hanh: 00:21:45
But one thing is clear. The integration of AI into our daily lives is not a matter of if, but when. As we navigate this new landscape, it's up to us to shape the future of AI in a way that aligns with our values and aspirations as a society. So, I want to know, how has AI already impacted your daily life? Perhaps in ways you hadn't even realized. What excites you most about the potential of AI to transform various industries and domains? And what concerns do you have about the increasing
Hanh: 00:22:22
integration of AI into our lives? In our next section, we'll be taking a deeper dive into the ethical and safety considerations surrounding AI from data privacy and algorithmic bias to transparency and accountability. We'll explore the concept of AI as a new digital species and consider the importance of proceeding with caution and respect as we unlock its vast potential. Stay tuned and join me as we continue this critical conversation about the future of AI and its impact on our world. Let's tackle one of the most crucial aspects of AI development, the
Hanh: 00:23:11
ethical and safety considerations. That must guide our progress is AI systems become more sophisticated and autonomous. It's essential that we navigate the associated risks and challenges with the utmost care and responsibility. One of the primary concerns is privacy and data protection. AI models are often trained on vast amounts of personal data, from our online behavior and preferences, to our health records and financial information, ensuring that this data is collected, stored, and used in a secure and ethical manner.
Hanh: 00:23:48
It's paramount to maintaining public trust in ai, but privacy is just the tip of the iceberg when it comes to AI ethics. Another key issue is algorithmic bias and fairness in decision making. AI systems are only as unbiased as the data they're trained on and the humans who designed them. If that data reflects historical inequalities or if the designers harbor unconscious biases. The resulting AI models can perpetuate and even amplify discrimination. We've already seen examples of this in areas like facial recognition, hiring,
Hanh: 00:24:29
and criminal sentencing, where AI has been found to exhibit racial and gender biases. So, how do we address these biases? One important step is to ensure that the data used to train AI models is diverse, representative, and free from historical bias. But it's not enough to simply feed the model unbiased data. We must also strive for transparency and explain ability in AI decision making. This means developing algorithms that can clearly articulate how they arrived at a particular conclusion or recommendation, rather than operating as a black box.
Hanh: 00:25:09
By making AI more transparent and interpretable, we can better identify and mitigate potential biases and errors. Another critical ethical consideration is accountability and liability. As AI systems become more autonomous, the question of who is responsible when something goes wrong becomes increasingly complex. Is it the designer of the AI system, the company that deploys it, or the AI itself? Developing clear legal and regulatory frameworks around AI liability will be essential to ensuring that the technology is used responsibly and that any negative
Hanh: 00:25:48
impacts are addressed swiftly and fairly. But perhaps the most profound ethical question surrounding AI is one that goes beyond specific applications and use cases. It's the question of what the rise of AI means for the future of humanity itself. As we develop systems that can match or even surpass human intelligence in certain domains, we must grapple with the implications of creating a new form of digital species. This is where the use of metaphors can be particularly illuminating. By comparing AI to other powerful
Hanh: 00:26:23
and potentially dangerous entities. Like nuclear energy or bioengineered viruses. We can begin to wrap our minds around the scale and complexity of the challenge before us, just as we have developed strict protocols and safeguards around these other world changing technologies. So too, must we approach AI with a mix of caution, respect, and proactive governance. Ultimately, the path forward will require ongoing collaboration and dialogue among all stakeholders. Researchers, policymakers, industry
Hanh: 00:26:56
leaders, and the general public. We must work together to develop robust ethical frameworks, safety protocols, and accountability measures that keep pace with the rapid advancements in AI. And we must do so with a deep sense of responsibility and humility, recognizing that the decisions we make today will have profound impacts on the trajectory of human civilization. But I don't want to paint an overly grim picture. The truth is, the rise of AI also holds immense potential for positive transformation, from democratizing
Hanh: 00:27:32
access to education and healthcare to combating climate change and advancing scientific discovery. AI could be a powerful tool for solving some of the world's most pressing challenges. The key is to approach its development and deployment with a clear eyed understanding of the risks and a firm commitment to using it for the greater good. So, as we navigate this brave new world of AI, I want to challenge you to think deeply about your own role in shaping its future. What ethical principles and values
Hanh: 00:28:07
should guide the development of AI? How can we foster a culture of responsibility and accountability in the tech industry and beyond? And what concrete actions can each of us take as consumers, citizens, and human beings? To ensure that the age of AI is one of prosperity, equality, and flourishing for all in our next section, we'll be exploring some of the positive transformative potential of AI from revolutionizing education and health care to addressing global challenges like climate
Hanh: 00:28:45
change and sustainable development. We'll consider how AI could be harnessed to empower individuals, strengthen communities, and build a better world for future generations. So stay tuned. The best is yet to come. Let's shift gears and explore the incredible potential for AI to drive positive societal transformation. One of the most exciting possibilities on the horizon is the democratization of education and healthcare through AI. Imagine a world where every person, regardless of their socioeconomic
Hanh: 00:29:23
status or geographic location, has access to high quality, personalized learning experiences. With AI powered educational platforms, this vision is becoming a reality. By leveraging machine learning algorithms, these platforms can adapt to each learner's unique needs, preferences, and pace. They can provide targeted feedback, recommend resources based on individual strengths and weaknesses, and even predict when a student is at risk of falling behind. And because they're often delivered online
Hanh: 00:29:53
or via mobile devices, They have the potential to reach learners in even the most remote or underserved communities. But the transformative power of AI extends far beyond the classroom. In healthcare, AI is poised to revolutionize the way we diagnose, treat, and prevent disease. From analyzing medical images to identifying patterns in patient data, AI can help doctors make faster, more accurate decisions and tailor treatments to individual needs. And with the rise of telemedicine and remote monitoring, AI is
Hanh: 00:30:33
making it possible for patients to receive high quality care from the comfort of their own homes. Imagine a future where AI powered chatbots can triage patients. answer basic health questions, and even detect early warning signs of serious conditions. By catching diseases early and expanding access to preventive care, AI could help us live longer, healthier lives. But perhaps the most profound impact of AI will be felt on a global scale as we grapple with existential challenges like climate
Hanh: 00:31:07
change and sustainable development. AI is already being used to optimize renewable energy systems, predict and respond to natural disasters, and monitor deforestation and wildlife populations. By analyzing vast amounts of environmental data and identifying patterns and trends, AI can help us make more informed decisions about how to protect our planet and its resources. In the realm of agriculture and food production, AI is enabling precision farming techniques that reduce water and pesticide use, improve crop yields, and minimize waste.
Hanh: 00:31:46
And in the fight against hunger and malnutrition, AI powered supply chain management systems are helping to ensure that food gets to the people who need it most while minimizing spoilage and loss. Of course, realizing the full potential of AI for societal transformation It will require more than just technological innovation. It will require a fundamental shift in the way we think about the role of technology in our lives and in our world. We must ensure that the benefits of AI are distributed equitably and that its development and deployment are
Hanh: 00:32:21
guided by a strong ethical framework. This means investing in education and workforce development programs. That prepare people for the jobs of the future, while also supporting those who may be displaced by automation. It means creating policies and regulations that protect individual privacy, prevent algorithmic bias, and hold technology companies accountable for the impact of their products. And it means fostering a culture of interdisciplinary collaboration and public engagement. Where diverse voices and
Hanh: 00:32:57
perspectives are heard and valued. So, as we contemplate the vast potential of AI to transform our world, I want to challenge you to think big. What societal challenges keep you up at night? And how might AI be harnessed to address them? What role can you play in shaping the future of AI, whether as a researcher, entrepreneur, policymaker, or engaged citizen? The path forward won't be easy, and there will undoubtedly be bumps and setbacks along the way.
Hanh: 00:33:32
But if we approach the age of AI with a sense of purpose, empathy, and collective responsibility, I believe we can create a future that is more just, sustainable, and fulfilling for all. In our next section, we'll be zooming out even further to consider the long term future of AI and its potential impact on the trajectory of human civilization. We'll explore mind bending concepts like artificial general intelligence and superintelligence And consider the importance of proactive, collaborative governance to ensure that the future of AI aligns with the future we want for
Hanh: 00:34:12
ourselves, and for generations to come. So buckle up. The ride is about to get even more interesting. Let's cast our gaze even further into the future and consider what lies ahead for AI and for humanity as a whole. As we've seen, the pace of AI development is accelerating at a breathtaking rate. Every day, it seems we hear about new breakthroughs and milestones from AI systems that can compose music and create art to those that can diagnose disease and predict natural disasters. But as impressive as these
Hanh: 00:34:53
achievements are, they may pale in comparison to what's on the horizon. One of the most tantalizing and controversial prospects is the development of artificial general intelligence, or AGI. Unlike narrow AI systems that are designed to excel at specific tasks, AGI would possess the kind of broad, flexible intelligence that we associate with human cognition. It would be able to learn, reason, and adapt in ways that are not pre programmed or constrained by its initial training data.
Hanh: 00:35:30
The implications of AGI are both exhilarating and sobering. On one hand, it could supercharge our ability to solve complex problems and make new discoveries, from curing diseases to colonizing other planets. But it could also pose existential risks to humanity if not developed and deployed with the utmost care and foresight. This is where the concept of superintelligence comes into play. Some experts worry. That if we create an AI system that surpasses human intelligence, it could rapidly recursive self improve, becoming
Hanh: 00:36:06
so powerful and inscrutable that we lose control over its actions and intentions. This is the stuff of science fiction nightmares. Think Skynet from the Terminator movies or the AI overlords in the matrix. But before we get too carried away with dystopian scenarios, it's important to emphasize that AGI and superintelligence are still largely hypothetical at this point. We don't know if or when they will be achieved, and there is much debate and uncertainty around the technical feasibility and
Hanh: 00:36:48
timeline of these developments. That said, it would be foolish to dismiss the possibility entirely or to assume that we have plenty of time to figure it out. The truth is, the rate of progress in AI is often underestimated, and we may be closer to these milestones than we realize. That's why it's so crucial that we start grappling with the implications now in developing frameworks and strategies for responsible AI development and governance. This is where international cooperation and collaboration will be essential. No single country, company, or research
Hanh: 00:37:25
institution can go it alone when it comes to shaping the future of AI. We need global standards and best practices, shared principles and values, and mechanisms for transparency and accountability. We also need to be proactive in addressing the potential negative impacts of AI. From job displacement and economic inequality to the erosion of privacy and civil liberties. This means investing in education and retraining programs, developing social safety nets and support systems, and creating legal and regulatory frameworks
Hanh: 00:38:04
that keep pace with technological change. Ultimately, the future of AI will be shaped by the choices we make today as individuals, as societies, And as a global community, we have an opportunity and a responsibility to steer this powerful technology towards outcomes that benefit humanity as a whole, rather than just a privileged few. So as we look ahead to the future of AI, I want to leave you with a challenge and a call to action. Educate yourself about the latest developments and debates in the field, engage in discussions and
Hanh: 00:38:40
dialogues with people from different backgrounds and perspectives. And most importantly, don't be a passive bystander in the AI revolution. Use your voice, your skills, and your influence to shape the future you want to see. The age of AI is upon us, and the stakes could not be higher. But if we approach this moment with wisdom, empathy, and a fierce commitment to the greater good, I believe we can create a future that is not just technologically advanced, but also deeply humane.
Hanh: 00:39:17
A future where AI is a tool for empowerment, discovery, and shared prosperity. Rather than a source of fear or oppression. So let us go forth with courage and conviction, knowing that the future is not yet written. It is ours to imagine and to build, and together we can make it a future worth fighting for. As we come to the end of our journey, exploring the past, present, and future of AI, I want to take a moment to reflect on just how far we've
Hanh: 00:39:55
come and how far we have yet to go. From the early days of AI research in the 1950s to the transformative breakthroughs of today, we've witnessed a remarkable evolution in the capabilities and applications of this technology. AI is no longer just a subject of academic interest or science fiction speculation. It is a powerful force that is reshaping our world in profound and far reaching ways. We've seen how AI is being integrated into every aspect of our lives, From the personal assistance in our phones to the algorithms that shape our online
Hanh: 00:40:34
experiences and the systems that power our industries and infrastructure, we've explored the incredible potential of a I to solve complex problems. Drive innovation and discovery and create new opportunities for growth and prosperity. But we've also grappled with the significant challenges and risks that come with this transformative power. From issues of bias and fairness to questions of privacy, security, and control. The rise of AI raises deep and complex ethical questions that we as
Hanh: 00:41:11
a society must confront and address. Navigating this new landscape will require more than just technical expertise and innovation. It will require a deep commitment to responsible development and deployment grounded in a clear eyed understanding of the potential impacts and implications of AI. It will require ongoing collaboration and dialogue among diverse stakeholders, from researchers and entrepreneurs to policymakers and the general public. And perhaps most importantly, it will require a fundamental shift.
Hanh: 00:41:47
In the way we think about the relationship between technology and society, we must move beyond the false dichotomy of man versus machine, and instead embrace a vision of man with machine, a future in which AI is developed and used in service of human values and aspirations, rather than in opposition to them. This is no easy task, and there will undoubtedly be challenges and setbacks along the way. But I believe that if we approach the age of AI with wisdom, empathy, and a fierce commitment to the greater good, we can create a future
Hanh: 00:42:25
that is not just technologically advanced, but also deeply humane. So let us go forth with courage and conviction, knowing that the future is not predetermined. It is ours. To shape and to build. Let us harness the incredible power of AI to solve the great challenges of our time from climate change and disease to poverty and inequality. Let us use this technology to empower individuals, strengthen communities and create a world that is more just, sustainable and flourishing for all.
Hanh: 00:43:00
The road ahead may be uncertain, but one thing is clear. The age of AI is just beginning and its impact will be felt for generations to come. So let us seize this moment. And work together to ensure that the future we create is one we can all be proud of. Thank you for joining me on this journey and for being a part of this vital and ongoing conversation. May we continue to learn from each other, challenge each other and inspire each other as we navigate
Hanh: 00:43:30
this brave new world together. The best is yet to come.
Narrator: 00:43:42
Wow. What an incredible journey through the history and potential of artificial intelligence. Hanh hopes this episode of AI50 Connect has sparked your imagination and inspired you to think about how we can harness AI's potential responsibly and ethically for a better future. Remember, AI is not just about technological marvels. It's about ensuring these advancements benefit humanity equitably. With AI50 as your guide, you can stay informed and engaged
Narrator: 00:44:12
in shaping the future of AI. Head over to our website, AI50.ai to discover more about our insights and resources at the forefront of responsible AI innovation. While you're there, don't forget to sign up for our newsletter and stay up to date on the latest AI trends, breakthroughs, and success stories. Make sure to subscribe to AI50 Connect on your preferred podcast platform and leave us a review. Your feedback is invaluable in helping us create content that explores the most pressing questions and exciting
Narrator: 00:44:43
possibilities surrounding AI. Connect with us on LinkedIn, TikTok, Twitter, and YouTube for a wealth of content designed to keep you engaged and informed about AI's transformative potential. And if you're ready to be a part of this exciting journey, reach out to us at AI50.ai. Our team is here to support you every step of the way. Thanks for joining Hanh on this eye opening adventure into the world of AI. Remember, with AI50, you're not just adapting to change, you're driving it.
Narrator: 00:45:15
Until next time, keep learning, innovating, and embracing the incredible possibilities that AI has in store for us all, while ensuring we develop and deploy it responsibly.
Hanh: 00:00:05
Imagine a future where education is truly personalized to your individual needs and learning style. That's the promise of AI in the educational sector. AI powered intelligent tutoring systems can assess your knowledge, pace, and learning preferences, then tailor content delivery to optimize your learning experience. This adaptive learning approach has the potential to significantly improve outcomes and make high quality education more accessible to learners from all backgrounds.
Narrator: 00:00:43
Welcome to AI50Connect, your portal into the revolutionary world of artificial intelligence and its transformative impact on education, work, and society. At AI50, we're passionate about exploring how AI is reshaping our world in profound ways. In today's captivating episode, AI Revolution, Reshaping Education, Work, and Society, your host and AI visionary, Hanh Brown, takes you on a journey through the far reaching effects of AI across various sectors. Hanh breaks down complex AI concepts and
Narrator: 00:01:15
reveals how this technology is not just advancing, but fundamentally altering the way we learn, work, and interact. With AI50's cutting edge insights, educators, business owners, and individuals can navigate the exciting possibilities and challenges that AI presents. We go beyond the tech jargon to explore how AI is leveling the educational playing field, Augmenting job roles and creating new opportunities. Each episode is a thought provoking expedition filled with real world examples, expert insights, and
Narrator: 00:01:51
conversations with trailblazers. We dive into the ethical considerations, societal impacts, and the need for responsible AI development to ensure that this technology benefits humanity as a whole. Whether you're an AI enthusiast, business leader, or simply curious about the future. Join Hanh on this eye opening exploration, get ready for engaging storytelling, in depth analysis, and a glimpse into a future where AI is not just a tool, but a transformative force shaping our lives. Let's embark on this
Narrator: 00:02:28
exciting journey together.
Hanh: 00:02:36
Welcome to AI50. I am Hanh Brown, your host. In today's episode, AI Revolution. Reshaping education work in society will dive into the transformative impact of AI across various sectors will discuss how AI is revolutionizing education, enhancing workforce efficiency and reshaping job roles. We'll also explore the societal and regulatory implications of this powerful technology. Throughout the episode, I'll be asking thought provoking questions to engage you in the conversation.
Hanh: 00:03:12
Sit back, relax, and let's dive into the exciting realm of AI. Let's reflect on the significance of AI. It's not just a buzzword or a passing trend. It's a revolutionary force with the potential to transform the way we live, work, and learn. From personalized education to enhanced decision making, AI is already making its mark. However, with great power comes great responsibility. As we embrace AI, we must navigate the ethical and societal implications,
Hanh: 00:03:47
ensuring that it is developed and deployed in a way that benefits humanity. This requires ongoing dialogue, collaboration, and a commitment to responsible innovation. Imagine a future where education is truly personalized to your individual needs and learning style. That's the promise of AI in the educational sector. AI powered intelligent tutoring systems can assess your knowledge, pace, and learning preferences, then tailor content delivery to optimize your learning experience.
Hanh: 00:04:26
This adaptive learning approach has the potential to significantly improve outcomes and make high quality education more accessible to learners from all backgrounds. Picture a world where every student has access to a virtual personal tutor that understands their strengths, weaknesses, and unique learning requirements. It can provide targeted support, feedback, and guidance to help them excel. This level of personalization could be a game changer in education. As a business owner, the implications of AI enhanced education are significant.
Hanh: 00:05:04
It means that future employees may possess a more diverse and adaptable skill set, better equipped to learn new skills and adapt to technological changes in the workplace. Consider partnering with educational institutions and platforms that leverage AI to help align curricula with industry needs. You could even develop your own AI power training programs to upskill current employees. Imagine a corporate training program that adapts to each employee's learning needs and preferences, delivering
Hanh: 00:05:36
targeted content, assessing progress, and providing personalized feedback. This approach could significantly enhance the effectiveness of employee training and development. AI can also help identify and address learning gaps at an early stage. By analyzing student data and performance, AI systems can flag potential issues and provide targeted interventions to prevent students from falling behind. This proactive approach could help reduce dropout rates and ensure that every student has the support they need to succeed.
Hanh: 00:06:14
AI can enable more engaging and interactive learning experiences. Like educational games and simulations that adapt to your skill level and learning style. These AI powered tools could make learning more fun, immersive, and effective. Providing real time feedback and rewards to keep students motivated and engaged. AI can also revolutionize access to education in underserved communities. With AI powered online learning platforms, Students from anywhere in the world can access high quality educational content, learn at their own
Hanh: 00:06:53
pace, and receive personalized support. This could help bridge the education gap and provide equal opportunities for all learners, regardless of their background or location. Of course, the integration of AI in education is not without challenges. There are concerns around data privacy, algorithmic bias, and the potential for AI to replace human teachers. Microsoft However, with proper governance and ethical considerations, these challenges can be addressed. The goal should be to use AI as a tool to enhance and support human teachers.
Hanh: 00:07:29
Not replace them by leveraging the strengths of both AI and human educators. We can create a more effective and inclusive learning environment. So I ask you, how do you envision AI transforming education? What exciting possibilities do you see for personalized learning? Now let's explore how AI can augment and enhance your capabilities as a worker. One of the most transformative applications of AI is in health care. While AI has made strides in diagnosis and drug discovery, its true potential goes beyond.
Hanh: 00:08:13
Imagine AI developing personalized treatment plans based on genetics, medical history, and lifestyle. By analyzing vast data and identifying patterns, AI could create targeted therapies for each patient. This could lead to better outcomes, fewer side effects, and more cost effective care. But the possibilities don't stop there. AI could revolutionize preventive medicine and health management. By continuously monitoring health data through wearables and smart sensors, AI could detect early signs
Hanh: 00:08:45
of disease long before symptoms appear. This enables proactive interventions and lifestyle changes to maintain optimal health. Imagine receiving personalized nutrition and exercise recommendations based on your genetics, or being alerted to health risks based on subtle changes in biometric data. AI could become a personalized health coach, empowering you to take control of your health. Of course, realizing this vision requires addressing data, privacy, security, and ethics challenges. We need robust frameworks to ensure health
Hanh: 00:09:23
data is protected and used responsibly. And that AI driven healthcare is accessible and equitable for all. But if we navigate these challenges, AI's potential to transform healthcare is incredible. So, I ask you, how do you envision AI shaping healthcare's future? What excites you about personalized medicine and predictive health management? What challenges must we overcome to realize this vision? Sophisticated AI tools have the potential to help you perform tasks more efficiently by providing real time insights.
Hanh: 00:10:08
Recommendations and decision support. This could lead to a narrowing of the skill gap between entry level and highly skilled positions, empowering all workers to perform at a higher level. As a business owner, this presents an opportunity to rethink job roles and workflows, identify tasks that can be augmented or automated by AI. Then redesign jobs around these new efficiencies. This may involve upskilling employees to work alongside AI systems, or creating new roles focused on managing and optimizing AI implementations.
Hanh: 00:10:47
Imagine a future where AI assistants help with tasks like data analysis, writing, and problem solving. These AI powered tools could greatly enhance productivity and decision making across all levels of your organization. By empowering employees with AI, you can boost innovation, job satisfaction, and overall performance. However, this transformation requires investment in AI tools and training, prioritize enhancing employee capabilities through AI powered solutions to stay competitive in the AI driven future. What if AI could not only
Hanh: 00:11:24
augment human workers, but also enable entirely new job roles. Imagine a world where AI becomes a creative collaborator working alongside you to generate novel ideas and solutions. Picture, an AI powered brainstorming tool that can help teams ideate and innovate at an unprecedented scale. This could give rise to new roles like AI creativity, facilitators who specialize in harnessing AI's creative potential leading brainstorming sessions, guiding AI assisted ideation, and helping turn AI generated concepts into actionable ideas. Or consider the potential for AI
Hanh: 00:12:08
to enable more fluid and dynamic work arrangements with AI handling routine tasks and providing real-time support, you could have more flexibility in when and where you work. This could lead to the emergence of AI enabled remote work specialists who optimize remote workflows and ensure seamless collaboration between AI and distributed teams. Designing AI power tools and processes that enable you to be productive from anywhere in the world. AI could also give rise to entirely new industries and job
Hanh: 00:12:47
roles that we can't yet imagine. Just as the internet sparked the creation of roles like social media managers and app developers, AI could spur the emergence of new AI centric careers. We may see the rise of AI ethics officers who ensure the responsible development and deployment of AI systems or AI personalization experts who specialize in creating hyper personalized experiences using AI. The possibilities are endless and the job market of the future may look very different from today. But what if we take this further?
Hanh: 00:13:28
Imagine AI creating entirely new fields of study. Picture AI driven biomimicry, where AI learns from nature to innovate in architecture and engineering. Or consider quantum AI, combining AI and quantum computing to solve impossible problems. These fields could create new jobs like A. I. biomimicry specialists and quantum AI researchers. They would push boundaries and unlock new possibilities. To stay ahead, attend conferences and read
Hanh: 00:13:59
research papers on these emerging areas. Consider how they might intersect with your industry and look for collaboration opportunities. By embracing these AI frontiers, you can be a pioneer in your field. You can shape the future and unlock potential for yourself and society. So, I ask you, what new AI driven fields capture your imagination? How might you start exploring these exciting frontiers today? As AI evolves, it's crucial for you to stay open to these new possibilities. AI is poised to profoundly
Hanh: 00:14:39
impact creativity and the arts. As AI becomes more sophisticated, it shows glimmers of creativity. From AI generated music and poetry to algorithms creating stunning visual art, AI blurs the lines between human and machine creativity. But what does this mean for the arts future? Will AI collaborate with human artists to push boundaries? Or could AI become a stand alone creative force, rivaling human masters? These are questions artists, philosophers, and technologists
Hanh: 00:15:18
are grappling with as AI evolves. As a business owner or a creative professional, stay attuned to these developments. Consider how they might impact your work. Could AI assisted tools help generate new ideas or explore creative directions? Might collaborating with AI open up new possibilities for expression or innovation? At the same time, consider the ethical implications of AI in the arts. How do we ensure AI generated art isn't mimicking human artists? How do we attribute authorship when AI
Hanh: 00:15:50
is involved in the creative process? These complex questions require ongoing dialogue as AI integrates into the creative world. So, I ask you, how do you envision AI shaping creativity and artistic expression? What role will AI play in your creative process or industry? Embracing AI not only as a tool for efficiency, but also as a catalyst for innovation and job creation will be key. So, I ask you, what unique job roles do you think AI could enable in the future? How can we harness AI's potential,
Hanh: 00:16:29
not only to enhance existing jobs, but to create entirely new opportunities? As AI continues to advance, it's crucial to consider the societal and regulatory implications. The adoption of AI will likely face resistance and regulatory challenges, particularly in sensitive sectors like health care and education, which have complex regulations and entrenched practices. As a business owner, this means proactively engaging with policymakers and regulators to shape the development of AI regulations.
Hanh: 00:17:13
Advocate for policies that support innovation while addressing ethical concerns by participating in industry groups and providing input on proposed regulations. Demonstrating responsible AI practices will be crucial in building trust with regulators and the public. Stay informed about regulatory developments in your industry and adapt your AI strategies accordingly to ensure compliance. This may require investing in compliance expertise and developing robust AI governance frameworks.
Hanh: 00:17:47
Navigating the regulatory landscape will be an ongoing challenge as AI evolves. You must strike a balance between innovation and responsible deployment, addressing legitimate concerns around ethics, safety, and fairness. To create a regulatory environment that fosters AI's positive impact and ensures that it is used for the good of society, collaboration between industry, policymakers, and other stakeholders will be crucial. As AI integrates into our lives and decision making, it could transform how we govern.
Hanh: 00:18:23
Imagine AI analyzing vast data on public sentiment, economics, and social issues. It could provide policymakers with real time insights for effective governance. AI driven simulations could model outcomes of different policy proposals, helping leaders make informed decisions. But AI's implications for governance go beyond insights and recommendations. AI could help people take part in and influence policymaking. By letting them share their views on draft laws, think of AI platforms that enable people to give feedback on bills or using machine learning
Hanh: 00:19:04
to identify and prioritize issues important to different communities. This could ensure diverse perspectives are heard and policies reflect everyone's needs. Of course, using AI in governance raises questions about transparency, accountability and fairness. We must ensure AI decision making processes are open to public scrutiny and that mechanisms prevent bias or discrimination. We must also consider risks of relying too heavily on AI, such as hacking or manipulation.
Hanh: 00:19:38
Despite these challenges, AI's potential to transform governance is significant. By harnessing AI to analyze data, simulate outcomes, and engage citizens, we could create responsive, effective, and inclusive governance that better serves everyone. So I ask you, how do you envision AI shaping governance and decision making? What opportunities and challenges do you see? How can we ensure AI strengthens democracy and promotes the public good? However, navigating AI regulations is not just about compliance, it's
Hanh: 00:20:16
also about proactive leadership. As a business owner, you have an opportunity to set the standard for responsible AI practices in your industry. By going beyond mere compliance and actively promoting ethical AI development, you can differentiate yourself and build trust with customers, partners, and the public. This may involve establishing internal AI ethics boards, conducting regular audits of AI systems, and being transparent about AI decision making processes. It could also mean investing in research to address potential biases
Hanh: 00:20:51
and ensure fairness in AI algorithms. By taking a leadership role in AI ethics, you can not only navigate regulatory hurdles, but also shape the future of AI governance, contributing to the development of industry standards and best practices that prioritize safety, transparency, and accountability. Proactive AI governance can help you mitigate potential risks and liabilities associated with AI deployment. By ensuring that AI systems are designed and used responsibly, You can reduce the likelihood of unintended consequences or legal challenges.
Hanh: 00:21:30
This is particularly important as AI becomes more prevalent in high stakes domains, like healthcare, finance, and transportation, where a single AI malfunction or biased decision could have severe consequences. Therefore, approach AI governance not as a box ticking exercise, but as a critical strategic priority. Embed AI ethics and responsibility into every stage of the AI life cycle, from development to deployment and monitoring. This requires ongoing collaboration between AI teams, legal experts, ethicists, and business
Hanh: 00:22:04
leaders, as well as a culture of transparency, accountability, and continuous improvement. By embracing this proactive approach to AI governance, you can not only navigate regulatory challenges, but also build a foundation for long term success in the AI driven future, fostering trust, mitigating risks, and positioning yourself as a leader in responsible AI innovation. So I ask you, how can you go beyond compliance and take a leadership role in AI ethics and governance? What practical steps can you take to ensure the responsible
Hanh: 00:22:45
development and deployment of AI? Here are some actionable tips and exercises for you. First, research AI powered learning platforms and explore how they can personalize your learning experience. If you're a teacher or educator, consider incorporating AI tools into your curriculum to provide adaptive learning experiences for your students. Advocate for the responsible integration of AI in education at your local schools or educational institutions. Second, identify tasks in your current role that could be augmented
Hanh: 00:23:27
or automated by AI and develop skills to work alongside AI systems. Stay updated on emerging AI technologies and their potential impact on your industry. Cultivate a growth mindset and be open to learning new skills and adapting to AI driven changes in the workforce. Third, familiarize yourself with current AI regulations and policies in your industry. Engage in discussions and provide feedback on proposed AI regulations to help shape the regulatory landscape. If you're a business owner,
Hanh: 00:24:04
establish internal AI ethics guidelines and best practices to ensure responsible AI deployment. Remember to continuously learn about AI and its potential impact on your personal and professional life. Engage in discussions about AI ethics and responsible AI development. Embrace AI as a tool for positive change. And consider how you can harness its potential to create a better future. Let's reflect on the key takeaways. AI has the potential to transform education, enhance workforce efficiency, and reshape job roles.
Hanh: 00:24:51
However, this transformation comes with societal and regulatory challenges that must be navigated. As a business owner, you have a crucial role to play in shaping the future of AI. Invest in AI talent and infrastructure, engage with policymakers, and prioritize responsible practices. By doing so, you can harness AI's potential for innovation, growth, and competitive advantage. To achieve this vision, we need more than just technological advancements. We need a fundamental shift in mindset. We need to cultivate a culture
Hanh: 00:25:26
of curiosity, creativity, and continuous learning. Fostering collaboration across disciplines, sectors, and borders. We need to prioritize human centered design, ensuring that AI serves the needs and values of the people it impacts. As we navigate this uncharted territory, there will undoubtedly be challenges and uncertainties, But remember, you have the power to shape this AI driven future, whether you're a student, a professional, or a business owner, there are steps you can take to prepare for and influence the changes ahead.
Hanh: 00:26:07
Consider upskilling in AI related fields such as data science, machine learning, or AI ethics. Online platforms like AI50 offer a wide range of podcasts. Live events in an AI user group to help you build relevant skills. Stay informed about the latest developments in AI by following industry publications, attending conferences, and engaging with AI communities online. Connect with us on LinkedIn at AI 50 and subscribe to our newsletter, which provides valuable insights and keeps you up to date on emerging trends.
Hanh: 00:26:49
If you're a business owner, start exploring how AI can be responsibly integrated into your organization. Develop an AI strategy that aligns with your values and priorities. And invest in building an AI literate workforce, seek out partnerships with AI experts and organizations to guide your journey by taking these proactive steps. You can position yourself and your organization to thrive in the AI powered world of tomorrow. The journey ahead may be uncertain, but one thing is clear. The future belongs to those
Hanh: 00:27:23
who dare to imagine it. As we've seen throughout this discussion, the potential for AI to transform our world is vast and far reaching. But perhaps one of the most exciting and important applications of AI lies in its ability to help us solve problems. Complex global challenges and create a better future for all. Imagine a world where AI is used to tackle problems like climate change, poverty, and disease. By analyzing vast amounts of data on weather patterns, carbon emissions, and resource consumption, AI could help us
Hanh: 00:27:58
develop more accurate climate models, and identify the most effective strategies for reducing our environmental impact. AI powered simulations. AI could be used to test different approaches to carbon sequestration or renewable energy, allowing us to identify the most promising solutions and scale them up quickly. In the fight against poverty and inequality, AI could be a powerful tool for optimizing resource allocation and ensuring that aid and support reaches those who need it most. Machine learning algorithms could
Hanh: 00:28:35
analyze data on income, education, and health outcomes to identify patterns and risk factors. enabling more targeted and effective interventions. AI power platforms could also be used to connect marginalized communities with essential services and support, helping to bridge the digital divide and promote greater social and economic inclusion. And in the realm of healthcare, AI could be a game changer in the fight against disease. From accelerating drug discovery and development to enabling more accurate
Hanh: 00:29:11
and early diagnosis, AI has the potential to revolutionize the way we prevent, treat, and cure illness. By analyzing genomic data and other biomarkers, AI could help us develop personalized therapies that are tailored to an individual's unique biology, improving outcomes, and reducing side effects. Of course, harnessing the power of AI to solve global challenges will require unprecedented levels of collaboration and coordination between governments, businesses, civil society organizations, and other stakeholders.
Hanh: 00:29:49
We'll need to work together to develop shared frameworks and standards for the responsible development and deployment of AI, ensuring that it is used in ways that are ethical, transparent, and accountable. But if we can rise to this challenge, the potential for AI to help us build a better world is truly incredible. By leveraging the power of this transformative technology, we could unlock new possibilities for human progress. And create a future that is more sustainable, equitable, and prosperous for all. So, I ask you, what role do you
Hanh: 00:30:24
think AI will play in solving the great challenges of our time? How can we work together to ensure that AI is developed and used in ways that benefit humanity as a whole? And what steps can we take today to start building that better future. So let's dream big, think differently and create a future that exceeds our wildest expectations, looking to the future, the long term implications of AI for human evolution are profound with AI integrating into our lives and biology, we may be entering a new era. One where the boundaries between
Hanh: 00:31:07
human and machine intelligence blur. Imagine a future where AI is not just a tool, but a part of us. Brain computer interfaces and neural implants could allow us to merge with AI. We could augment our cognitive abilities and access vast knowledge and processing power. We could become transhumans with capabilities exceeding unaugmented humans. But this raises questions about human identity and the nature of intelligence. If we merge with AI, when do we cease being human? Will there be a day when human and machine
Hanh: 00:31:44
intelligence are indistinguishable? These are not just theoretical questions, but ones we may face as AI advances. As individuals in society, we must think deeply about these implications. We must consider what they mean for our understanding of ourselves and our place in the world. We must also consider the risks and unintended consequences of merging with AI, such as losing autonomy or becoming dependent on technology in uncontrollable ways. Despite these challenges, AI's potential to shape human evolution is profound.
Hanh: 00:32:25
By augmenting our intelligence and offering new ways to understand the world, AI could help solve problems and achieve feats once thought impossible. It could drive human progress and transformation in the coming decades and centuries. So I ask you, how do you envision AI shaping human intelligence and evolution? What possibilities and pitfalls do you see? How can we ensure AI integration benefits humanity as a whole? Thank you for joining me on this exploration of AI's
Hanh: 00:33:00
transformative potential. If you found value in today's discussion, I would greatly appreciate it if you could take a moment to leave a review and share your thoughts. Your feedback helps me improve the podcast and bring you more engaging and informative content. Subscribe to the podcast to stay updated on the latest episodes, exploring the fascinating world of AI together. Let's embrace the AI revolution and create a future that benefits us all. And remember, this is just the beginning. As we continue to uncover the
Hanh: 00:33:35
mysteries of AI, there will be countless more opportunities to learn. To innovate and to shape the future. Stay curious, stable, and stay tuned for more mind expanding discussions in the episodes to come. Until then, keep dreaming, keep exploring, and keep pushing the limits of what's possible. The future is ours to create, and with AI as our ally, there's no telling how far we can go.
Narrator: 00:34:13
Wow. What an incredible journey into the world of AI and its revolutionary impact on education, work and society. Hanh hopes this episode of AI50 Connect has sparked your imagination and inspired you to think about how you can be a part of shaping this AI driven future. Remember, AI is not just a technological advancement. It's a powerful force that is transforming the way we learn, work, and live. With AI50 as your guide, you can stay informed and prepared for the changes that lie ahead.
Narrator: 00:34:46
Head over to our website, AI50.ai to discover more about our insights and resources at the forefront of the AI revolution. While you're there, don't forget to sign up for our newsletter and stay up to date on the latest AI trends, breakthroughs, and success stories. Make sure to subscribe to AI50 Connect on your preferred podcast platform and leave us a review. Your feedback is invaluable in helping us create content that explores the most pressing questions and exciting possibilities surrounding AI.
Narrator: 00:35:18
Connect with us on LinkedIn, TikTok, Twitter, and YouTube for a wealth of content designed to keep you engaged and informed about AI's transformative potential. And if you're ready to be a part of this exciting journey, reach out to us at AI50.ai, our team is here to support you every step of the way. Thanks for joining Hanh on this eye opening adventure into the AI revolution. Remember, with AI50, you're not just adapting to change, you're driving it. Until next time, keep learning, innovating, and embracing the
Narrator: 00:35:50
incredible possibilities that AI has in store for us all.
Hanh: 00:00:05
The most exciting aspect of RAG and Azure machine learning is their potential to democratize AI and make it accessible to businesses of all sizes and industries. With these tools, even small companies and startups can create powerful, intelligent applications that rival those of much larger enterprises.
Narrator: 00:00:30
Welcome to AI50 Connect, your gateway to the extraordinary world of artificial intelligence and its revolutionary impact on businesses, entrepreneurs, and the lives of people across generations. Add AI50. We're passionate about transforming data into groundbreaking innovations in today's captivating episode, unlocking the power of retrieval, augmented generation RAG for business. Your host in AI luminary Hanh Brown explores the game changing potential of RAG technology in sectors like
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healthcare, legal, real estate and information intensive businesses. Hanh breaks down the intricacies of RAG, revealing how it combines the prowess of large language models with specific business data to deliver highly accurate and personalized responses to customer queries. With AI50's cutting edge LLM apps, businesses across diverse industries can harness the full potential of RAG, tailoring solutions to their unique needs and preferences. We dive deep into RAG's ability to revolutionize data handling, streamline
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processes, and enhance customer satisfaction in various sectors. Each episode is a thrilling expedition, packed with inspiring stories, trailblazing innovations, and thought provoking conversations with industry leaders. We navigate the advancements and ethical implications of RAG, illuminating how it can drive positive change and fuel business growth. Whether you're an entrepreneur seeking to leverage RAG for your venture, a business owner aiming to serve clients better, or simply captivated by the
Narrator: 00:02:12
transformative power of AI, join Hanh on this enlightening odyssey. Get ready for captivating storytelling, expert insights, and real world applications that showcase the incredible depth and breadth of RAG. Let's embark on this exciting journey together.
Hanh: 00:02:34
Hello, everyone, and thank you for joining us on today's amazing episode, where we'll be looking at the amazing world of Retrieval Augmented Generation, or REG for short. My name is Hanh Brown, and I'm delighted to be your host on this adventure into the advanced field of data solutions. Picture this, you're running a healthcare clinic, a legal firm, a real estate agency, or any business that deals with a vast amount of information. You want to provide your clients with the most accurate, personalized, and efficient service possible, but
Hanh: 00:03:08
you're drowning in a sea of data. That's where REG comes in. It's like having a superhero sidekick that can process all your information at lightning speed and deliver the most relevant answers to your client's questions. I'll break it down in simple terms and explain how it can be a game changer for businesses, especially in the realms of legal, Medicare, healthcare, and real estate. So what exactly is REG? In a nutshell, it's a way to combine the power of large language models.
Hanh: 00:03:42
Like GPT 4, with your company's own specific data. This unique combination allows you to generate highly accurate and relevant responses to customer queries, all while saving time and money on model fine tuning. Imagine you're running a healthcare clinic and you want to create a chatbot that can help patients understand their Medicare coverage. With RAG, you can feed your chatbot all of the relevant information about Medicare plans, benefits, and eligibility requirements.
Hanh: 00:04:13
Then, when a patient asks a question like, does my Medicare plan cover prescription drugs? The chat bot can quickly scan through the data and provide a personalized answer based on the patient's specific plan. But that's not all. RAG can also be a game changer for real estate businesses. Let's say you have a database of property listings, complete with details about each home's features and features. Location, and price. With REG, you can create a recommendation engine that suggests properties
Hanh: 00:04:47
to potential buyers based on their preferences and search history. So if a buyer is looking for a three bedroom home with a backyard in a specific neighborhood, your REG powered system can quickly find the best matches and present them to the buyer. The possibilities are endless, whether you're a legal firm looking to streamline your document search process, or Or a healthcare provider wanting to create personalized treatment plans for patients. RAG can help you unlock the full potential of your data. Now, you might be thinking, this
Hanh: 00:05:21
sounds great, but how do I actually implement RAG in my business? In this episode, we'll explore the key components of RAC and how you can get started with Azure AI services like Azure AI Search and Azure Machine Learning. Let's start by talking about Azure AI Search, which is the foundation of RAC. In simple terms, Azure AI Search is a service that allows you to index and search. Through large volumes of data, making it easy to find the information you need when you need it. Think of it like a super powered
Hanh: 00:06:00
search engine for your business data, whether you have text documents, images, or even videos. As your AI search can help you organize and search through it all effortlessly. To put this into context, let's consider a real world example in the healthcare industry. Imagine you run a large hospital system with multiple facilities, each with its own electronic health record, EHR system. These EHR systems contain a wealth of data about your patients, including their medical histories, medications, allergies, and test results.
Hanh: 00:06:41
But with so much data spread across different systems and formats. It can be a challenge for clinicians to find the information they need quickly and easily. This is where Azure AI Search comes in. With Azure AI Search, you can create a unified index of all your EHR data. Making it easy for clinicians to search and find the information they need, regardless of which facility or system it comes from. For example, let's say a doctor needs to find all the patients who have been prescribed a certain
Hanh: 00:07:20
medication in the last year. With Azure AI Search, the doctor can simply type in the name of the medication and get instant results showing all of the relevant patient records across the entire hospital system. But Azure AI Search isn't just about keyword searches. It also uses advanced natural language processing. and machine learning algorithms to understand the meaning and context behind your data. This means that it can provide more accurate and relevant search
Hanh: 00:07:56
results, even when the search query isn't an exact match for the data. For example, let's say a doctor searches for patients with high blood pressure, but some of the patient records use the term hypertension instead. With Azure AI Search, the system can understand that these terms are synonymous and return all of the relevant results. Even if the exact phrase, high blood pressure, doesn't appear in the data. Another key advantage of Azure AI Search is its ability to handle unstructured data, such as clinical notes and discharge summaries.
Hanh: 00:08:36
These types of data are often in a narrative format, with important information buried in long paragraphs of text. With Azure AI Search, you can use advanced techniques like entity recognition and sentiment analysis to extract key insights and make this unstructured data more searchable and actionable. For example, let's say you want to find all the patients who have a history of smoking and have been diagnosed with lung cancer. With Azure AI Search, you can create a custom entity recognition model
Hanh: 00:09:13
that looks for mentions of smoking and lung cancer in the clinical notes, and then use this information to generate a list of relevant patient records. This kind of advanced analysis would be impossible with a traditional keyword search. Azure AI Search But with Azure AI Search, it becomes a powerful tool for uncovering insights and improving patient care. Finally, AI Search is designed to be flexible and scalable, so it can grow and adapt as your healthcare organization evolves. Whether you're starting with a
Hanh: 00:09:46
small pilot project, Or rolling out a system wide search solution. AI Search has the tools and capabilities to meet your needs. And with its tight integration with other Azure services, such as Azure Machine Learning and Azure Cognitive Services, You can create even more powerful and intelligent search experiences that improve clinical decision making and patient outcomes. AI Search is the foundation of RAG because it provides a fast, flexible, and intelligent way to search and analyze your healthcare data.
Hanh: 00:10:24
By making it easy for clinicians to find the information they need when they need it, Azure AI Search can help improve the quality and efficiency of patient care while also reducing the burden on healthcare staff. And when combined with other Azure services and the power of RAG, it becomes an even more potent tool for driving innovation and transformation. Let's say you're a legal firm with a vast database of case files and court decisions. With Azure AI Search, you can quickly index all these documents and make them
Hanh: 00:11:01
searchable by keywords, dates, and time. Or even specific legal concepts. So, when a lawyer needs to find a relevant case to support their argument, they can simply type in a few keywords and get instant results, saving them hours of manual searching. But how does this relate to RAG? Well, when you're generating responses using a large language model, it's crucial to have access to relevant information from your company's knowledge base. That's where Azure AI Search comes in. It indexes your data and provides the language model with the
Hanh: 00:11:40
context it needs to generate accurate and helpful responses. For instance, let's say you have a Medicare chatbot that needs to answer questions about different health plans. With Azure AI Search, you can index all the details about each plan, including coverage, premiums, and network providers. When a user asks a question like, What's the best Medicare plan for someone with diabetes? The chatbot can quickly search through the indexed data and provide a personalized recommendation based on the user's specific needs.
Hanh: 00:12:19
This is a game changer for businesses because it means you can provide fast, accurate support without having to manually search through countless documents yourself. Plus, as your knowledge base grows and evolves, Azure AI Search can easily keep up, ensuring that your RAG system always has access to the latest information. So, to recap, Azure AI Search is the foundation of RAG because it enables you to index and search through your company's data, providing the language model with the context it needs to generate relevant and accurate responses.
Hanh: 00:12:59
In the next section, we'll explore how you can use Azure Machine Learning to actually implement REG in your business. Now that we've covered the basics of Azure AI Search, let's talk about how you can actually implement REG using Azure Machine Learning. Think of Azure Machine Learning as a user friendly tool that helps you create smart applications, like chatbots or recommendation systems. Without needing to be a tech wizard. It's like having a personal assistant that handles all the complex behind the scenes work for you.
Hanh: 00:13:40
To give you a real world example, let's say you're a healthcare provider looking to create a personalized treatment plan for a patient with chronic back pain with Azure Machine Learning and RAG. You can create a system that analyzes the patient's medical history, lifestyle factors, and treatment preferences, and then generates a customized plan that takes all these factors into account. The system can even suggest alternative therapies or medications that Based on the latest research and clinical guidelines, but how does this all work in practice? Let's walk through the steps of
Hanh: 00:14:17
implementing RAG with as your machine learning using a real world example from the legal industry. Imagine you're a law firm that specializes in intellectual property. Your firm has a vast database of past cases. Legal briefs and court decisions related to IP law. But it's a challenge for your lawyers to sift through all this information and find the most relevant precedents and arguments for their current cases. With Azure Machine Learning and RAG, you can create a system that helps
Hanh: 00:14:56
your lawyers find the information they need quickly and easily. Here's how it works. First, you use Azure AI Search to index all your legal data, including case files, briefs, and court decisions. This creates a unified search index that your lawyers can query. You then use Azure Machine Learning to create a custom RAG model that understands the language and terminology of IP law. This model is trained on your specific legal data, so it can provide highly accurate and relevant results. You then use Prompt Flow to create
Hanh: 00:15:31
a user friendly interface for your lawyers to interact with the RAG model. This could be a simple search box where lawyers can type in their queries, or a more advanced interface that allows them to filter results by case type, jurisdiction, or other criteria. When a lawyer types in a query, such as find cases related to patent infringement in the software industry. The REG model uses Azure AI Search to find the most relevant cases and briefs and then generates a summary of the key arguments and precedents. The lawyer can then review the
Hanh: 00:16:10
summary and decide which cases and arguments to use in their current case. They can also provide feedback on the relevance and usefulness of the results, which is used to continuously improve the RAG model over time. By using this RAG system, your law firm can save countless hours of manual research and help your lawyers build stronger, more persuasive cases. And because the system is built on Azure machine learning, it can scale to handle even the largest and most complex legal databases without sacrificing speed or accuracy.
Hanh: 00:16:51
But the benefits of RAG and Azure machine learning don't stop there. Because these tools are so flexible and customizable, you can use them to create all kinds of intelligent applications across a wide range of industries and use cases. for listening. For example, in the real estate industry, you could use RAID to create a system that helps property managers find the most relevant maintenance records and vendor contracts for their buildings. In the retail industry, you could use RAG to create a system that helps
Hanh: 00:17:22
store managers forecast demand and optimize inventory levels based on past sales data and customer behavior. The possibilities are endless, and the best part is that you don't need to be a machine learning expert to get started. With Azure Machine Learning and PromptFlow, you can create powerful RAG systems using a simple, intuitive interface that guides you through the process step by step. Of course, as with any AI system, there are some best practices and considerations to keep in mind when implementing RAG with Azure Machine Learning.
Hanh: 00:18:00
For example, you'll want to make sure that you have a clear understanding of your data. And the specific problem you're trying to solve. You'll also want to invest time in testing and refining your RAG model to ensure that it's providing accurate and relevant results, but with the right approach and the power of Azure machine learning and RAG, you can create intelligent applications that transform the way you work and serve your customers. Whether you're. In healthcare, legal, real estate,
Hanh: 00:18:32
or any other industry, RAG and Azure Machine Learning can help you unlock the full potential of your data and drive innovation like never before. Another example, let's say you're a healthcare provider looking to create a personalized treatment plan for a patient with chronic back pain. With Azure Machine Learning and RAC, you can create a system that analyzes the patient's medical history, lifestyle factors, and treatment preferences, and then generates a customized plan that takes all these factors into account. Azure Machine Learning The system can
Hanh: 00:19:11
even suggest alternative therapies or medications based on the latest research and clinical guidelines. One of the coolest features of Azure Machine Learning is called Prompt Flow, which makes implementing RAG a breeze. Imagine you have a bunch of data scattered across different files and folders, like patient records, medical journals, and more. or clinical trial results. With PromptFlow, you can easily organize and combine this data with a powerful language model, creating a RAG system that can understand and respond to
Hanh: 00:19:55
complex medical queries in no time. But how does this all work under the hood? Let's dive a bit deeper into the technical concepts behind RAG and Azure Machine Learning. At its core, RAG is all about using machine learning algorithms to generate relevant responses based on a given input or query. The key components of a RAG system are the language model, which is trained on a large corpus of text data, and the retrieval mechanism, which fetches relevant information from your company's knowledge base.
Hanh: 00:20:29
Azure Machine Learning provides a range of pre built models and tools that make it easy to implement these components without needing to start from scratch. For more technically inclined listeners, it's worth noting that Azure Machine Learning supports a wide range of machine learning frameworks and libraries, including popular ones like TensorFlow, PyTorch, and Sikkit Learn. This allows developers to leverage existing models and architectures, or build custom models from scratch. Azure Machine Learning also provides a suite of tools for data
Hanh: 00:21:06
preprocessing, feature engineering, and model evaluation, enabling end to end machine learning workflows. For example, you can use the prompt flow feature to create a pipeline that takes your input data, processes it using various machine learning algorithms, and then generates an output based on the retrieved information under the hood. PromptFlow uses techniques like data encoding, semantic search, and natural language processing to understand the meaning and context behind your data. It then uses this understanding to generate a relevant response
Hanh: 00:21:46
that takes into account it. Thank you. For those interested in the technical details, PromptFlow leverages state of the art deep learning models, like transformers, to encode data into dense vector representations. These representations capture the semantic meaning of the data, allowing for more accurate retrieval and generation. PromptFlow also employs advanced techniques like cross attention and self attention to weigh the importance of different data points and generate more coherent and
Hanh: 00:22:19
contextually relevant responses. But the benefits don't stop there. PromptFlow also makes it easy to keep your RAG system up to date as your business evolves. Let's say you add new products to your store or receive fresh customer reviews. With PromptFlow, you can easily retrain your language model and update your data, ensuring that your chatbot always has the latest information at its fingertips. This is a game changer for businesses of all sizes. Instead of spending countless hours and resources building a RAG system
Hanh: 00:22:59
from scratch, You can use PromptFlow to get up and running quickly. It's like having a ready made solution that you can customize to fit your specific needs. Plus, as you collect more data and feedback from your customers, PromptFlow makes it easy to continuously improve your RAC system. It's like having a smart assistant that learns and grows with your business, helping you stay ahead of the curve and provide better service to your customers. PromptFlow. com So, whether you're a small online
Hanh: 00:23:28
store looking to create a simple chatbot, or a large enterprise wanting to build a sophisticated recommendation engine, Azure Machine Learning and PromptFlow have you covered. With these tools at your fingertips, you can create intelligent applications. That understand your customers needs and provide personalized experiences all without breaking a sweat. While RAG and PromptFlow offer many benefits for businesses, implementing these technologies can come with its own set of challenges. One of the biggest hurdles is
Hanh: 00:24:12
dealing with unstructured and siloed data that's scattered across different systems and formats. Let's say you're a real estate company with a database of property listings. But the information is spread out across multiple spreadsheets, documents, and images. Before you can use RAG to create a recommendation engine, you first need to consolidate and organize all this data in a way that's easy to search and analyze. This is where Azure AI Search and Prompt Flow come in handy. With these tools, you can easily
Hanh: 00:24:50
ingest and index your data from various sources, creating a unified knowledge base that's ready for RAG. Diving deeper into the technical aspects, Azure AI Search uses advanced indexing techniques like inverted indexes, and Term Frequency Inverse Document Frequency, TF IDF, to efficiently store and retrieve data. It also supports custom analyzers and tokenizers, allowing you to tailor the indexing process to your specific data and use case. PromptFlow, on the other hand, provides a declarative language for defining
Hanh: 00:25:33
data ingestion and processing pipelines. Making it easy to build complex data workflows without writing low level code. PromptFlow even offers pre built connectors and APIs. That make it easy to integrate with popular data sources like Salesforce, SharePoint, and Dynamics 365. Another challenge businesses face is keeping their RAG system up to date with the latest information in industries like healthcare and legal, new regulations, guidelines. and best practices are constantly emerging.
Hanh: 00:26:11
And it's crucial to ensure that your REG system is always providing accurate and compliant information. With PromptFlow, you can easily retrain your language model and update your data on a regular basis, ensuring that your REG system stays current and reliable. You can even set up automated workflows that trigger retraining and updating based on specific events or schedules. Thanks. So you don't have to worry about falling behind. But perhaps the biggest challenge businesses face is simply knowing
Hanh: 00:26:42
where to start with RAG and PromptFlow. Implementing these technologies can seem daunting, especially if you don't have a background in data science or machine learning. That's where the ease of use and accessibility of Azure Machine Learning and PromptFlow come in. These tools are designed to be user friendly and intuitive, even for non technical users. www. microsoft. com With guided workflows, drag and drop interfaces, and pre built templates, you
Hanh: 00:27:11
can create powerful RAG systems without needing to write a single line of code. Plus, Azure Machine Learning and PromptFlow come with extensive documentation, tutorials, and support resources to help you get started and troubleshoot any issues along the way. Whether you're a beginner or an experienced developer, Azure You'll find plenty of guidance and best practices to help you succeed with RAG. As RAG and Azure machine learning continue to evolve, the possibilities for businesses are truly endless. In the coming years, we can expect to
Hanh: 00:27:51
see even more advanced and sophisticated applications of these technologies across a wide range of industries and use cases. One exciting area of development is in the realm of personalized medicine. With RAG and Azure Machine Learning, healthcare providers could create systems that generate customized treatment plans based on a patient's unique genetic profile, medical history, and lifestyle factors. This could revolutionize the way we approach diseases like cancer, diabetes, and heart disease, leading to more targeted and effective therapies.
Hanh: 00:28:32
Another promising application of RAG is in the field of predictive maintenance. By analyzing vast amounts of sensor data from machines and equipment, RAG systems could predict when a particular component is likely to fail, allowing businesses to schedule maintenance and repairs proactively. This could help companies avoid costly downtime and improve overall efficiency and reliability. But perhaps the most exciting aspect of RAG and Azure machine learning is their potential to democratize AI and make it accessible to businesses
Hanh: 00:29:06
of all sizes and industries. With these tools, even small companies and startups can create powerful, intelligent applications that rival those of much larger enterprises. As the technology continues to mature and become more user friendly, we can expect to see a proliferation of RAG powered chatbots, recommendation engines, and decision support systems across a wide range of domains. From customer service and sales to healthcare and finance, RAG has the potential to transform the way businesses operate and interact with their customers.
Hanh: 00:29:43
Of course, with great power comes great responsibility, and it's important for businesses to use RAG and Azure machine learning in an ethical and transparent manner. This means being clear about how data is being collected and used. Providing users with control over their personal information and ensuring that the outputs of RAG systems are fair, unbiased, and aligned with human values. But with the right approach and safeguards in place, the future of RAG and Azure machine learning is truly bright. As these technologies continue to
Hanh: 00:30:18
evolve and mature, they have the potential to unlock new insights. Drive innovation and create value for businesses and society as a whole. And that's an exciting prospect indeed. In today's episode, we've taken a deep dive into the world of retrieval augmented generation or REG, a powerful approach that combines the best of large language models and custom business data to create intelligent applications that can transform industries. We started by exploring the basics of RAG and how it works. We saw how RAG can help businesses provide
Hanh: 00:30:59
personalized and accurate responses to customer queries, while also saving time and money on model fine tuning. Next, we looked at Azure AI Search. The foundation of REG and how it provides a fast, flexible, and intelligent way to search and analyze large volumes of data. We explored how Azure AI Search can handle structured and unstructured data, and how it uses advanced techniques like natural language processing and entity recognition to provide more accurate and relevant search results. We then turned our attention to Azure Machine Learning, and And how it
Hanh: 00:31:43
provides a user friendly platform for building and deploying RAG models. We walk through a step by step example of how to implement RAG using Azure machine learning and prompt flow. And how this can help businesses in industries like legal, real estate and retail unlock the full potential of their data. Throughout the episode, we emphasize the importance of taking a thoughtful and strategic approach to implementing RAG. And how businesses need to have a clear understanding of their data and the problems they're trying to solve.
Hanh: 00:32:20
We also highlighted the benefits of RAG, including improved accuracy, efficiency, and customer satisfaction, and how it can help businesses stay ahead of the curve in an ever changing landscape. As we wrap up today's episode, I want to leave you with a few key takeaways. First, RAG is a powerful approach that can help businesses of all sizes and industries create intelligent applications. That drive innovation and growth. Second, as your AI search and as your machine learning provide a comprehensive and user friendly
Hanh: 00:33:03
platform for implementing RAG, even if you're not a machine learning expert. And third, by taking a thoughtful and strategic approach to RAG businesses can unlock the full potential of their data and create intelligent applications that transform the way they work and And serve their customers. If you're interested in learning more about RAG and how it can benefit your business, I encourage you to reach out to our team. We can walk you through this process. And if you enjoyed today's episode, I would love to hear
Hanh: 00:33:41
your thoughts and feedback. Please take a moment to leave a review and rating on your favorite podcast platform, and let us know what you found most valuable and interesting about today's discussion. Your feedback helps us continue to create content that is relevant, informative, and engaging for our listeners. Thank you for tuning into today's episode of the AI in Business podcast. Until next time, stay curious and keep exploring the exciting world of AI and machine learning.
Narrator: 00:34:17
Wow. What a mind expanding exploration of retrieval, augmented generations, potential for businesses and entrepreneurs. Hanh hopes this episode of AI50 Connect has ignited your imagination and inspired you to consider how RAG can help you scale your venture and deliver unparalleled service to your clients. Remember, RAG is more than just a fancy acronym. It's a transformative tool that empowers you to make data driven decisions, uncover hidden opportunities, and
Narrator: 00:34:45
revolutionize your business processes. With AI50 as your trusted partner, you can fully leverage the power of RAG to propel your business to new heights. Visit our website, AI50.ai, to discover more about our cutting edge RAG solutions tailored for businesses of all sizes. While you're there, be sure to subscribe to our newsletter and stay at the forefront of the latest AI trends, insights, and success stories. Don't forget to hit that subscribe button on AI50. Connect on your favorite podcast platform and leave us a review.
Narrator: 00:35:21
Your feedback is invaluable in helping us create content that addresses your most pressing AI questions and concerns. Connect with us on LinkedIn, TikTok, Twitter, and YouTube for a treasure trove of RAG related content designed to keep you ahead of the curve. And when you're ready to embark on your RAG journey, reach out to us at AI50.ai, our team of experts is here to guide you every step of the way. Thank you for joining Hanh on this mind expanding RAG adventure. Remember with AI50, you're not just keeping up with
Narrator: 00:35:52
change, you're pioneering it. Until next time, keep innovating, growing, and harnessing the power of RAG to transform your business and the lives of your clients.
Hanh: 00:00:05
With the power of AI, we could revolutionize healthcare, making it more accessible, affordable, and personalized. Imagine a world where every person has access to the same level of medical expertise, regardless of their location or income. Where doctors can spend more time caring for patients. In less time on paperwork and
Hanh: 00:00:26
administrative tasks where diseases are caught earlier, treatments are tailored to individual needs and outcomes are vastly improved.
Narrator: 00:00:42
Welcome to AI50 connect your gateway to the fascinating interplay between technology, policy, and society. At AI50, we're passionate about exploring how data and innovation shape our collective future. In today's captivating episode, Politics and the Future of Tech, your host and visionary, Hanh Brown. Delves into the complex dynamics
Narrator: 00:01:04
between technology, government policy, and societal impact. Hanh breaks down the crucial decisions that will mold the societal frameworks of tomorrow from AI regulation to blockchain innovation and equitable tech access with AI 50s cutting edge insights, businesses. Policymakers and the public can navigate the ethical dilemmas, geopolitical tensions and challenges
Narrator: 00:01:30
of fair tech distribution. We go beyond the hype to uncover how these technologies can fundamentally transform society for the better. Each episode is a thought provoking journey filled with compelling stories, groundbreaking ideas and conversations with trailblazers. We examine the interplay between big tech startups and government, shedding
Narrator: 00:01:55
light on how collaborative engagement can drive positive change and align technology with ethical standards. Whether you're a business leader, policymaker, or simply curious about technology's transformative power, join Hanh on this enlightening exploration. Get ready for engaging storytelling, expert analysis, and real world examples that showcase the incredible
Narrator: 00:02:17
potential of technology to shape a more equitable and sustainable future. Let's embark on this journey together.
Hanh: 00:02:32
Welcome to today's episode, Politics and the Future of Tech, where we'll be diving deep into the exciting world of technology's future. I am Hanh Brown, your host. This is a topic that affects every aspect of our lives, from the way we communicate and work to the way our governments operate and make policies. As someone who's passionate about
Hanh: 00:02:54
technology, I know just how crucial it is to get these policies right. How we choose to act today, whether it's about setting rules for artificial intelligence, supporting innovation in the blockchain domain. Or providing fair access to technological progress will affect our world for many years and possibly generations. But here's the thing.
Hanh: 00:03:23
The future of technology isn't just about the gadgets and gizmos. It's about the fundamental ways in which these tools can transform our society for better or for worse. It's about grappling with complex ethical questions, navigating geopolitical tensions, and ensuring that the benefits of progress are distributed fairly and equitably.
Hanh: 00:03:47
That's why today I'm thrilled to dive into these topics with you. Because the future of technology is not only challenging, but also amazing. It can transform healthcare and education, fight climate change and poverty, and offer countless opportunities. But realizing that potential will require more than just technical know how. It will require a deep understanding
Hanh: 00:04:11
of the social, political, and economic factors that shape technological development. It will require collaboration across borders. And across disciplines, and most importantly, it will require a willingness to ask tough questions, challenge assumptions and think creatively about the kind of future we want to build.
Hanh: 00:04:36
So let's get started on this journey together. A journey towards a future that's not just technologically advanced, but fundamentally human. Picture this. On one side, we have the tech giant. The big, established companies with vast resources and influence. On the other, we have the startups.
Hanh: 00:05:02
The small, innovative newcomers, eager to make their mark. You might think they're on the same team, united by their love for technology and progress. But when it comes to their interests and interactions with the government, things get a bit more complicated. The big tech companies, they're focused on maintaining their dominance in the market.
Hanh: 00:05:24
They've worked hard to build their empires, and they're not about to let anyone else steal their thunder. So what do they do? They lobby the government, using their deep pockets and connections to shape policies in their favor. But is that really in the best interest of innovation and competition? Do we want a world where a handful
Hanh: 00:05:42
of companies control the direction of technological progress? Where startups with groundbreaking ideas struggle to even get a foot in the door, that's where the startups come in. They have a different vision, one that challenges the status quo and pushes the boundaries of what's possible. They're the underdogs, the disruptors, fighting for a chance to prove themselves.
Hanh: 00:06:09
But they can't do it alone. They need a level playing field, one where their ideas can flourish and compete on their own merits. Now, here's the thing. The technology industry as a whole needs a voice in policymaking. They can't just sit back and let the government make decisions that could impact their future without any input.
Hanh: 00:06:31
It's like trying to play a game without knowing the rules. But how do they make their voices heard? That's where lobbying and advocacy come in. But it's not just about throwing money at the problem and hoping for the best. It's about building relationships, educating policy makers, and finding common ground.
Hanh: 00:06:51
It's a long term commitment, one that requires patience, persistence, and commitment. And a willingness to engage in good faith. But even then, it's not always easy. The government has its own interests and priorities, and they don't always align with those of the tech industry. So, how do we find that balance? How do we create policies that
Hanh: 00:07:12
promote innovation and progress, while also ensuring fair competition and protecting consumer interests? These are the questions we need to grapple with as we navigate this complex landscape. And the stakes couldn't be higher. Because at the end of the day, it's not just about the tech companies and their bottom lines.
Hanh: 00:07:34
It's about how technology can make our lives better. How it can solve problems and create opportunities for everyone. Imagine a world where startups with brilliant ideas can thrive. Where competition drives innovation and keeps the big players on their toes. Imagine a world where policymakers have the knowledge and understanding
Hanh: 00:07:56
to craft regulations that protect consumers without stifling progress. Imagine a world where technology is a force for good, a tool for tackling our greatest challenges and unlocking our highest potential. That's the world we should be striving for. And it starts with getting the relationship between tech companies
Hanh: 00:08:18
and the government, right? That's It starts with fostering open, honest dialogue and finding ways to work together towards common goals. As we continue to explore the future of technology, keep this dynamic in mind. Ask yourself, what kind of world do you want to live in? What role should technology play in shaping that world?
Hanh: 00:08:42
And what can we do as individuals and as a society? To make sure that the relationship between tech companies and the government works for everyone. These are the questions that will define the future of technology. And we all have a stake in getting the answers right. Let's talk about the hot topic
Hanh: 00:09:04
that's on everyone's minds. Artificial intelligence. It's advancing at a mind boggling pace with new breakthroughs and applications emerging every day. But as we marvel at the incredible potential of this technology, we can't help but wonder, are we ready for the consequences? On one hand, AI has the power to
Hanh: 00:09:29
revolutionize industries and transform our lives in ways we never thought possible. Think of a world where medical conditions are detected and identified more quickly and precisely than before. Where education is tailored to each student's individual needs and learning style. Where transportation is more secure and effective, thanks to autonomous cars.
Hanh: 00:09:58
The possibilities are endless, and the benefits could be immense. But on the other hand, there's a darker side to AI that we can't ignore. What happens when AI systems are used to make decisions that perpetuate biases and discriminate against certain groups. What if AI is used to manipulate public opinion, spread misinformation, or even carry out cyber attacks?
Hanh: 00:10:23
These are not just hypothetical scenarios. They are real risks that we need to confront head on. So how do we ensure that AI is developed and used responsibly in a way that maximizes its benefits and minimizes its risks? There are no easy answers, but there are some key principles that we can follow. First and foremost, we need to
Hanh: 00:10:46
foster a competitive and diverse market for AI development. We can't afford to have just a handful of companies controlling the future of this technology. We need a wide range of players, from startups to academia to government agencies, all pushing the boundaries of what's possible and keeping each other in check.
Hanh: 00:11:10
It's like a system of checks and balances for the tech world. But even with a competitive market, we can't just sit back and let the chips fall where they may. We need smart, targeted regulations that address the specific risks and challenges posed by AI. For example, if an AI system is being used to make hiring decisions, there should
Hanh: 00:11:34
be clear guidelines in place to prevent discrimination and ensure fairness. If an AI chatbot is interacting with children, there should be safeguards to protect their privacy and well being. At the same time, we have to be careful not to over regulate AI to the point where we stifle innovation. It's a delicate balance, and finding that sweet spot will require ongoing dialogue
Hanh: 00:12:00
and collaboration between policymakers, technologists, ethicists, and the public. One approach that I believe holds a lot of promise is to focus on regulating the applications of AI, rather than the underlying technology itself. What do I mean by that? Well, think about it this way, the core algorithms and models that power AI are essentially just mathematical equations.
Hanh: 00:12:25
They're not inherently good or bad, it's how they're used that matters. So, instead of trying to regulate the math, we should be regulating the specific ways in which AI is being applied in the real world. Another crucial piece of the puzzle is transparency. We need to be able to peer inside the black box of AI and understand
Hanh: 00:12:49
how it's making decisions, especially when those decisions have real world consequences for people's lives. That's where open source comes in. When AI is developed in the open, with the code and algorithms available for anyone to inspect and contribute to, it helps prevent monopolies and ensures that the technology is being used responsibly. Open source also has the added benefit
Hanh: 00:13:14
of democratizing AI and making it accessible to a wider range of people. Imagine if the only people who could work on AI were those who could afford expensive proprietary software and hardware. We'd be missing out on a wealth of talent and perspectives from researchers, developers, and communities around the world.
Hanh: 00:13:38
By embracing open source, we can tap into that collective intelligence and create AI that truly benefits everyone. So, as we continue on this rollercoaster ride of AI development, let's keep these principles in mind. Let's ask the tough questions and have the difficult conversations. Let's push for competition, regulate applications responsibly, and
Hanh: 00:14:03
champion transparency and open source. And most importantly, let's never lose sight of the ultimate goal, creating AI that is not just technologically impressive, but fundamentally ethical and beneficial to society as a whole. What do you think? How can we strike the right balance between innovation and responsibility when it comes to AI?
Hanh: 00:14:27
What role should policymakers, technologists, and the public play in shaping the future of this technology? Bye bye. These are the questions that will define the coming decades, and we all have a stake in getting the answers right. So let's keep the conversation going, and let's work together to build an AI powered future that we can all be proud of.
Hanh: 00:14:55
Alright, let's dive into another exciting and often misunderstood area of technology, blockchain and cryptocurrencies. These terms can be a bit intimidating, conjuring up images of shady dealings and get rich quick schemes. Let's break it down in a way that makes sense and shows the true potential of these technologies.
Hanh: 00:15:19
At its core, blockchain is all about decentralization. It's a way of recording and verifying transactions without relying on a central authority. Like a bank or a government. Think of it like a giant tamper proof ledger that everyone can see and contribute to, but no single entity controls.
Hanh: 00:15:41
It's like taking the power away from the middlemen and giving it back to the people. One of the most well known applications of blockchain is cryptocurrencies, like Bitcoin. These digital currencies allow for secure and fast transactions without the need for traditional financial institutions. Thanks.
Hanh: 00:16:00
It's like having a digital wallet that you control, rather than trusting a bank to manage your money. But here's the thing. Cryptocurrencies are just the tip of the iceberg when it comes to the potential of blockchain. Think of a world where you have true ownership and control over your personal data.
Hanh: 00:16:21
No more big tech companies profiting off your information without your consent or knowledge. With blockchain, you could choose to sell your data directly to companies or keep it entirely private. It's about putting the power back in your hands and giving you the freedom to decide how your information is used. And that's just the beginning.
Hanh: 00:16:43
This concept of decentralization is particularly important when it comes to AI. As we discussed earlier, we don't want a future where AI is controlled by just a few powerful entity with no transparency or accountability. Decentralized AI, powered by blockchain, could ensure that AI systems are open, auditable, and aligned with the
Hanh: 00:17:05
values of the communities they serve. But of course, with any new technology, there are challenges and risks to consider. How do we prevent fraud and protect consumers? How do we ensure the integrity of blockchain systems and prevent them from being hijacked by bad actors? That's where clear and
Hanh: 00:17:27
effective regulation comes in. We need frameworks in place to mitigate these risks, but we also need to be careful not to stifle innovation in the process. It's a delicate balance, but one that we must strive to achieve, because the potential benefits of blockchain and decentralization are simply too great to ignore.
Hanh: 00:17:50
Imagine a world where data marketplaces allow individuals to securely sell or license their personal information, getting compensated for their contributions, while helping companies improve their products and services. Imagine a world where the provenance of digital assets like artwork or music can be tracked and verified on the blockchain, eliminating disputes
Hanh: 00:18:14
over ownership and authenticity. And perhaps most importantly, imagine a world where the spread of misinformation and deepfakes can be combated with the help of blockchain technology by establishing a tamper proof record of the origin and manipulation of digital content. We could help restore trust in the media we consume and the information we rely on.
Hanh: 00:18:37
But to get there, we need to approach this brave new world of decentralized technologies with a mix of excitement and caution. We need to push for innovation while also advocating for responsible regulation. We need to educate ourselves and others about the true potential of blockchain and cryptocurrencies. Separating the hype from the reality.
Hanh: 00:18:59
So what do you think? Are you ready to embrace the decentralized future? What excites you most about the potential of blockchain and cryptocurrencies? What concerns do you have and how do you think we can address them? These are the questions we need to be asking ourselves. As we navigate this rapidly evolving
Hanh: 00:19:18
landscape, because one thing is for sure, blockchain and decentralization are not going away anytime soon. They have the power to fundamentally reshape our world from the way we conduct business to the way we interact with each other and with technology. But it's up to us to shape that future in a way that benefits society as a whole. It's up to us to have the
Hanh: 00:19:45
difficult conversations. To ask the tough questions and to push for the kind of innovation that uplifts and empowers everyone, not just a select few. So let's get to work and educate ourselves and others. Let's collaborate across industries and disciplines. Let's build the decentralized future we want to see.
Hanh: 00:20:10
One block at a time. The potential is immense, and the journey ahead is sure to be a wild ride. But together, we can make it a ride worth taking. Now, let's zoom out and look at the bigger picture. The development of technology doesn't happen in a vacuum. It's deeply intertwined with
Hanh: 00:20:32
global competition and geopolitics. Shaping the very fabric of our world. And right now there are two major players dominating the landscape, the United States and China. It's like a high stakes game of chess with each nation vying for supremacy in fields like AI, blockchain, and quantum computing. The stakes couldn't be higher because
Hanh: 00:20:59
whoever wins this race could have a significant advantage in shaping the future Not just of their own country, but of the entire world. For the United States, maintaining a competitive edge is crucial. It's not just about economic prosperity or technological prowess, it's about safeguarding fundamental values like freedom, democracy, and innovation.
Hanh: 00:21:25
The U. S. has long been a leader in technological advancement, thanks in large part to a culture that encourages risk taking, entrepreneurship, and innovation. And outside the box thinking, but China is a formidable competitor with a government that's heavily investing in technology and a population
Hanh: 00:21:45
eager to adopt new innovations. They have the advantage of a centralized system that can quickly mobilize resources and implement policies. Allowing them to move at a speed that can be difficult for other countries to match. So how can the U. S. stay ahead in this high stakes game? The answer lies in doubling
Hanh: 00:22:04
down on its strengths. Fostering innovation, attracting top talent from around the world and creating an environment where startups can thrive. It means resisting the temptation to over regulate or stifle competition in the name of short term gains and instead taking a long term view that prioritizes the free flow of ideas and the power of the market to drive progress.
Hanh: 00:22:34
But it's not just about the U. S. and China. The global technology landscape is complex and multifaceted with many other players vying for a seat at the table. Europe, for example, has taken a different approach to technology regulation, one that prioritizes privacy, security, and the concept
Hanh: 00:22:54
of the precautionary principle. This principle holds that new technologies should be heavily restricted or even banned until they can be proven absolutely safe. While well intentioned, this approach can significantly slow down progress and innovation, putting countries that adopt it at risk of falling behind in the global race for technological supremacy.
Hanh: 00:23:18
Imagine if the precautionary principle had been applied to past inventions like the automobile, the airplane, or the internet. We might still be riding horses, sending letters by mail, and relying on libraries for information. Of course, safety is important, but it must be balanced with the potential benefits of new technologies and the need for speed.
Hanh: 00:23:42
and agility in a rapidly changing world. Many developing nations, however, want to use technology to skip over conventional steps of development and address urgent problems like poverty, inequality, and access to education and healthcare. For these countries, technology represents not just an opportunity, but a necessity. These countries could achieve the next breakthroughs in technology by
Hanh: 00:24:10
supporting innovation, creating their own startup environments, and working with other nations and organizations. Their progress could have positive impacts, not just for their own people, but for global society. As global citizens, we have a responsibility to support and collaborate with these efforts, recognizing that the benefits of
Hanh: 00:24:33
technology should be accessible to everyone, not just a select few. But navigating this complex global landscape is no easy feat. It requires a delicate balance of competition and cooperation, of innovation and regulation, of speed and safety. It requires leaders who are willing to take bold risks and make difficult decisions, while also being attuned
Hanh: 00:24:53
to the needs and concerns of their citizens in the wider world. As we look to the future, let's ask ourselves, What kind of world do we want to live in? One where technology is a force for good, driving progress and improving lives? Or one where it's a source of division, inequality, and conflict? The choices we make today will
Hanh: 00:25:18
shape the answer to that question. Will we prioritize short term gains over long term sustainability? Will we let fear and uncertainty hold us back or will we embrace the power of innovation to tackle the greatest challenges of our time? These are not easy questions, but they are essential ones because the stakes are high and the future is ours to shape.
Hanh: 00:25:44
So let us rise to the occasion. Let us work together across borders and boundaries, sectors and disciplines to build a world where technology is a force for good. A tool for empowerment and a catalyst for positive change. Let us strive for a future where competition drives innovation, where regulation promotes rather than
Hanh: 00:26:05
hinders progress, and where the transformative power of technology is harnessed for the good of all humanity. It won't be easy, but it is possible. And it starts with each and every one of us doing our part to shape a brighter, more hopeful tomorrow. As we've explored throughout this podcast, technology has the potential to transform our world in profound
Hanh: 00:26:36
ways, but it's not just about the cool gadgets or the latest app. It's about how these innovations can be harnessed to address some of the most pressing challenges we face as a society. Think about it. With the power of AI, we could revolutionize healthcare, making it more accessible, affordable, and personalized. Imagine a world where every person
Hanh: 00:27:00
has access to the same level of medical expertise, regardless of their location or income. Where doctors can spend more time caring for patients and less time on paperwork and administrative tasks. Where diseases are caught earlier, treatments are tailored to individual needs. And outcomes are vastly improved,
Hanh: 00:27:21
but the potential doesn't stop there. We could use blockchain to create some bits of secure and transparent voting systems. Strengthening our democracies and ensuring that every voice is heard. We could leverage the internet of things to build smarter, more sustainable cities, reducing waste and improving quality of life.
Hanh: 00:27:46
And with the rise of clean energy technologies, we could combat climate change and build a more sustainable future for generations to come. However, to truly realize this potential, we need to ensure that everyone has access to the benefits of technology. And that starts with education. We need to equip the next generation with the skills and knowledge they
Hanh: 00:28:11
need to thrive in a tech driven world. That means investing in STEM programs, coding boot camps, and digital literacy initiatives. It means reimagining our educational systems to prioritize problem solving, creativity, and adaptability, the key skills of the 21st century. But access to education is just the beginning.
Hanh: 00:28:34
We also need to make sure that technology is inclusive and representative of the diverse communities it serves. We can't afford to leave anyone behind in this digital revolution. Whether it's ensuring that AI algorithms are free from bias, creating tech solutions that cater to the needs of underserved populations, or building products with accessibility
Hanh: 00:28:57
in mind, inclusivity must be at the forefront of our efforts. Thank you When it comes to some of the most fundamental aspects of our lives, housing, healthcare, and education technology could be a game changer. Imagine if we could use AI in big data to predict and prevent disease making healthcare more proactive and less reactive.
Hanh: 00:29:24
Or if we could leverage blockchain to create more efficient and affordable housing markets. Helping to address the growing crisis of homelessness and housing insecurity. The possibilities are endless, but they require us to think creatively and collaboratively about how we apply these powerful tools. Of course, with great power
Hanh: 00:29:45
comes great responsibility. As we embrace the transformative potential of technology, we must also be mindful of the risks and challenges. We need robust frameworks for data privacy and security to protect individuals rights and prevent abuse. We need to address the ethical implications of AI and automation, ensuring that these technologies
Hanh: 00:30:07
are developed and deployed in ways that benefit society as a whole. And we need to have difficult conversations about the future of work. And how we can ensure that everyone has access to meaningful, fulfilling livelihoods in a world where many jobs may be automated. Ultimately, building a better future with technology will require
Hanh: 00:30:34
a culture of techno optimism, balanced with responsible innovation. It means embracing the vast potential of these tools, while also being clear eyed about the challenges and working proactively to address them. It means we all have a responsibility, whether you're a technologist making the next amazing app, a policymaker creating rules that support innovation
Hanh: 00:31:00
and protect consumers, or just a citizen using technology in your everyday life. So let's dream big and bold. Let's imagine a future where technology is a force for good, a tool for tackling our greatest challenges. And unlocking our highest potential. Let's approach this journey with curiosity, collaboration, and a commitment to making a positive impact.
Hanh: 00:31:30
Because if we get it right, there's no limit to what we can achieve for ourselves, for our communities, and for the world. As we come to the end of this podcast, I want to leave you with a few final thoughts. Throughout our discussion, we've explored the incredible potential of technology from AI and blockchain to the societal
Hanh: 00:31:56
implications and the global landscape. But if there's one thing I hope you take away from this conversation, it's that the future of technology is not predetermined. It's a story that we are all writing together. Every day through our choices and actions, we stand at a critical juncture, a moment where the decisions we make about technology will ripple out and
Hanh: 00:32:25
shape our world for generations to come. And that's why it's so important that we get it right. We need policymakers who are informed and proactive, who understand the nuances and complexities of these technologies. We need technologists who are driven not just by the pursuit of innovation, but by a deep sense of responsibility and ethics. But most of all, we need a society that
Hanh: 00:32:49
is engaged and empowered, a society that doesn't just consume technology, but actively participates in shaping it. That means staying informed, asking tough questions, and holding those in power accountable. It means advocating for policies that promote competition, protect privacy, and ensure that the benefits of technology are distributed fairly and equitably.
Hanh: 00:33:18
Because, at the end of the day, technology is not an end in itself. It's a means to an end, a tool that we can harness To build the kind of world we want to live in a world that is more just, more sustainable, more compassionate, a world where every individual has the opportunity to thrive and reach their full potential. So let us seize this moment. Let us approach the future of technology
Hanh: 00:33:42
with a sense of possibility and purpose. Let us be bold in our vision, but humble in our approach. And let us never forget that the true power of technology lies not in the machines or the algorithms, but in the human spirit that drives them. Together, we can build a future that is not just technologically advanced, but fundamentally human.
Hanh: 00:34:10
A future that reflects our highest aspirations and our deepest values. A future that we can be proud to leave to the generations that will follow.
Narrator: 00:34:27
Wow. What an eyeopening exploration of the complex interplay between technology, politics, and society. Hanh hopes this episode of AI50 Connect has inspired you to think about How we can collectively shape a future where innovation aligns with ethical standards and promotes global welfare. Keep in mind that the decisions we
Narrator: 00:34:46
make today about technology regulation, innovation, and access will have profound impacts on generations to come. With AI50 as your guide, you can stay informed and engaged in this crucial conversation. Head over to our website, AI50, to discover more about our insights and solutions at the intersection of technology and society.
Narrator: 00:35:11
While you're there, don't forget to sign up for our newsletter and stay informed about the latest trends, ideas, and success stories. Make sure to subscribe to AI50 Connect on your preferred podcast platform and leave us a review. Your feedback is invaluable in helping us create content that tackles the most pressing questions and concerns
Narrator: 00:35:29
about technology's impact on our world. Connect with us on LinkedIn, Tik TOK, Twitter, and YouTube for a wealth of content designed to keep you at the forefront of the tech society dialogue. And if you're ready to be part of shaping a better future, Reach out to us at AI50. Our team is here to collaborate with you every step of the way. Thanks for joining Hanh on this
Narrator: 00:35:52
thought provoking adventure. Remember, with AI50, you're not just adapting to change, you're driving it. Until next time, keep innovating and working towards a future where technology uplifts us all.
Hanh: 00:00:05
What's even more incredible is the pace at which AI is advancing. Many experts believe that we're on the cusp of a new era in AI where the technology will start to rival and even surpass human intelligence in many domains. Some predict that we could achieve artificial general intelligence AGI, that is, an AI system that can
Hanh: 00:00:25
match or exceed human intelligence across a wide range of tasks. Within the next few decades, others believe it could happen even sooner. Of course, predicting the future is always a tricky business, and there are many unknowns and uncertainties when it comes to AI development.
Narrator: 00:00:52
Welcome to AI50, your gateway to the captivating world of artificial intelligence. In this episode, the future of AI We'll take an exciting journey through AI's abilities, it's possible effects on our lives and the ethical issues that arise from this revolutionary technology. AI50 is not just a podcast. It's a captivating exploration of
Narrator: 00:01:13
AI's potential to reshape the world. We share fascinating stories, cutting edge inventions, and engaging discussions with AI trailblazers. Our goal is to reveal AI's. Diverse and rich aspects and its ability to create beneficial impacts for people from all walks of life from the possibility of human AI merging to AI's. Role in scientific discovery,
Narrator: 00:01:36
Hanh, our host will guide us through the most exciting and thought provoking aspects of AI's. Future. So get ready for an enlightening adventure. Let's hand it over to Hanh Brown to begin unraveling the mysteries of AI's. Future.
Hanh: 00:01:58
In today's episode of the future of AI, we'll dive into AI's capabilities, its potential impact on various aspects of our lives, and the ethical considerations surrounding this transformative technology. So let's get started. Imagine a world where machines can think and learn like humans, or even surpass us. That's the potential of
Hanh: 00:02:25
artificial intelligence. AI has already shown remarkable abilities in various fields, from playing complex games to assisting in scientific discoveries. But how far can AI really go? Some experts believe that AI could one day match or even exceed human intelligence, while others are more cautious, pointing out the current limitations of AI systems.
Hanh: 00:02:53
One of the main questions is whether AI can truly be creative and intuitive. Sure, AI can process vast amounts of data and find patterns, but can it make those aha moments that often lead to groundbreaking ideas? Think about it like this. Imagine you're a chef and you have a recipe book. An AI system could easily
Hanh: 00:03:17
follow the recipes and even optimize them based on data. But could it create an entirely new dish that surprises and delights your taste buds? That's the kind of creativity and intuition that some argue AI might struggle with. However, others point out that AI has already shown glimmers of
Hanh: 00:03:40
creativity in certain domains, like creating art or composing music. So, the jury's still out on this one. Another aspect to consider is The timeline for achieving human level or superhuman AI. Some experts predict it could happen within decades, while others believe it's further away. The truth is, there is a lot
Hanh: 00:04:01
of uncertainty around this, and predicting the future is always tricky. What we do know is that AI is advancing at an incredible pace. And it's capabilities are expanding every day from self driving cars to AI assisted medical diagnoses. The potential applications are vast and exciting, but with great power comes great responsibility.
Hanh: 00:04:29
And as we develop more advanced AI systems, we'll need to grapple with some tough questions about the limitations and risks involved. Now, here's a wild idea. What if we could merge with AI? Imagine having a computer chip in your brain that could instantly access information or even enhance your cognitive abilities.
Hanh: 00:04:58
Some experts believe that human AI merging could be a real possibility in the future. The idea is that by integrating AI technology with our own biology, we could overcome our limitations, become something more than human. Think about it like getting a superhero upgrade. Suddenly, you could process information faster, remember everything you've
Hanh: 00:05:23
ever learned, and even communicate with machines using your thoughts. But not everyone is on board with this idea. Some worry that merging with AI could lead to a loss of our humanity. Or even create a new form of inequality between those who can afford the technology and those who can't. There's also the question of whether
Hanh: 00:05:47
we would still be in control or if the AI would start calling the shots. It's a bit like the classic brain in a vat thought experiment. How do you know if your thoughts are really your own? And what happens if the AI becomes so advanced that That it decides to leave us behind. It's a scary thought, but some
Hanh: 00:06:09
experts warn that if we create super intelligent AI, it might not have much use for us mere mortals. On the other hand, some argue that merging with AI is the only way for us to keep up with the rapid pace of technological change. They say it's our best shot at staying relevant in a world increasingly shaped by machines.
Hanh: 00:06:36
Of course, this is all speculation at this point. We're still a long way from having the technology to truly merge with AI, and there are a lot of ethical and practical hurdles to overcome. But it's fascinating to think about the possibilities and to consider what the future might hold. Will we become cyborgs,
Hanh: 00:06:55
part human and part machine? Or will we find other ways to coexist with AI? While still retaining our humanity, only a time will tell, but one thing's for sure. The relationship between humans and AI is going to be one of the defining issues of the 21st century. All right. Let's talk about one of the most exciting
Hanh: 00:07:24
applications of AI, scientific discovery. Imagine having a super smart assistant that could help you solve complex problems and make groundbreaking discoveries in fields like biology, physics, and chemistry. That's exactly what AI is already starting to do. By analyzing vast amounts of data and finding patterns that humans might
Hanh: 00:07:52
miss, AI is helping scientists make new discoveries at an unprecedented pace. Take the field of drug discovery, for example. Traditionally, it could take years and billions of dollars to develop a new drug, with a lot of trial and error involved. But now, AI algorithms can predict which compounds are most likely to be effective, drastically reducing
Hanh: 00:08:14
the time and cost of the process. In fact, AI has already helped identify potential treatments for diseases like Alzheimer's and COVID 19. It's like having a team of super smart scientists working around the clock without ever getting tired or needing a coffee break. But it's not just about speed, AI is also helping us tackle problems that
Hanh: 00:08:41
were previously thought to be unsolvable. For example, predicting how proteins fold into specific shapes is a hugely complex problem that has stumped scientists for decades. But last year. An AI system called AlphaFold cracked the code, accurately predicting the structure of proteins based on their amino acid sequence.
Hanh: 00:09:04
This is a major breakthrough that could have huge implications for everything from drug design to material science. Of course, AI isn't a magic bullet. It still relies on the input of human scientists and the availability of high quality data. And there are some problems that even the most advanced AI systems can't solve, at least not yet.
Hanh: 00:09:28
But the potential is truly incredible. With AI as a tool, we could see a new era of scientific discovery, with breakthroughs happening faster than ever before. It's like having a cheat code for the universe. So, the next time you hear about a major scientific discovery, there's a good chance that AI
Hanh: 00:09:50
played a role. And who knows? Maybe someday, an AI system will even win a Nobel Prize. Stranger things have happened. Now, let's dive into one of the most fascinating and controversial topics in AI consciousness and Sentience. This is the idea that AI systems could one day have subjective
Hanh: 00:10:16
experiences, emotions, and even self awareness, just like humans do. It's a tricky concept because we don't really have a clear definition of what consciousness is, even in humans. Is it just a byproduct of complex information processing? Or, is there something more to it? Something that can't be reduced to mere computation?
Hanh: 00:10:40
Some experts argue that consciousness is an emergent property of any sufficiently complex system and that as AI systems become more advanced, they will naturally develop some form of sentience. Others are more skeptical, arguing that there's something unique about consciousness. About biological brains that can't be replicated in silicon.
Hanh: 00:11:03
They point out that even the most advanced AI systems today are still just crunching numbers without any real understanding or subjective experience. But what if we could create an AI system that truly believed it was conscious? Would that be enough to say that it actually was conscious or would it just be a very convincing simulation? These are the kinds of philosophical
Hanh: 00:11:28
questions that keep AI researchers up at night, because if we do create sentient AI, it would raise a whole host of ethical concerns. For example, would a sentient AI have rights? Would it be wrong to turn it off or delete it, effectively ending its existence? And if an AI system became more intelligent than humans, would we have any
Hanh: 00:11:54
right to control it or limit its actions? These are not just theoretical questions, they could have very real consequences as AI systems become more advanced, and there are no easy answers. Some researchers are already taking these issues seriously and working on developing frameworks for AI ethics that could guide the development and deployment of these systems.
Hanh: 00:12:21
But others worry that we're not moving fast enough and that we need to have these conversations now, before it's too late. Because once Pandora's box is open, it may be very difficult to close. So what do you think is consciousness, something that can be replicated in a machine? And if so, what would that mean for our understanding of ourselves
Hanh: 00:12:45
and our place in the universe? It's a fascinating question and one that we'll be grappling with for many years to come. As AI systems become more advanced and potentially sentient, We'll need to grapple with some tough ethical questions about their rights and responsibilities. For example, if we create an AI that can think and feel like a human,
Hanh: 00:13:14
would it be entitled to the same basic rights and protections that we enjoy? Would it be wrong to force it to work for us or to treat it like property? These are not just theoretical questions. They could have very real legal and social consequences. In fact, some countries have already started to grant legal status to certain types of AI systems.
Hanh: 00:13:39
In 2017, Saudi Arabia famously granted citizenship to a humanoid robot named Sophia. Now this was mostly a publicity stunt, but it raises some interesting questions about the legal personhood of AI. And in the European Union, there's been talk of granting certain types of AI systems a form of electronic personhood that would give them some
Hanh: 00:14:07
legal rights and responsibilities. But not everyone is on board with this idea. Some argue that granting rights to AI could be a slippery slope, leading to a world where machines have more rights than humans. Others worry that it could let companies off the hook for any harm caused by their AI systems.
Hanh: 00:14:29
There's also the question of accountability. If an AI system causes harm, who is responsible? The company that created it? The users who deployed it? The AI itself? These are thorny issues that will require a lot of careful thought and debate. And as AI systems become more
Hanh: 00:14:46
integrated into our lives, The stakes will only get higher. Another ethical consideration is the potential for AI to be used in ways that are harmful or discriminatory. We've already seen examples of AI systems that perpetuate bias and discrimination, often unintentionally. For example, there have been cases of facial recognition systems that are
Hanh: 00:15:14
less accurate for people of color or hiring algorithms that discriminate against women and minorities. These are serious problems that need to be addressed. Some argue that the solution is to make AI systems more transparent and accountable, so that we can understand how they make decisions and identify any biases. Others believe that we need to
Hanh: 00:15:36
have more diverse teams designing and testing these systems to help catch and correct these issues. Ultimately, the development of AI is going to require a lot of ethical reflection and hard conversations. We'll need to balance the incredible potential benefits of this technology with the very real risks and challenges it poses.
Hanh: 00:16:02
But one thing is clear, we can't just let the technology develop unchecked. We need to be proactive in shaping the future of AI to ensure that it benefits all of humanity. The field of AI is moving incredibly fast, and it can be hard to keep up with all the latest developments and breakthroughs. In just the past few years, we've seen AI systems that can beat world
Hanh: 00:16:33
champions at complex games, create stunningly realistic images and videos, and even write code and compose music. It's truly amazing to see how far the technology has come in such a short time. But what's even more incredible is the pace at which AI is advancing. Many experts believe that we're on the cusp of a new era in AI, where the technology will start
Hanh: 00:16:58
to rival and even surpass human intelligence in many domains. Some predict that we could achieve artificial general intelligence AGI, that is an AI system that can match or exceed human intelligence across a wide range of tasks. Within the next few decades, others believe it could happen even sooner. Of course, predicting the future is
Hanh: 00:17:23
always a tricky business, and there are many unknowns and uncertainties when it comes to AI development. There could be unforeseen roadblocks. or breakthroughs that completely change the trajectory of the field. But one thing that's clear is that the pace of progress is accelerating. Thanks to advances in computer hardware, big data, and machine learning algorithms,
Hanh: 00:17:51
AI systems are getting smarter and more capable at an exponential rate. Some experts even talk about the possibility of a technological singularity, a point at which AI becomes so advanced That it can recursively improve itself, leading to an intelligence explosion that quickly surpasses human understanding and control. Now this idea is still very speculative
Hanh: 00:18:14
and controversial, and not everyone in the AI community buys into it. But it does underscore just how transformative and disruptive this technology could be in the coming years and decades. So what does this mean for us? Well, for one thing, it means that we need to start thinking seriously. about the implications of advanced AI and
Hanh: 00:18:35
how we can ensure that it is developed and used in ways that benefit humanity. It also means that we need to be prepared for a world in which AI is an increasingly ubiquitous and powerful force, shaping everything from our economy and politics to our personal lives and relationships. This can be both exciting and daunting, depending on your perspective, but one thing is clear.
Hanh: 00:19:07
The future is coming, and it's going to be shaped by AI in ways that we can only begin to imagine. As we've seen, AI has the potential to transform our world in incredible ways, from revolutionizing scientific discovery to enhancing our own cognitive abilities. But it's also important to recognize that this powerful technology comes with significant risks and challenges
Hanh: 00:19:36
that we'll need to navigate carefully. On one hand, AI could be our greatest hope for solving some of the world's most pressing problems, like climate change, disease, and poverty. By augmenting human intelligence and creativity, AI could help us find new solutions and innovations, That we never could have imagined on our own. For example, AI powered systems are
Hanh: 00:20:01
already being used to optimize renewable energy grids, develop new materials for carbon capture, and create more efficient and sustainable supply chains. In the future, AI could play an even greater role in helping us transition to a more sustainable and equitable world. But on the other hand, AI could also pose existential risk to humanity if not developed and used responsibly.
Hanh: 00:20:28
One of the greatest concerns is the possibility of AI systems becoming so advanced that they could outpace and potentially harm human interests. This could happen through a variety of scenarios, such as AI systems pursuing goals that are misaligned with human values or AI being used as a tool for oppression and manipulation by malicious actors.
Hanh: 00:20:52
There are also risks associated with AI systems making consequential decisions that affect human lives. In society, such as in healthcare, finance, and criminal justice. If these systems are biased, opaque, or unreliable, they could lead to serious harms and injustices. So how do we ensure that AI remains a positive force for humanity?
Hanh: 00:21:17
It will require a concerted effort from researchers, policy makers, and society as a whole to prioritize the responsible development and governance of AI systems. This means investing in research on AI safety and ethics, creating standards and regulations for the development and deployment of AI, and fostering public dialogue and participation in shaping the future of this powerful technology.
Hanh: 00:21:48
Ultimately, the fate of AI and perhaps the fate of humanity will depend on the choices we make in the coming years and decades. We have an opportunity to steer this technology towards a future that uplifts and empowers all of us, but it will require wisdom, foresight, and a commitment to the greater good. One of the key debates in the AI
Hanh: 00:22:16
community today is over the question of whether AI models and algorithms should be open source and made freely available to the public. On one side of this debate are those who argue that openness and transparency are essential for the responsible development of AI. By making models and code publicly available, researchers and developers
Hanh: 00:22:41
can scrutinize them for potential biases, safety risks, and other issues. Open sourcing also allows for greater collaboration and innovation as developers around the world can build on and improve existing models. This could accelerate the pace of AI development and help ensure that its benefits are widely distributed. Some of the most influential AI
Hanh: 00:23:04
models and tools today, such as the machine learning framework TensorFlow and the language model GPT 3, have been open sourced by their creators. allowing anyone to use and build upon them. However, there are also valid concerns about the risk of open sourcing AI models, particularly as they become more advanced and potentially dangerous.
Hanh: 00:23:30
One worry is that malicious actors could use open source models to create harmful applications, such as deep fakes, spam bots, Or even autonomous weapons. There are also risks that bias or flawed models could be deployed at scale, leading to unintended consequences and harms. Some argue that the solution is to create a staged release model for AI, where models are first shared with
Hanh: 00:23:58
a trusted group of researchers and stakeholders who can vet them for safety and alignment with human values. Before being released more widely, others believe that the benefits of openness outweigh the risk and that the AI community has a responsibility to democratize access to this transformative technology. There are also questions about
Hanh: 00:24:21
the economic implications of open sourcing AI models. Some worry that it could lead to a concentration of power and wealth among a few large tech companies that have the resources to develop and deploy these models at scale. On the other hand, open sourcing could level the playing field and allow smaller players and individual developers
Hanh: 00:24:43
to create innovative applications and compete with larger firms. Ultimately, the debate over open sourcing AI models reflects the complex trade offs and uncertainties involved in the development of this powerful technology. As AI continues to advance and become more integrated into our lives and society. We'll need to find ways to balance the benefits of openness and
Hanh: 00:25:12
collaboration with the need for safety, security, and accountability. This will likely require new models of governance and cooperation among researchers, developers, policymakers, and the public to ensure that AI remains a force for good in the years and decades to come. As we've explored in this podcast, the future of artificial intelligence
Hanh: 00:25:41
is both exciting and uncertain. From its potential to revolutionize scientific discovery and augment human intelligence to the risks and challenges of creating safe and beneficial AI systems, there are many complex issues to navigate. One thing is clear, AI is advancing at an unprecedented pace, and its impact on our world is only going to
Hanh: 00:26:03
grow in the coming years and decades. As we move forward, it will be essential to approach the development of AI with both optimism and caution, working to harness its incredible potential while also mitigating its risks and ensuring that it benefits all of humanity. This will require ongoing collaboration and dialogue among researchers, policymakers, and the broader public as
Hanh: 00:26:30
we grapple with the profound implications of this transformative technology. Thank you It will also require a commitment to transparency, accountability, and the responsible development and deployment of AI systems. Ultimately, the future of AI is in our hands. We have the opportunity to shape this technology in ways that reflect our
Hanh: 00:26:54
values and aspirations as a species, and to create a world where AI is a powerful tool for solving our greatest challenges and enhancing our quality of life. But we must also be vigilant and proactive in addressing the risks and challenges posed by AI from the potential for misuse and unintended consequences to the need for robust safety and security measures. By working together and staying engaged in
Hanh: 00:27:20
these important conversations, we can help ensure that the future of AI is bright and that its benefits are shared by all. Thank you for joining us on this fascinating exploration of the future of AI. We hope that this podcast has sparked your curiosity and encouraged you to think deeply about the implications of this incredible technology.
Hanh: 00:27:45
If you enjoyed this episode, we'd love to hear your thoughts and feedback. Please take a moment to leave us a review and share this podcast with your friends and colleagues. Your support helps us continue to bring you insightful and engaging content at the intersection of technology and humanity. Until next time, keep learning, stay curious, and let's work together
Hanh: 00:28:10
to build a better future with the help of artificial intelligence. Thank you for listening.
Narrator: 00:28:21
Wow. What an incredible journey we've been on today with Hanh Brown. Exploring the boundless potential and complex challenges of artificial intelligence. From the awe inspiring possibilities of AI driven scientific breakthroughs to the mind bending implications of human AI merging, this episode has given us
Narrator: 00:28:39
a glimpse into the future that is both exhilarating and thought provoking. As we've learned, AI is not just a tool. It's a force that is reshaping our world in ways we are only beginning to understand. It's a technology that demands our attention, our curiosity, and our active engagement as we work to harness its power for the greater good.
Narrator: 00:29:00
At AI50, we are committed to being your trusted guide on this journey. We'll continue to bring you the latest insights, the most compelling stories, and the most innovative ideas from the front lines of AI research and development. Because we believe that the future of AI is not something that will happen to us, it's something that we have the power to shape.
Narrator: 00:29:20
So stay connected with us. Subscribe to AI50 and provide a review on your favorite podcast platform. Follow us on LinkedIn and YouTube and join the conversation. Together, we can build a future where AI is a powerful ally in our quest for a better world. Until next time, remember the future of AI is not something to fear.
Narrator: 00:29:41
It's something to embrace with open arms and an open mind. Thanks for listening.
Hanh: 00:00:06
With Azure Functions, they can create a workflow that automatically extracts the relevant data from the sale agreements using techniques like regular expressions. or natural language processing. The extracted data can then be validated against property records, tax databases, and other relevant sources.
Narrator: 00:00:31
Welcome to AI50, where we open the doors to the exciting world of artificial intelligence, focusing today on its impact in the legal field. In CSI episode, Revolutionizing Legal Document Processing with Azure AI, your host, Hanh Brown, will guide us through how Azure AI is changing the game for legal professionals. We're going to talk about how this
Narrator: 00:00:53
technology is improving the way legal documents are handled, making tasks quicker and more accurate for everyone from lawyers to paralegals. Get ready to learn about the nuts and bolts of intelligent document processing and how it's making a big difference in legal work, especially for our senior community.
Hanh: 00:01:17
Hello and welcome. On today's episode, AI powered intelligent document processing for legal services, we'll explore how intelligent document processing is transforming the legal industry. If you are a legal professional, you know firsthand the challenges of manually processing vast amounts of documents. It's time consuming, error prone, and
Hanh: 00:01:40
can hinder your ability to provide efficient services to your clients. But what if I told you there's a better way? Today, we'll dive into the world of Azure AI and discover how it can revolutionize the way you handle legal documents, whether you're a lawyer, paralegal, or part of a legal operations team. This episode is packed with valuable
Hanh: 00:02:04
insights that can help you streamline your document processing workflows. We'll start by looking at the current state of document processing in the legal industry and the pain points that come with it. Then we'll introduce Azure AI and its powerful services that can automate and enhance various aspects of document processing.
Hanh: 00:02:27
Throughout the episode, we'll explore real world applications. Providing a comprehensive understanding of how Azure AI can enhance your legal practice. Let's dive in. Let's kick things off with Azure Form Recognizer, a game changer for automating data extraction from legal documents. Imagine you're a paralegal working
Hanh: 00:02:48
on a case that involves hundreds of client intake forms. Manually going through each form and extracting relevant information, like client names, addresses, and case details, can be a daunting and time consuming task. This is where Azure Form Recognizer comes to the rescue. Think of it as a highly skilled assistant that can read and
Hanh: 00:03:20
understand your documents. Just like a human would, it uses advanced machine learning models to analyze the structure and content of your forms, accurately identifying and extracting key information. To put it into perspective, let's say you have a stack of 100 client intake forms. It might take you around five minutes to go through each form
Hanh: 00:03:46
and extract the necessary details. That's over eight hours of tedious work. With Azure Form Recognizer, you can automate this process and get the job done in a matter of minutes. But, how does it work? Azure Form Recognizer uses a technology called Optical Character Recognition, OCR, to convert the text in your documents into a machine readable format.
Hanh: 00:04:11
It then applies advanced algorithms and pre trained models to identify and categorize the different fields and elements within the document. For example, let's say you have a client intake form that includes fields like client name, Address, phone number, and case description. Azure Form Recognizer can automatically detect and extract the values associated
Hanh: 00:04:37
with each of these fields, organizing the information into a structured format that can be easily integrated into your legal software or database. One of the great things about Azure Form Recognizer is that it continuously learns and improves over time. As you process more documents, it gets smarter. and more accurate in its
Hanh: 00:04:59
data extraction capabilities. It can even handle variations in document layouts and formats, adapting to the unique characteristics of your legal forms. Let's consider the case of a law firm that specializes in estate planning. They receive hundreds of client questionnaires and intake forms on a daily basis, each containing crucial
Hanh: 00:05:20
information about clients assets, beneficiaries, and legal preferences. By implementing Azure Form Recognizer, the law firm was able to automate the data extraction process, significantly reducing the time and effort required to manually input client information into their systems. The paralegals and administrative staff could focus on more high value
Hanh: 00:05:45
tasks, such as client communication and document preparation, rather than spending hours on data entry. Azure Form Recognizer helped ensure the accuracy and consistency of the extracted data. With manual data entry, there's always a risk of human error, such as typos or misinterpreted handwriting. Azure Form eliminates these errors.
Hanh: 00:06:10
providing reliable and precise data extraction. In addition to client intake forms, Azure Form Recognizers can be applied to a wide range of legal documents, such as contracts, agreements, and legal filings. It can extract key clauses, dates, parties involved, and other relevant information, making it easier to manage and analyze legal documents at scale.
Hanh: 00:06:36
So, whether you're a solo practitioner or part of a large legal firm, Azure Form Recognizer can be a game changer in streamlining your document processing workflows. It saves time, reduces errors, and allows you to focus on delivering exceptional legal services to your clients. Let's talk about Azure Cognitive Search and how it can revolutionize the way
Hanh: 00:07:07
you search and retrieve legal documents. In today's digital age, legal professionals are drowning in a sea of information. From case files and legal research to contracts and regulations, Finding the right document when you need it can feel like searching for a needle in a haystack. Azure Cognitive Search is like having a highly intelligent
Hanh: 00:07:29
librarian at your fingertips. It goes beyond simple keyword matching and uses advanced techniques like natural language processing and semantic understanding to help you find the most relevant documents based on their meaning and context. Imagine you're working on a complex legal case. Involving intellectual property
Hanh: 00:07:50
rights, you need to find all the contracts and agreements related to a specific patent or trademark. With traditional search methods, you might spend hours sifting through countless documents, trying to find the ones that are most relevant to your case. With Azure Cognitive Search, you can simply ask a question in plain English, such as, Find all contracts related to
Hanh: 00:08:15
Patent X filed between 2015 and 2020. The search engine will understand your intent and retrieve the most pertinent documents, even if they don't contain the exact keywords you use. But how does it work? Azure Cognitive Search uses a combination of techniques to understand the meaning and context of your documents. It applies natural language processing.
Hanh: 00:08:44
Algorithms to analyze the text, extracting key entities, phrases, and sentiment. It also uses machine learning models to identify patterns and relationships between documents, allowing it to surface the most relevant results. One of the powerful features of Azure Cognitive Search is its ability to handle unstructured data. Legal documents often contain a mix
Hanh: 00:09:06
of text, tables, and images, making them challenging to search and analyze using traditional methods. Azure Cognitive Search can extract meaningful information from these unstructured documents, making them fully searchable and discoverable. For example, let's say you have a collection of legal briefs that include citations to
Hanh: 00:09:28
various case laws and statutes. Azure Cognitive Search can automatically identify and extract these citations, allowing you to quickly find all the documents that reference a specific case. Another great thing about Azure Cognitive Search is its ability to provide semantic search capabilities. Instead of just matching keywords, it can understand the intent behind
Hanh: 00:09:56
your search query and provide results that are conceptually related. This is particularly useful when you're not sure of the exact terminology or phrasing to use in your search. For instance, if you search for intellectual property infringement, Azure Cognitive Search can return documents that mention related concepts like copyright violation.
Hanh: 00:10:22
or trademark dispute, even if they don't contain the exact phrase, intellectual property infringement. To illustrate the power of Azure Cognitive Search, let's consider a scenario. A law firm specializing in environmental litigation needed to quickly find relevant case law and regulations related to a specific toxic substance. They had a vast database of
Hanh: 00:10:47
legal documents, but traditional keyword searches often returned irrelevant or incomplete results. By implementing Azure Cognitive Search, the law firm was able to significantly improve the accuracy and efficiency of their document retrieval process. Lawyers could easily search for documents using natural language queries, and the search engine would return the
Hanh: 00:11:11
most relevant results based on the meaning and context of the documents. Thanks. This not only saved the lawyers countless hours of manual searching, but also helped them uncover important legal precedents and arguments that they might have otherwise missed. With Azure Cognitive Search, they could quickly build strong cases and provide
Hanh: 00:11:33
better legal advice to their clients. Azure Cognitive Search is a powerful tool that can revolutionize the way legal professionals search and retrieve documents. By leveraging advanced techniques like natural language processing and semantic understanding, it helps you find the most relevant information quickly and efficiently, saving you time and effort in
Hanh: 00:11:54
your legal research and case preparation. Let's shift gears and talk about Azure Cosmos DB, a globally distributed multi model database service that offers scalable and secure storage for your legal documents. In the legal industry, data security and compliance are of utmost importance. You need a reliable and robust storage solution that can handle the sensitive
Hanh: 00:12:29
nature of legal documents while providing fast and efficient access. Azure Cosmos DB ticks all those boxes and more. It's designed to scale seamlessly across multiple regions, ensuring high availability and low latency for your document storage needs. Whether you're dealing with a small law firm or a global legal enterprise, Cosmos
Hanh: 00:12:53
DB can handle the scale and complexity of your document management requirements. But what really sets Cosmos DB apart is its strong focus on security and compliance. It offers multiple layers of data protection, including encryption at rest and in transit, role based access control, and multi factor authentication. www.
Hanh: 00:13:16
cosmosdb. com This means you can store your legal documents with confidence, knowing that they are secure and compliant with industry regulations, such as GDPR and HIPAA. Cosmos DB provides flexible data modeling options, allowing you to store and query your documents in a way that makes sense for your legal workflows.
Hanh: 00:13:38
You can use the document database model for unstructured data, such as case files and legal opinions, or the key value model for fast lookup of specific documents. Moving on, let's explore how Azure Functions can help you automate various document processing tasks in your legal workflows. Azure Functions is a serverless compute service that allows you
Hanh: 00:14:07
to run code without worrying about the underlying infrastructure. It's a powerful tool for automating repetitive tasks and integrating different services and applications. Think of Azure Functions as a highly efficient personal assistant that can take care of mundane and time consuming document processing tasks, freeing you up to focus on
Hanh: 00:14:27
more strategic and high value work. One of the key use cases for Azure Functions in legal document processing is document classification and routing. Imagine you receive a constant stream of incoming documents, such as contracts, case files, and client correspondence. Manually sorting and distributing these documents to the appropriate teams. or individuals can be a tedious
Hanh: 00:14:54
and error prone process. With Azure Functions, you can automate this task by writing a simple piece of code that analyzes the content and metadata of each incoming document and automatically routes it to the correct recipient based on predefined rules. For example, let's say you want to automatically classify and route contracts based on their type and value.
Hanh: 00:15:24
You can create an Azure function that examines the text of each contract, extracts relevant information like the contract type and dollar amount, and then applies business logic to determine the appropriate routing. If it's a high value contract over a certain threshold, the function can automatically send it to the senior legal team for review.
Hanh: 00:15:48
If it's a standard non disclosure agreement, it can be routed directly to the contract administration team for processing. This automation saves manual effort, reduces the risk of misclassification, and ensures that documents are promptly handled by the right people. Another powerful application of Azure Functions is data
Hanh: 00:16:13
extraction and validation. Legal documents often contain critical information that needs to be extracted and validated against predefined rules or external data sources. Thanks. Azure Functions can automate this process, saving you time and reducing the risk of errors. Let's consider an example.
Hanh: 00:16:35
A legal firm that handles real estate transactions needs to extract key information from property sale agreements, such as the property address, sale price, and closing date. They also need to validate this information against external databases to ensure accuracy and compliance. Azure With Azure Functions, they can create a workflow that
Hanh: 00:16:58
automatically extracts the relevant data from the sale agreements using techniques like regular expressions. or natural language processing. The extracted data can then be validated against property records, tax databases, and other relevant sources. If any discrepancies or red flags are detected, the Azure function can trigger alerts or notifications
Hanh: 00:17:20
to the appropriate team members for further review and action. This automation not only saves time, but also helps ensure the accuracy and integrity of the data, reducing the risk of costly errors or compliance issues. Microsoft Mechanics Azure Functions can also be used to automate document generation and assembly. In many legal scenarios, you need
Hanh: 00:17:42
to create standardized documents like contracts, agreements, or legal notices based on predefined templates and input data. For instance, let's say you need to, need to generate employment contracts for new hires. Instead of manually filling out the same template each time, you can create an Azure function that takes the employee's
Hanh: 00:18:04
information, name, position, salary, etc., as input and automatically generates the customized employment contract based on a predefined template. The Azure Function can populate the template with the relevant data, apply any necessary formatting or branding, and then generate the final document in the desired format, PDF, Word, etc. This automation saves
Hanh: 00:18:33
significant time and effort. ensures consistency across documents, and reduces the risk of errors or omissions. In addition to these use cases, Azure Functions can be integrated with other legal software and services to create end to end automation workflows. For example, you can use Azure Functions to automatically trigger e discovery processes, initiate
Hanh: 00:18:57
legal holds, or send notifications to relevant parties and parties. based on specific events or document changes. To sum up, Azure Functions is a versatile and powerful tool for automating legal document processing workflows. By leveraging its capabilities for document classification, data extraction, validation, and
Hanh: 00:19:20
generation, you can streamline your processes, reduce manual effort, and ensure accuracy and compliance. Whether you're a solo practitioner or part of a large legal organization, Azure Functions can help you work smarter, enabling you to focus on providing high quality legal services to your clients. As we've seen, intelligent document processing powered by Azure AI is
Hanh: 00:19:55
already transforming the legal industry. But what does the future hold? Let's explore some of the emerging trends and innovations. That are shaping the future of legal document processing. One exciting development is the increasing adoption of AI powered contract review and analysis tools. These tools can automatically
Hanh: 00:20:16
scan and analyze contracts, identifying key clauses, potential risks, and areas for negotiation. This can greatly speed up the contract review process and help legal professionals make more informed decisions. Blockchain technology is also making its way into legal document processing. With its ability to provide
Hanh: 00:20:37
secure, tamper proof storage and verification of documents, blockchain can revolutionize the way legal agreements and contracts are handled. It can enable secure document sharing and collaboration across multiple parties, reducing the risk of fraud and increasing transparency. The potential impact of these innovations on the legal industry is significant.
Hanh: 00:21:03
They can transform traditional legal processes, making them more efficient, accurate, and cost effective. They can enable new business models and service offerings, such as AI assisted legal advice or smart contract automation. And they can enhance access to legal services by reducing costs and increasing speed and convenience for clients. However, there are also challenges
Hanh: 00:21:29
and considerations to keep in mind. Data privacy and security concerns are paramount when dealing with sensitive legal information. There are ethical and regulatory implications to consider, such as the need for explainable AI and the potential for bias in algorithmic decision making. And there is the challenge of change management and user adoption
Hanh: 00:21:58
as legal professionals adapt to new technologies and workflows. Now that we've explored the exciting world of intelligent document processing in the legal industry, I want to leave you with a few calls to action. First, I encourage you to assess your current document processing challenges. Take a close look at your workflows and identify areas where manual processes are
Hanh: 00:22:28
slowing you down or introducing errors. Consider how Azure AI services like Form Recognizer, Cognitive Search, and Cosmos DB could help streamline and automate those processes. If you have questions or want to learn more, I invite you to reach out to me via email or social media. I'm always happy to discuss how Azure AI can benefit legal professionals
Hanh: 00:22:53
and share additional resources. As we come to the end of today's episode, let's recap the key benefits and applications of intelligent document processing in the legal industry. We've seen how Azure Form Recognizer can automate data extraction, reducing manual effort, We've explored how Azure Cognitive Search can enhance document retrieval, enabling faster
Hanh: 00:23:24
and more relevant search results. We've discovered the scalability and security benefits of Azure Cosmos DB for storing legal documents. And we've learned how Azure Functions can automate various document processing tasks. Streamlining workflows and improving efficiency. But beyond these specific services,
Hanh: 00:23:46
the broader message is clear. Embracing AI technology is crucial for the future of the legal industry. As client expectations evolve and the volume of legal data continues to grow, intelligent document processing will become increasingly essential for staying competitive and delivering high quality legal services. So, I encourage you to take action.
Hanh: 00:24:12
Start exploring how Azure AI can transform your legal document processing workflows. Embrace the opportunities for innovation and efficiency that these technologies offer, and stay tuned for future episodes. Where we'll dive even deeper into the exciting world of AI and its impact on the legal industry. Thank you for joining me today. Until next time, keep
Hanh: 00:24:37
innovating and stay curious.
Narrator: 00:24:45
Wrapping up today's episode of AI50 Connect, we've discussed through the world of AI as it applies to legal services, seeing firsthand how it's changing the landscape. We've discussed how AI tools like Azure services are not just new gadgets, but key players in redefining how legal documents are processed, making businesses more efficient and informed.
Narrator: 00:25:08
AI50 isn't just about talking tech. It's about providing real world solutions and strategies that align with the goals and aspirations of businesses, especially in the legal sector. If you're curious about what AI can do for your legal practice, AI50 is your go to resource. Stay connected with us for more insights and stories that show the real power
Narrator: 00:25:30
of AI in the professional world. Don't hesitate to reach out for a deeper discussion on how AI can be part of your business journey. Together, let's pave the way for a future where AI and legal expertise merge to create unprecedented value and opportunities. And if you found today's discussion enlightening, please take a
Narrator: 00:25:51
moment to leave us a review. Your feedback helps us improve and continue bringing valuable insights into the world of AI.
Hanh: 00:00:05
The seamless integration of these Azure cognitive services allows you to build chatbots that are not only conversational, but also intelligent, context aware, and user centric. As you develop your chatbot, consider how you can leverage LUIS to improve intent recognition and entity extraction, enabling more natural and meaningful interactions with your users.
Narrator: 00:00:35
Welcome to AI50 Connect, where we transform your understanding of AI's role in business. In this episode, chatbot revolution in customer support with Azure AI. Hanh Brown will navigate us through the innovative landscape of customer support, now redefined by intelligent chatbots powered by Azure. As we delve into this episode,
Narrator: 00:00:55
you'll gain not just insights, but practical solutions that promise to revolutionize your customer experience and streamline your support operations. Hanh's journey and expertise will shed light on the significant strides Azure has made in enhancing customer interactions, ensuring you leave with actionable strategies to implement in your own business.
Hanh: 00:01:24
Welcome to AI50 Connect, your go to podcast for practical AI insights. I'm your host, Hanh Brown. Today, we're exploring a game changing topic in customer support. Intelligent chatbots powered by Azure. Get ready to discover how you can revolutionize your customer experience and streamline support operations. This episode perfectly aligns with
Hanh: 00:01:48
our mission to empower businesses with cutting edge AI technology. A few years ago, I had a frustrating customer support experience that left me feeling unheard. I was stuck in an endless loop of generic responses. Yearning for a better solution? That's when I realized the immense potential of intelligent chatbots
Hanh: 00:02:15
to transform customer support. In today's fast paced digital world, customers crave instant, personalized attention, and businesses face the challenge of delivering it. Intelligent chatbots powered by Azure offer a game changing solution to this common pain point. By the end of this episode, you'll have a clear roadmap for leveraging Azure
Hanh: 00:02:40
to build chatbots that deliver value. We'll explore the key components, best practices, and real world examples that showcase the power of intelligent chatbots. As we go along, I invite you to reflect on your own customer support challenges. How could intelligent chatbots help you provide better experiences and optimize your support operations?
Hanh: 00:03:06
Keep that question in mind as we embark on this exciting journey together. Let's take a quick look at what we'll cover in today's episode. First, we'll define intelligent chatbots and explore their role in transforming customer support. Then we'll dive into Azure Bot Service, the foundation for building and deploying chatbots.
Hanh: 00:03:37
I've done extensive research and can't wait to share some surprising insights with you. Did you know that chatbots can handle up to 80 percent of routine customer inquiries? That's just the tip of the iceberg when it comes to their potential impact. Think of this episode as a journey, starting with the basics, and
Hanh: 00:03:59
leading to a comprehensive roadmap. By the end, you'll have the knowledge and tools to create your own intelligent chatbots. Before we dive in, let me ask you a question. Have you ever been frustrated by generic, unhelpful responses when seeking customer support? If you've ever felt stuck in
Hanh: 00:04:20
an endless loop of automated messages, you're not alone. Now imagine a world where you can get instant personalized support 24 seven, a world where your unique needs are understood and addressed promptly without the wait. That's the power of intelligent chatbots, and it's more attainable than you might think.
Hanh: 00:04:46
With Azure's cutting edge AI technology, you can create chatbots that revolutionize your customer experience. So, if you're ready to say goodbye to frustrating support interactions and hello to efficiency, keep listening. This episode is your gateway to a new era of customer support. Excellent. Now that we've set the stage and
Hanh: 00:05:15
explored the potential of intelligent chatbots, let's dive deeper into the key components and best practices that make them truly transformative. Intelligent chatbots are AI powered virtual assistants. that understand and respond to customer inquiries using natural language. They provide instant, personalized support 24 7, reducing wait times,
Hanh: 00:05:42
and increasing customer satisfaction. Imagine a customer who needs assistance with a product late at night. With an intelligent chatbot, they can get immediate help, even outside of regular business hours. Chatbots can handle a wide range of tasks, from answering FAQs to processing orders and providing recommendations. By automating routine inquiries, chatbots
Hanh: 00:06:07
free up human agents to focus on more complex, high value interactions. This optimization of support resources leads to improved efficiency and cost savings for businesses. Chatbots can provide a consistent on brand experience across all customer touchpoints. No matter how a customer chooses to interact with your business, they'll
Hanh: 00:06:33
receive the same level of support. So whether it's a quick question or a multi step process, intelligent chatbots have you covered. Building upon the foundation of Azure Bot Service, let's explore how other Azure services can help you get started. such as Cognitive Services and Cosmos DB can further enhance your chatbot's capabilities.
Hanh: 00:07:03
Azure Bot Service is a fully managed platform that empowers you to build and deploy intelligent chatbots with ease, revolutionizing the way businesses interact with their customers. It offers a comprehensive set of tools and templates to streamline the development process with their customers. Making it accessible to developers of all skill levels.
Hanh: 00:07:27
With Azure Bot Service, you can create chatbots that seamlessly integrate with websites, social media, and popular messaging apps like Microsoft Teams, Slack, and Facebook Messenger. This multi channel approach ensures that you can engage with customers on their preferred platforms. Meeting them where they are most comfortable.
Hanh: 00:07:50
Imagine a customer named Sarah, who reaches out to your business on Facebook Messenger with a question about your product's features. With a chatbot built on Azure Bot Service, Sarah can receive instant personalized assistance right within the messaging interface, without having to navigate to a separate website or wait for an email response.
Hanh: 00:08:13
The chatbot can greet Sarah by name. Understand her specific question using natural language processing, and provide a tailored response based on your product's information. This seamless interaction creates a positive customer experience, making Sarah feel valued and valued. One of the key advantages of Azure Bot Service is its seamless integration
Hanh: 00:08:40
with other powerful Azure services, such as Cognitive Services and Cosmos DB. By leveraging Cognitive Services, particularly language understanding, at Lewis, your chatbot can be trained to understand and interpret user intents and entities accurately. For example, if a customer asks, What's the status of myOrder hash 12, 345? LUIS can help your chatbot
Hanh: 00:09:11
understand that the intent is to check the order status and the entity is the specific order number. This natural language understanding capability enables your chatbot to provide more accurate and relevant responses, enhancing the user experience. By integrating with Cosmos DB, a globally distributed NoSQL database, Cosmos Your chatbot can store and
Hanh: 00:09:35
retrieve data efficiently, ensuring quick response times and scalability. Let's say you have a customer named John who wants to track the status of his recent order. By integrating your chatbot with your order management system, using Cosmos DB, the chatbot can retrieve real time information about John's specific order and provide him
Hanh: 00:10:00
with up to date status updates. This integration allows for a seamless and personalized experience, making John feel informed and valued as a customer. Azure Bot Service also offers built in analytics and monitoring capabilities to help you optimize your chatbot's performance and make data driven improvements. You can track key metrics, such
Hanh: 00:10:25
as user engagement, conversation flow, and common user queries. Gaining valuable insights into how your customers interact with your chatbot. For instance, if you notice that a significant number of users are asking about your return policy, you can update your chatbot's knowledge base to provide clearer information on this topic proactively.
Hanh: 00:10:51
By continuously monitoring and refining your chatbot based on real user data, you can ensure that it remains effective and relevant over time. Another powerful feature of Azure Bot Service is its ability to handle multiple conversations simultaneously, enabling you to scale your customer support efficiently. Whether you have a small business
Hanh: 00:11:14
with a handful of customers or a large enterprise serving millions, your chatbot can handle the load without compromising on the quality of service. This scalability is particularly valuable during peak seasons or promotional campaigns. When customer inquiries may surge, for example, during Black Friday sales, your chatbot can handle a high
Hanh: 00:11:36
volume of customer questions related to product availability, pricing, and shipping times, providing instant support, and reducing the workload on your human customer service team. By leveraging Azure Bot Services scalability, you can ensure that your customers receive timely assistance. Even during the busiest period, maintaining a positive brand experience.
Hanh: 00:12:10
In summary, Azure Bot Service is a game changer for businesses looking to enhance their customer support and engagement through intelligent chatbots. With its user friendly development tools, seamless integration capabilities, and powerful analytics, Azure Bot Service empowers you to create chatbots that are not only conversational, but also highly effective and scalable.
Hanh: 00:12:37
By providing instant, personalized support across multiple channels, your chatbot can improve customer satisfaction, reduce response times, and free up your human agents to focus on more complex tasks. As you embark on your chatbot journey with Azure Bot Service, keep the customer experience at the forefront. Leverage the power of integration and continuously monitor and refine
Hanh: 00:13:03
your chatbot based on real user data. With these best practices in mind, you can unleash the full potential of Azure Bot Service and revolutionize the way you engage with your customers. As we continue our exploration of Azure's AI ecosystem, let's turn our attention to two powerful tools that can take your chatbots to Natural Language, Understanding, to the next level.
Hanh: 00:13:35
Language, Understanding, LUIS, and Q& A Maker. Azure Cognitive Services are a powerful suite of AI services that enable chatbots to understand and interact with users naturally, enhancing the overall conversational experience. Among the wide range of services offered, two key components stand out for their integral role in chatbot development.
Hanh: 00:13:59
for listening. Language, Understanding, LUIS, and Q& A Maker. LUIS is a game changing tool that empowers your chatbot to understand user intent and extract relevant information from their messages, enabling more contextual and meaningful interactions. By defining intents and entities within LUIS, you can create a chatbot that
Hanh: 00:14:24
can accurately interpret and respond to a wide range of user queries, even when expressed in different ways. Imagine a customer named Emily, who is having trouble logging into her account on your website. She asks your chatbot, Can you help me reset my password? I can't seem to log in. With a well trained LUIS model, your
Hanh: 00:14:47
chatbot can understand that the primary intent behind Emily's message is to seek assistance with resetting her password. The chatbot can then initiate a guided process to help Emily reset her password securely, providing step by step instructions and reassurance throughout the interaction. This level of understanding and a context aware response helps create
Hanh: 00:15:16
a more human like and empathetic conversational experience, making Emily feel supported and valued as a customer. Training a LUIS model involves providing sample utterances for each intent and labeling relevant entities within those utterances. For example, to train your chatbot to handle password reset requests, You would provide various sample phrases
Hanh: 00:15:39
that users might use to express this intent, such as, I forgot my password. I need to change my password. Can you help me reset my login credentials? By exposing your LUIS model to a diverse range of utterances, you can improve its ability to accurately recognize user intent, even when expressed in different ways.
Hanh: 00:16:06
Azure provides an intuitive and user friendly interface for training LUIS models, making it accessible to both developers and non technical users alike. The platform offers features like active learning and pre built domains, which can accelerate the training process. and improve the model's performance over time. On the other hand, QnA Maker is a
Hanh: 00:16:29
powerful service that enables you to create a comprehensive knowledge base of questions and answers, perfect for building chatbots that can handle frequently asked questions, FAQs, or provide information on specific topics. With QnA Maker, you can easily create a repository of question answer pairs that your chatbot can draw upon to provide instant,
Hanh: 00:16:56
accurate responses to user inquiries. Let's say you have an e commerce store that sells clothing and accessories. A common question that customers might ask is, what is your return policy? Using Q& A Maker, you can create a question answer pair that addresses this specific inquiry, providing clear and concise information about your store's return policy.
Hanh: 00:17:27
For example, you might create an answer that states, We accept returns within 30 days of purchase as long as the item is in its original condition and accompanied by a valid receipt. Please visit our returns page for more detailed information. By having this information readily available in your chatbot's knowledge base, you can provide instant, accurate
Hanh: 00:17:48
answers to customer questions, reducing the need for human intervention and improving the overall user experience. One of the most powerful features of QnA Maker is its ability to import existing FAQs, product manuals, or other relevant documents, automatically extracting question answer pairs, and creating a comprehensive knowledge base. This feature saves you significant
Hanh: 00:18:14
time and effort in curating content. for your chatbot, ensuring that it has access to a wide range of information to assist users effectively. For instance, if you have an extensive FAQ section on your website, you can easily import that content into QnA Maker, and the service will automatically identify and extract the relevant question answer pairs.
Hanh: 00:18:43
This not only streamlines the knowledge based creation process, but also ensures consistency between the information provided by your chatbot and other customer support channels. By leveraging the power of LUIS and QnA Maker, you can create chatbots that truly understand and respond to a wide range of customer needs, from handling complex queries to providing quick,
Hanh: 00:19:06
accurate answers to common questions. The seamless integration of these Azure Cognitive Services allows you to build chatbots that are not only conversational, but also intelligent, context aware, and user centric. As you develop your chatbot, consider how you can leverage LUIS to improve intent recognition and entity extraction. enabling more natural and meaningful
Hanh: 00:19:33
interactions with your users. Similarly, explore how QnA Maker can help you create a comprehensive and easily maintainable knowledge base, ensuring that your chatbot has access to the information it needs. to provide reliable and efficient support to your customers. By harnessing the power of Azure Cognitive Services, you can
Hanh: 00:19:57
elevate your chatbot's capabilities and deliver a truly exceptional conversational experience that sets your brand apart from the competition. With a solid understanding of how Azure Bot Service and cognitive services can elevate your chatbot. Let's now explore the role of Azure Cosmos DB in storing and managing your chatbot's data efficiently.
Hanh: 00:20:28
Azure Cosmos EDB is a globally distributed, multi model database service that offers unparalleled scalability and low latency. It's an ideal choice for storing and retrieving chatbot data in real time. With Cosmos DB, you can store user profiles, conversation history, and other chatbot related data in a flexible, schema less format.
Hanh: 00:20:53
This allows your chatbot to provide personalized responses based on the user's context in previous interactions. Imagine a customer who has interacted with your chatbot before. and has shared their preferences. By storing this information in Cosmos DB, your chatbot can tailor its responses and recommendations to that specific user. Cosmos DB's automatic scaling and
Hanh: 00:21:16
multi region replication ensure that your chatbot can handle high traffic loads with ease. No matter how many users are interacting with your chatbot simultaneously, Cosmos DB can scale to meet the demand. This means that your customers will always experience fast, responsive conversations without any lag or downtime. Cosmos DB's global distribution
Hanh: 00:21:41
capabilities allow your chatbot to serve users from multiple regions with low latency. So whether your customers are in New York or London, they'll receive the same, seamless experience. By leveraging Cosmos DB, you can create chatbots that are not only intelligent, but also highly performant and scalable. You can focus on crafting
Hanh: 00:22:04
engaging conversations. While Cosmos DB takes care of the underlying data management. With its flexible data model and powerful querying capabilities, Cosmos DB opens up a world of possibilities for your chatbot. You can store and retrieve data in real time, enabling your chatbot to provide up to date information and personalized experiences.
Hanh: 00:22:31
So, whether you're building a simple FAQ bot or a complex virtual assistant, Cosmos DB has you covered. To further extend your chatbot's functionality and enable seamless integrations, Azure Functions offers a serverless compute solution that can revolutionize the way your chatbot interacts with external services and systems.
Hanh: 00:22:59
Azure Functions is a serverless compute service that allows you to run code without managing infrastructure. It's perfect for implementing custom logic and integrations for your chatbots. With Azure Functions, you can write small pieces of code, called functions, that execute in response to specific events or triggers. This means you can extend your
Hanh: 00:23:20
chatbot's capabilities without the need for complex infrastructure setup. Imagine a scenario where your chatbot needs to retrieve data from an external API based on user input. With Azure Functions, you can create a function that is triggered whenever a specific question is asked. The function can then make the necessary API call, process the response, and send
Hanh: 00:23:49
the information back to the chatbot. This seamless integration allows your chatbot to provide real time, dynamic responses to user queries. Azure Functions supports a wide range of programming languages, including C JavaScript, and Python. This flexibility allows you to choose the language that best suits your skills and project requirements.
Hanh: 00:24:11
You can also leverage pre built templates and bindings to accelerate your development process. For example, let's say you want to send a personalized email to a customer after a chatbot interaction. Azure With Azure Functions, you can create a function that is triggered by the chatbot conversation's completion. The function can then compose and
Hanh: 00:24:31
send the email, using a pre built email binding, making the process efficient and straightforward. Another powerful feature of Azure Functions is its ability to scale automatically based on demand. As your chatbot receives more interactions, Azure Functions can scale up to handle the increased load without any manual intervention.
Hanh: 00:24:57
This means that your chatbot can handle sudden spikes in traffic without compromising performance or reliability. By leveraging Azure Functions, you can create chatbots that are not only intelligent, But also highly extensible and scalable. You can focus on building engaging conversations and custom logic while Azure Functions takes care
Hanh: 00:25:19
of the underlying infrastructure. With its event driven architecture and seamless integration capabilities, Azure Functions opens up a world of possibilities for your chatbots. You can create powerful integrations, automate tasks and extend your chatbots functionality with ease. So whether you're building a simple FAQ bot or a complex virtual assistant,
Hanh: 00:25:46
Azure Functions has you covered. As we near the end of our technical deep dive, let's take a moment to consider the best practices and key considerations that will ensure your chatbot delivers a truly exceptional user experience. Designing effective conversation flows is crucial for creating chatbots that provide a positive user experience. Start by mapping out the key scenarios
Hanh: 00:26:14
and user goals and ensure that your chatbot can handle them smoothly. For example, if your chatbot is designed to handle customer inquiries, consider the most common questions and create clear paths to resolution. Use a conversational tone and provide prompts to guide users towards successful outcomes. It's also important to handle fallback
Hanh: 00:26:36
scenarios gracefully when your chatbot doesn't understand a user's input. Provide clear guidance on how to rephrase the question or offer alternative options to keep the conversation moving forward. You can use phrases like, I'm sorry, I didn't quite understand that. Could you please rephrase your question? Or, it seems like I'm having trouble with your request, here are a few
Hanh: 00:27:04
other options that might help. Another best practice is to design your chatbot with a clear personality and tone that aligns with your brand. This helps create a consistent and engaging experience for users, making the interaction feel more natural and human like. Consider using friendly greetings, empathetic responses, and even a
Hanh: 00:27:25
touch of humor when appropriate. It's also crucial to regularly monitor and analyze your chatbot's performance to identify areas for improvement. Use analytics tools to track user interactions, identify common pain points, and optimize your chatbot's responses over time. For example, if you notice that users frequently ask a question
Hanh: 00:27:49
that your chatbot struggles to answer, you can update your knowledge base with analytics tools. or train your language model to better handle that specific query. Security and privacy considerations are paramount when building chatbots that handle sensitive customer data. Ensure that your chatbot complies with relevant regulations, such
Hanh: 00:28:10
as GDPR, and implement robust authentication and access controls. Be transparent about how user data is collected, stored, and used. and provide clear opt out mechanisms for users who wish to delete their data. Finally, remember that chatbots are not a replacement for human interaction, but rather a complement to it. Design your chatbot to seamlessly
Hanh: 00:28:34
escalate complex or sensitive issues to human agents when needed. By finding the right balance between automation and human touch, you can create a customer support experience. That is both efficient and empathetic. Implementing these best practices and considerations will help you build intelligent chatbots. That not only meet user expectations,
Hanh: 00:28:57
but also drive business value. By carefully designing your chatbot's conversation flows, personality, and security measures, you can create a powerful tool that enhances customer satisfaction and loyalty. So, keep these best practices in mind. As you embark on your chatbot development journey, and always prioritize the user experience above all else.
Hanh: 00:29:29
Now that we've explored the technical aspects of building intelligent chatbots with Azure, I'd like to share some personal insights and experiences from my own journey in this field. Building intelligent chatbots has been a transformative journey for me. Both professionally and personally, when I first started the complexity of natural language processing
Hanh: 00:29:50
seemed overwhelming and daunting. However, as I delved into Azure's AI services, I realized. The incredible power they bring to the table. Of course, the journey hasn't been without its challenges and learning moments. I remember spending hours debugging a misbehaving Louise model, only to realize I had forgotten to train it.
Hanh: 00:30:14
It was a humbling reminder of the importance of thorough testing and attention to detail. Through trial and error, I've learned that building successful chatbots requires a balance of technical skills and human empathy. It's not just about the code, but also about understanding the user's needs and crafting meaningful conversations.
Hanh: 00:30:37
So as you embark on your own chatbot journey, embrace the challenges as opportunities for growth and learning. With perseverance and a user centric mindset, you can create chatbots that truly make a difference. Before we move on, I'd like to take a moment to engage with you directly. And invite you to reflect on your own experiences with customer support and the
Hanh: 00:31:05
potential impact of intelligent chatbots. Think back to a recent customer support experience. That left you feeling frustrated or unsatisfied. Maybe it was a long wait time, a generic response, or an unresolved issue. Take a moment to reflect on that interaction and how it made you feel. Now imagine if that same interaction
Hanh: 00:31:28
had been with an intelligent chatbot powered by Azure. How might the experience have been different? Would you have received faster, more personalized assistance? Think about it. Would your issue have been resolved more efficiently, leaving you with a positive impression of the company?
Hanh: 00:31:49
I invite you to pause the episode for a moment and really visualize that scenario. Consider the potential impact that intelligent chatbots could have on your own customer support challenges. How could they help you provide better experiences? Reduce wait times and increase customer satisfaction. As you reflect on these questions,
Hanh: 00:32:11
remember that the power to transform your customer support lies within your reach. With Azure's AI services and the right approach, you can create chatbots that exceed customer expectations and drive business value. So, keep those thoughts in mind as we continue our exploration of intelligent chatbots. Your insights and experiences are
Hanh: 00:32:34
valuable guides on this journey towards exceptional customer support. As we near the end of our discussion, let's address some common questions and concerns that you might have. About implementing chatbots in your own business. At this point, you might be wondering, can chatbots really handle complex customer issues effectively?
Hanh: 00:33:03
It's a valid concern, and one that many businesses grapple with when considering chatbot implementations. While chatbots excel at handling routine inquiries and providing instant assistance, they may struggle with more nuanced or emotionally charged issues. That's why it's crucial to design your chatbot with clear escalation paths to human agents when needed.
Hanh: 00:33:30
By seamlessly transferring complex cases to trained support staff, You can ensure that customers receive the level of assistance they require. Another common question is how to strike the right balance between automation and human interaction. The key is to identify the strengths of chatbots and human agents and leverage them accordingly.
Hanh: 00:33:52
Chatbots can handle high volume, repetitive tasks. Freeing up human agents to focus on more complex, high value interactions. By finding that sweet spot, you can create a support system that is both efficient and empathetic. If you have any other questions about implementing chatbots in your business, I'm here to help.
Hanh: 00:34:13
Feel free to reach out to me and I'll be happy to provide guidance and resources. Remember the path to successful chatbot implementation is paved with careful planning. User-centric design and a commitment to continuous improvement. Now, I'd like to shift gears and invite you, the listener to actively participate in the conversation.
Hanh: 00:34:43
Your experiences and insights are invaluable in shaping the future of intelligent Chat bot. Whether you've interacted with them as a customer or implemented them in your own business, your insights are valuable. What have been your biggest challenges or success stories when it comes to chatbots? Have you encountered any particularly memorable or
Hanh: 00:35:07
impactful chatbot experiences? I invite you to share your stories and perspectives with me on LinkedIn. I believe that by sharing our experiences and learning from one another, we can collectively push the boundaries of what's possible with chatbots. Your feedback and insights can help shape the future of customer support and drive innovation in this exciting field.
Hanh: 00:35:30
If you're ready to take your chatbot journey to the next level, I have an exclusive offer for you. As a listener of AI50 Connect, you can reach out to our team for a free consultation on how to integrate chatbots into your business. Our team of experts will work with To understand your unique needs and provide tailored recommendations.
Hanh: 00:35:54
We'll guide you through the process of leveraging Azure's AI services to build chatbots that drive real business value. Mention the code AI50 Connect to unlock your free consultation. Don't miss this opportunity to transform your customer support and stay ahead of the curve. As we wrap up today's episode, let's recap the key insights we've covered.
Hanh: 00:36:25
First, we explored how intelligent chatbots powered by Azure can revolutionize customer support by providing instant, personalized assistance. We delved into the capabilities of Azure Bot Service, Cognitive Services, and Cosmos DB, and how they streamline chatbot development and deployment. We also discussed best practices
Hanh: 00:36:47
for designing effective conversation flows, handling fallback scenarios, and ensuring security and privacy. But perhaps the most important takeaway is that chatbots are not meant to replace human interaction, but rather to enhance it. By automating routine tasks and providing 24 7 support, chatbots free up human agents to focus
Hanh: 00:37:10
on high value, complex issues. The key is to find the right balance between automation and human touch. Creating a support system that is both efficient and empathetic. As you embark on your own chatbot journey, remember to keep the user experience at the forefront. Design your chatbots with empathy, clarity, and a commitment to
Hanh: 00:37:37
continuous improvement by doing so. You can create chatbots that not only meet customer expectations, but exceed them, driving satisfaction and loyalty. Before we conclude, I want to express my heartfelt gratitude for joining me on this deep dive into intelligent chatbots. Your presence and engagement mean the world to me. And I'm honored to be a part
Hanh: 00:38:07
of your learning journey. I hope this episode has provided you with valuable insights and practical tips to transform your customer support. If you found this content helpful, I'd love to hear your thoughts and feedback. Please take a moment to leave a review on Apple podcasts or wherever you're listening. Your support helps me create
Hanh: 00:38:29
more engaging and informative content that makes a difference. Remember, the power to revolutionize your customer support is within your reach. With Azure's AI services and a user centric mindset, you can build chatbots that delight your customers and drive business growth. Until next time, stay curious, stay innovative, and keep pushing
Hanh: 00:38:55
the boundaries of what's possible. This is Hanh Brown signing off.
Narrator: 00:39:04
As we conclude our enriching journey on AI50 Connect, we've transcended the basics to uncover the profound impact of intelligent chatbots on customer support. Guided by Hanh Brown's expert insights and real world experiences, we've explored how Azure's AI technology is not just changing, but elevating the customer service paradigm.
Narrator: 00:39:26
This episode has not only been about discovery, But also empowerment, equipping you with the knowledge and tools to transform your customer interactions. If today's exploration has ignited a spark of curiosity or ambition in you, we encourage you to delve deeper, reach out, and engage with us on this transformative path. Your journey towards customer
Narrator: 00:39:47
service excellence is just beginning. And we're here to support each step. Don't forget to share your thoughts and leave us a review, as your feedback is a cornerstone of our continuous journey into the innovative world of AI and business.
Hanh: 00:00:05
Picture this. You have a never ending to do list with tasks ranging from booking appointments to filling out forms and managing customer inquiries. It's like juggling a dozen balls while trying to keep your business running smoothly. But what if you had a personal assistant that could handle all these tasks for
Hanh: 00:00:25
you without ever taking a coffee break?
Narrator: 00:00:33
Welcome to AI 50 Connect. The podcast that explores the latest trends and innovations in artificial intelligence. In this episode, AI Trends 2024, Realistic Expectations, Multimodal Capabilities, and Responsible Innovation. Host Hanh Brown takes us on a deep dive into the world of AI, separating the hype from reality and highlighting the
Narrator: 00:00:54
importance of ethical considerations. We will discuss the need for a reality check when it comes to AI tools like ChatGPT and DALI, emphasizing the importance of setting realistic expectations and understanding their limitations. We will explore the rise of multimodal AI, which combines various data types to create more
Narrator: 00:01:13
intuitive and natural interactions. Next, we will dive into the quest for smaller and more efficient AI models, the benefits of custom local solutions, and the power of virtual agents in automating tasks. We will also examine the impact of increased AI regulation and the legal battles surrounding the use of copyrighted data in training AI models.
Narrator: 00:01:36
Throughout the episode, Hanh underscores the importance of responsible AI use and the need for comprehensive corporate governance policies. Join us as we navigate the exciting and complex landscape of AI in 2024, with Hanh Brown as our guide. Hanh, let's get started.
Hanh: 00:01:59
Welcome to AI50 Connect. I am your host, Hanh Brown. Today's episode, AI Trends 2024, Realistic Expectations, Multimodal Capabilities, and Responsible Innovation, is all about getting real with AI. We're cutting through the hype, understanding what AI tools like ChatGPT really offer, and how they're evolving to be more than just novelties.
Hanh: 00:02:25
We'll dive into the rise of multi modal AI, which isn't just about text or images anymore. It's about AI that understands and integrates various data types, making our interactions more intuitive. And we can't ignore the big picture, the ethics and responsibility of using AI. It's about making sure these powerful tools benefit everyone.
Hanh: 00:02:52
Let's uncover what 2024 has in store for AI. With a keen eye on realistic expectations, the magic of multimodal capabilities, and the paramount importance of responsible innovation. Today, we're tackling a crucial topic, the reality check. In the past few years, we've seen an explosion of hype around
Hanh: 00:03:20
generative AI tools, like ChatGPT. These models can produce human like text, engage in conversations, and even create images from textual descriptions. It's like having a genie in a bottle, right? But as we move into 2024, the AI community is collectively taking a step back. We're moving past the initial excitement and hyperbolic headlines to develop
Hanh: 00:03:47
a more nuanced understanding of what these AI models can actually do, and more importantly, what they can't. You see, tools like ChatGPT are incredibly powerful, but they're not magic. They have limitations. They can make mistakes, produce bias or nonsensical outputs, and, and struggle with complex reasoning. As businesses and consumers, it's crucial
Hanh: 00:04:12
that we understand these limitations and set realistic expectations. That's where the trend of embedded AI comes in. Instead of positioning these models as standalone solutions, companies are integrating them into existing software and workflows. Microsoft's Copilot, for example, acts as an AI powered writing assistant in Word.
Hanh: 00:04:41
Adobe's Generative Fill uses AI to help users expand and edit images in Photoshop. By embedding AI in this way, we're setting the right expectations. These models become productivity aids, not replacements for human workers. They automate repetitive tasks, make intelligent suggestions, and enhance our capabilities. But they don't take over the whole job.
Hanh: 00:05:08
Think of it like the introduction of GPS navigation in cars. It's an incredibly helpful tool that suggests routes and provides real time updates. But it doesn't replace the need for a human driver. You're still in control, making decisions based on your judgment and experience. As we progress through 2024,
Hanh: 00:05:29
I predict we'll see more of this embedded AI approach. Companies will focus on seamlessly integrating AI into their products, positioning it as a co pilot rather than an autopilot. Users will grow accustomed to working alongside AI, leveraging in its strengths while understanding its weaknesses. Learn to harness its capabilities
Hanh: 00:05:54
to boost your productivity and creativity, but don't buy into the hype. That it will solve all your problems or replace human intelligence. I'm excited about the potential of these technologies, but I'm also a realist. By setting grounded expectations and focusing on integration, we can make the most of AI without getting carried away by the hype.
Hanh: 00:06:22
And speaking of potential, let's set the stage for our next segment. We'll be diving into the world of multimodal AI, exploring how models are learning to process and generate, not just text, but images, audio, and video. It's like having a Swiss army knife of AI capabilities. Remember, AI is a powerful tool, but it's not a silver bullet.
Hanh: 00:06:49
Approach it with a mix of enthusiasm and realism. You'll be well positioned to thrive in the AI driven world of 2024. Let's dive into the next big trend in AI for 2024. The rise of multimodal models, an AI that cannot only understand and generate text, but also process images, audio and video. It's like having a multi-talented
Hanh: 00:07:18
digital assistant that can handle any type of data you throw at it. Enter the world of multi modal AI. These advanced models are trained on multiple types of data, allowing them to seamlessly transition between different modes of communication. It's like having a superhero with multiple powers. Take GPT 4 and Google's
Hanh: 00:07:42
Gemini, for example. These cutting edge language models can analyze an image and answer questions about it using natural language. You could show them a picture of a cat and ask what color is the cat's fur, and they'd respond with ease. Imagine asking for instructions out loud and receiving not just a text response, but also synchronized
Hanh: 00:08:08
visual aids and step by step guidance. It's like having a personal tutor that adapts to your learning style. The magic behind multimodal AI lies in its ability to ingest and learn from diverse data sources. By training on videos, images, audio, and text, these models develop a more holistic understanding of the world. It's important to note that
Hanh: 00:08:36
developing multi modal AI comes with its own set of challenges. These models require extensive multi task training data, which can be difficult and expensive to obtain. It's like trying to find the perfect ingredients for a complex recipe. Despite the challenges, the potential of multi modal AI is truly exciting. It opens up new possibilities
Hanh: 00:09:00
for more natural and intuitive human machine interaction. Imagine having a conversation with an AI that can not only understand your words, but also pick up on your tone, facial expressions, and gestures. It's like having a digital companion that truly gets you. As we move through 2024, I predict we'll see more and more
Hanh: 00:09:25
applications of multimodal AI. From virtual assistants that can guide you through complex tasks, to educational tools that adapt to your learning preferences, The possibilities are endless, but as with any powerful technology, it's crucial that we approach multimodal AI with both enthusiasm and responsibility. We need to ensure that these models
Hanh: 00:09:48
are trained on diverse and unbiased data, and that they are used in ways that benefit society as a whole. I'm excited to see how multimodal AI will shape the future of human machine interaction. It's a thrilling time to be at the forefront of this technological revolution. The rise of multi modal AI
Hanh: 00:10:10
is just beginning, and we're in for an exhilarating ride. Get ready to experience the power of AI that can see, hear, and understand the world like never before. And speaking of power, our next segment, we'll dive into the fascinating world of smaller and more efficient AI models. We'll Believe it or not, sometimes less is more when it comes to AI,
Hanh: 00:10:38
but for now, let's marvel at the incredible potential of multimodal AI. It's a game changer that will redefine how we interact with technology and each other. Let's tackle the next big trend in AI for 2024, the quest for smaller and more efficient models. You've probably heard about the massive foundation models like GPT 4.
Hanh: 00:11:06
These behemoths are the giants of the AI world, boasting trillions of parameters. But with great size comes great energy consumption. Let's put it into perspective. Training a model like GPT 4 uses as much electricity as over 1, 000 households in a year. That's enough to power a small village and running daily queries on ChatGPT.
Hanh: 00:11:31
That can rival the energy usage of a staggering 33, 000 homes. It's like having a superpowered AI that requires its own dedicated power plant. Not exactly the most sustainable solution, right? But fear not, the industry is rising to the challenge and driving innovation in developing smaller, more parameter efficient models.
Hanh: 00:11:57
It's like putting AI on a diet and optimizing its performance. Take Mistral's Mixtrel, for example. This open source model boasts just 56 billion parameters, a fraction of GPT 3's size. But here's the kicker. It claims to deliver superior performance compared to its larger counterparts. Talk about punching above its weight.
Hanh: 00:12:25
The beauty of these smaller models lies in their versatility. They enable on device deployment, meaning you can run AI directly on your personal laptop or hardware. No more reliance on power hungry cloud services. It's like having a pocket sized AI assistant that's always ready to help. But the benefits don't stop there.
Hanh: 00:12:49
Smaller models also mean faster training times, reduced costs, and improved accessibility. It's a win win win situation. As we move through 2024, I predict we'll see a surge in the development and adoption of these compact, yet mighty AI models. Researchers and companies alike will focus on pushing the boundaries of efficiency
Hanh: 00:13:12
without sacrificing performance. It's an exciting time to be in the AI field, as we witness the shift from bigger is better to smaller is smarter. And as an AI enthusiast, I can't wait to see how these efficient models will revolutionize the way we interact with and deploy AI in our daily lives. But of course, the quest for efficiency doesn't end with smaller models.
Hanh: 00:13:40
In our next segment, we'll explore how the drive for optimization is influencing GPU and cloud costs. Spoiler alert, it's all about finding the right balance. For now, let's marvel at the incredible potential of these compact AI powerhouses. They may be small in size, but they're making a big impact in the world of artificial intelligence.
Hanh: 00:14:07
Keep your eyes peeled for the rise of smaller and more efficient AI models. They're proof that sometimes the best things come in small packages. So now, we're diving into a crucial topic, GPU and cloud cost considerations in the era of generative AI. As we've seen, large AI models like GPT 4 are the heavyweight champions of the AI world.
Hanh: 00:14:38
But with great power comes great cost, especially when it comes to GPU resources. Training and running, or tooling these models requires a significant amount of GPU horsepower, which drives up cloud computing expenses. It's like fueling a high performance race car. The faster you want to go, the more you have to spend on premium gas.
Hanh: 00:15:04
As the adoption of generative AI grows, cloud providers are feeling the heat. They're under pressure to invest in optimized GPU infrastructure to meet the soaring demand. But here's the catch. GPUs are in short supply, and that scarcity comes with a hefty price tag. It's a classic case of supply and demand. As more businesses jump on
Hanh: 00:15:28
the AI bandwagon, the cost of GPU resources skyrockets. And guess who bears the brunt of those increased operating costs? The AI industry is adapting to these challenges by focusing on smaller, more efficient models. It's like downsizing from a gas guzzling SUV to a sleek, eco friendly hybrid. By developing models that require
Hanh: 00:15:53
fewer parameters and less computational power, businesses can manage the rising cloud and infrastructure expenses. It's a necessity in the face of escalating costs and limited GPU availability. But the benefits of this trend go beyond just saving money. Smaller, efficient models also enable faster deployment, improve scalability, and reduce environmental impact.
Hanh: 00:16:22
It's a win win situation for both the bottom line and the planet. As we navigate through 2024, I predict we'll see a growing emphasis on cost optimization in the AI realm. Companies will seek out innovative solutions to maximize performance while minimizing expenses. It's like finding the perfect balance between power and efficiency.
Hanh: 00:16:45
And that's where techniques like quantization, pruning, and model compression come into play. These approaches allow us to streamline AI models without sacrificing too much in terms of accuracy. It's like putting your model on a lean, mean, cost cutting machine. But the quest for cost efficiency doesn't stop there.
Hanh: 00:17:06
In our next segment, we'll explore how businesses are taking control of their AI destiny by embracing custom, local models. Get ready to discover the power of bringing AI in house. For now, let's applaud the AI community for rising to the challenge of GPU and cloud cost considerations. By prioritizing efficiency and optimization, we're paving the way for a
Hanh: 00:17:31
more sustainable and accessible AI future. So my fellow cost conscious AI enthusiasts, keep a watchful eye on the evolving landscape of GPU and cloud expenses. And remember, sometimes the smartest solutions come in smaller, more efficient packages. Let's talk about the next big thing in 2024.
Hanh: 00:17:59
The exciting world of model optimization techniques. Now, I know what you might be thinking. Optimization, isn't that just a fancy word for making things more complicated? These techniques are actually designed to simplify and streamline AI models, making them more efficient and cost effective for your business. Let's start with quantization.
Hanh: 00:18:25
Imagine you have a huge spreadsheet full of numbers, but you only need a rough estimate of the values. Quantization is like rounding off those numbers to the nearest whole digit. It reduces the memory needed to store the data without losing too much accuracy. It's like compressing a high resolution image into a smaller file size. You still get the essential
Hanh: 00:18:48
information, but it takes up less space. Next up, we have low rank adaptation or Laura for short. Think of it as a shortcut for fine tuning, large AI models. Instead of updating every single parameter, which can be time consuming and resource intensive. Laura focuses on a smaller subset of important weights.
Hanh: 00:19:16
It's like having a personal trainer who targets specific muscle groups instead of making you do a full body workout every session with Laura. You can quickly adapt a pre trained model to your specific business needs without breaking the bank. Now, let's talk about mixture of experts or MOE models. Imagine you have a team of specialists,
Hanh: 00:19:38
each with their own area of expertise. A MOE model works similarly by incorporating multiple sub networks that specialize in different tasks. It's like having a marketing expert, a financial analyst, and a customer service guru all working together to solve a complex business problem. By leveraging the strengths of each specialist, MOWI models can tackle
Hanh: 00:20:08
diverse tasks that More efficiently than a single generic model. Researchers are constantly exploring new techniques to get the most bang for your buck in terms of model performance. Pruning is like decluttering your AI model, removing unnecessary connections and parameters. Sparsity is like putting your model on a diet, focusing on the most important
Hanh: 00:20:35
information and discarding the rest. It's all about finding the right balance between efficiency and effectiveness. So, why should you care about these optimization techniques as a business owner? Well, for starters, they can help you save money on computational resources and storage costs. By making your AI models leaner and
Hanh: 00:20:53
meaner, you can reduce your reliance on expensive hardware and cloud services. Plus, optimized models tend to run faster and respond more quickly to user queries Leading to a better customer experience, but perhaps most importantly, these techniques democratize AI, making it more accessible to businesses of all sizes. You don't need a massive budget or a team of PhDs to leverage the power of AI.
Hanh: 00:21:24
With optimized models, you can start small, iterate quickly, and scale up as your needs grow. So, my fellow business owners and AI enthusiasts, Don't be intimidated by the jargon. Embrace the world of model optimization and discover how it can help you achieve your business goals more efficiently and effectively.
Hanh: 00:21:50
And speaking of efficiency, stay tuned for our next segment, where we'll explore the benefits of custom local models and how they can give you even more control over your AI destiny. Remember, optimization is your friend. It's like having a personal assistant that helps you streamline your AI workflows, saving you time, money, and headaches along the way.
Hanh: 00:22:14
So let's raise a toast to the unsung heroes of model optimization. May your AI models be lean, mean, and ready to tackle any business challenge that comes their way. The next anticipated big thing in 2024 in the world of AI is custom local models. Now, I know what you might be thinking, local models? Isn't the whole point of AI to
Hanh: 00:22:44
leverage the power of the cloud? Custom local models are like having your very own AI superpower tailored specifically to your business needs. Imagine this. You have a wealth of proprietary data and unique use cases that set your organization apart. With open source models, you can train custom versions of AI that are fine
Hanh: 00:23:12
tuned to your specific requirements. Thanks. It's like having a bespoke suit made just for you, instead of settling for an off the rack option. But the benefits don't stop there. By keeping your model, training, and deployment local, you maintain complete control over your sensitive data. No more worrying about sharing
Hanh: 00:23:33
your trade secrets or customer information with third party providers. It's like having a personal vault for your AI assets, with you holding the key. And here's the kicker, with retrieval techniques like RAG, Retrieval Augmented Generation, you can supplement your local models with relevant information from external sources on the fly. It's like having a personal librarian.
Hanh: 00:24:02
That fetches the exact book you need without having to store the entire library on your shelf. This approach allows you to keep your models lean and mean while still providing them with the knowledge they need to excel. But perhaps the most compelling reason to embrace custom local models is the peace of mind they offer.
Hanh: 00:24:24
With local control, you can ensure that your AI complies with all relevant regulations and security standards. No more worrying about data breaches or unauthorized access. It's like having a personal body guard for your AI, making sure it stays within the boundaries you set. Now, I know what you might be thinking. This all sounds great, but isn't
Hanh: 00:24:45
it complicated and expensive to build custom models? Well, my friends, that's where the beauty of open source comes in. With the rise of accessible AI frameworks and pre trained models, Building your own custom solution has never been easier or more cost effective. It's like having a recipe book for AI with all the ingredients
Hanh: 00:25:11
and instructions laid out for you. So why should you care about custom local models as a business owner? For starters, they give you a competitive edge by leveraging AI that's tailored to your unique needs. You can make better decisions, automate processes, and deliver personalized experiences to your customers. It's like having a secret weapon that
Hanh: 00:25:33
your competitors don't have access to. But more than that, custom local models put the power of AI in your hands. You're not dependent on the whims of a third party provider or the limitations of a generic model. You have the freedom to innovate, experiment, and adapt your AI to your evolving business requirements. It's like being the master
Hanh: 00:25:58
of your own AI destiny. So my fellow business owners and AI enthusiasts, don't be afraid to think local, embrace the power of custom models and take control of your AI journey. And speaking of control, stay tuned for our next segment, where we'll explore the world of virtual agents and how they can automate tasks and streamline your operations like never before.
Hanh: 00:26:26
Remember custom local models. Are your key to unlocking the full potential of AI for your business? There's like a bespoke suit, a personal vault in a secret weapon, all rolled into one. So let's raise a toast to the unsung heroes of custom AI. May your models be tailored, your data be secure, and your business
Hanh: 00:26:49
be propelled to new heights. Let's dive into the exciting world of virtual agents and task automation. Picture this. You have a never ending to do list with tasks ranging from booking appointments to filling out forms and managing customer inquiries. It's like juggling a dozen balls while trying to keep
Hanh: 00:27:17
your business running smoothly. But what if you had a personal assistant that could handle all these tasks for you without ever taking a coffee break? Enter the world of virtual agents. Gone are the days of simplistic chatbots that could barely understand your queries. Let alone provide meaningful assistance in 2024, conversational AI agents are graduating to a
Hanh: 00:27:41
whole new level of sophistication. They're like the valedictorians of the AI world. Ready to tackle complex tasks and automate processes like never before. Imagine having a virtual agent that can directly make reservations on your behalf. Whether it's booking a table at a restaurant or scheduling a meeting with a client.
Hanh: 00:28:09
No more endless phone calls or email chains. Your virtual assistant takes care of it all, freeing up your time to focus on the big picture stuff. But it doesn't stop there. These virtual agents can also fill out forms, extract relevant information, and even connect to external services and APIs.
Hanh: 00:28:31
It's like having a superhuman admin that can navigate the digital world with ease. Virtual agents are bringing general task automation and personal productivity assistance to businesses of all sizes and sectors. It's like having a Swiss Army knife for your daily operations, with each tool perfectly adapted to your needs. But the benefits of virtual agents go
Hanh: 00:28:54
beyond just saving time and effort. By automating routine tasks, You're also reducing the risk of human error and ensuring consistency across your processes. It's like having a quality control expert on your team, making sure that every task is completed accurately and efficiently. Plus, with virtual agents handling the mundane stuff, your human
Hanh: 00:29:22
employees can focus on the tasks that truly require their creativity, empathy, and problem solving skills. It's a win win situation. Your team gets to do more meaningful work, while your business reaps the benefits of increased productivity and customer satisfaction. Now, I know what you might be thinking. This all sounds too good to be true.
Hanh: 00:29:48
What's the catch? Well, my friends, the catch is that you need to choose the right virtual agent solution for your business. Not all AI assistants are created equal, and it's crucial to find one that aligns with your specific needs and integrates seamlessly with your existing systems. With the rapid advancements in conversational AI and the growing
Hanh: 00:30:15
ecosystem of virtual agent providers, finding the perfect match for your business has never been easier. It's like having a personal matchmaker for your AI needs, helping you find the one that will take your productivity to new heights. So my fellow business owners and productivity enthusiasts. Don't miss out on the
Hanh: 00:30:37
virtual agent revolution. Embrace the power of automated task completion and watch your business soar. And speaking of soaring, stay tuned for our next segment, where we'll explore the impact of AI regulations. And how to navigate the evolving legal landscape. Remember, virtual agents are your secret weapon for productivity and growth.
Hanh: 00:31:07
They're like a personal assistant, a quality control expert in a Swiss army knife, all rolled into one. The next crucial topic in 2024 is increased regulation of AI. As AI becomes more powerful and pervasive, governments and regulatory bodies are taking notice. It's like the Wild West of technology is finally getting some sheriffs
Hanh: 00:31:38
in town, and leading the charge is, is the European Union with their Artificial Intelligence Act. Think of the AI Act as a set of guardrails for the development and use of AI systems. It's like a code of conduct for the AI industry, ensuring that the technology is developed and deployed responsibly. The Act aims to protect citizens rights, promote trust in AI, and create
Hanh: 00:32:06
a level playing field for businesses. It's like having a referee on the field, making sure everyone plays by the rules. But the regulatory landscape isn't just about new laws. There are also ongoing legal battles around the fair use of copyrighted data in training AI models. It's a tricky balancing act between fostering innovation and protecting
Hanh: 00:32:32
intellectual property rights. Imagine you're an artist who spent countless hours creating a unique style, only to find out that an AI model has been trained on your work without permission. It's like having someone copy your signature dish and pass it off as their own. As generative AI's capabilities rapidly expand across public and private
Hanh: 00:32:58
domains, the need for regulatory oversight becomes even more pressing. These models can create content that looks and sounds like it was made by humans, blurring the lines between original and generated work. It's like having a Photoshop for everything with the potential to create both amazing and misleading content. But here's the thing, regulation
Hanh: 00:33:20
isn't just about restricting AI. It's also about creating a framework for responsible innovation. By setting clear guidelines and boundaries, regulations can actually help businesses navigate the complex landscape of AI ethics and compliance. It's like having a map and a compass for your AI journey, helping you stay on course and avoid pitfalls.
Hanh: 00:33:51
So what does this mean for you as a business owner? First and foremost, it means staying informed about the evolving regulatory landscape. Keep an eye on developments like the AI Act and the outcomes of legal battles around data use. It's like being a scout for your business, always on the lookout for
Hanh: 00:34:11
potential challenges and opportunities. Secondly, it means embedding responsible AI practices into your organization's DNA. This includes being transparent about your AI use, ensuring data privacy and security, and regularly auditing your AI systems for fairness and accountability. It's like having a checklist for AI best practices. Making sure you're ticking all the boxes.
Hanh: 00:34:37
Finally, it means collaborating with regulators, industry partners, and other stakeholders to shape the future of AI governance. No one has all of the answers and it's through open dialogue and shared learning that we can create a regulatory framework that balances innovation and responsibility. It's like being part of a team working
Hanh: 00:34:58
together towards a common goal. So my fellow, uh, business owners and AI enthusiasts don't fear the increased regulation of AI embrace it as an opportunity to build trust. Mitigate risk and create a sustainable future for this transformative technology. Speaking of the future, stay tuned for our final segment, where we'll delve into the world of explainable AI and
Hanh: 00:35:27
how it can help you build transparency and accountability into your AI systems. But for now, remember, Responsible AI isn't just a buzzword. It's a commitment to using this powerful technology in a way that benefits society as a whole. Next, we are going to shine the light on a shadowy topic. Shadow AI and the importance
Hanh: 00:35:57
of responsible use. Imagine this, your employees are using generative AI tools without your knowledge or oversight. It's like having a secret society of AI enthusiasts within your own company. While their intentions may be good, this unauthorized usage can lead to some serious risks. First and foremost, there's the
Hanh: 00:36:20
danger of inadvertently exposing trade secrets or intellectual property. If employees are training AI models on sensitive data without proper safeguards. It's like leaving the vault door wide open. Your company's crown jewels could be walking right out the front door. But it's not just about data leaks. There's also the potential
Hanh: 00:36:44
for copyright infringement. If employees are using proprietary data to train AI models without the necessary licenses or permissions, it's like plagiarizing someone else's work. You wouldn't want your company to be accused of stealing, would you? And let's not forget about the reputational risk. If word gets out that your company
Hanh: 00:37:06
is using AI irresponsibly or unethically, it can be a PR nightmare. It's like having a stain on your brand that no amount of spin can remove. So, what's the solution? It all comes down to comprehensive corporate governance and responsible AI implementation policies. Think of it as a rule book for AI use within your organization.
Hanh: 00:37:33
It's like having a code of conduct that everyone must follow, from the intern to the CEO. These policies should cover everything from data privacy and security to ethical considerations and legal compliance, but policies alone aren't enough. It's also crucial to educate your employees about the importance of responsible AI use.
Hanh: 00:37:59
This includes training them on best practices, providing clear guidelines and fostering a culture of transparency and accountability. It's like having a team of AI superheroes equipped with the knowledge and tools to use their powers for good. So, my fellow business owners and AI enthusiasts, don't let shadow AI cast a dark cloud over your organization.
Hanh: 00:38:24
Embrace the light of responsible use and take control of your AI destiny. By implementing comprehensive governance policies, educating your employees, and fostering a culture of responsibility, you can harness the power of AI while mitigating the risk. It's like having a secret weapon for innovation and growth, but one that's wielded with wisdom and care.
Hanh: 00:38:53
And that, my friends, brings us to the end of our journey through the AI trends of 2024. We've explored the rise of multi modal AI, the quest for smaller and more efficient models, the importance of custom local solutions, the power of virtual agents, the impact of increased regulation, and the necessity of responsible use. But the journey doesn't end here.
Hanh: 00:39:20
As AI continues to evolve at a breakneck pace, it's up to us, the business owners, the innovators, the enthusiasts, to make it happen. To shape its future, we have the power to create an AI landscape that is innovative, inclusive, and responsible. So let's rise to the challenge. Let's create a world where AI is not a shadowy threat, but
Hanh: 00:39:43
a shining beacon of progress. The future is ours to write, and I can't wait to see what incredible stories we'll tell. Thank you for joining me on this adventure until next time. Stay curious, stay responsible, and keep pushing the boundaries of what's possible.
Narrator: 00:40:07
As we conclude this captivating episode of AI50 Connect, let's take a moment to reflect on the exhilarating journey we've just undertaken. Today's adventure has been a thrilling deep dive into the world of AI and data, packed with eye opening insights and groundbreaking ideas that are shaping the future. Imagine AI as a key, unlocking
Narrator: 00:40:25
new realms in data intelligence. It's not just about processing information. It's about sparking a revolution for tech enthusiasts and business leaders alike. AI is the secret weapon for making smarter, faster, and bolder decisions. Envision AI transforming your business. Workflows streamline like never before, trends emerging crystal
Narrator: 00:40:50
clear, errors shrinking, and a team energized like a well oiled machine. It's not just about growth. It's a complete metamorphosis of your business universe. At AI50, we're more than just another voice in the podcast world. We're your AI navigators. Our mission is to empower and inspire your journey with tailored,
Narrator: 00:41:12
cutting edge AI and data strategies. We craft solutions that don't just fit, they propel your unique vision forward. Intrigued by what AI50 can do for your business? We're just a chat away. Let's connect and turn your data into a powerhouse of strategy and innovation. To stay on the pulse of AI, be sure to follow AI50 and Hanh Brown on LinkedIn.
Narrator: 00:41:35
Dive into a sea of the latest news, insights, and all things AI, keeping you ahead in the AI race. Don't just listen, join the movement, subscribe to AI50 Connect on your favorite podcast platforms, and be part of our upcoming episodes that delve deeper into AI secrets, bringing expert insights straight to you. For an extra dose of inspiration,
Narrator: 00:41:56
check us out on YouTube. From engaging podcast recaps to exclusive interviews, it's your visual gateway to the AI world. And if you're ready to leap into AI with your business, We're here to soar with you. Reach out to us and let's transform AI into your ultimate business ally for decision making and efficiency.
Narrator: 00:42:18
Thank you for tuning in to AI50 Connect. Remember, you're not just following the AI revolution, you're leading it. Until next time, stay curious, stay connected, and be the change with AI50. We can't wait to see you on the next frontier of AI exploration.
Hanh: 00:00:05
Imagine being able to just type in something like, Hey, how did our top selling product perform last quarter compared to the same period last year? And having Fabric automatically pull the relevant data, crunch the numbers, and give you a clear, easy to understand answer. No more digging through reports. No more trying to decipher
Hanh: 00:00:28
complex visualizations. Just a simple, natural language interaction that puts the power of your data right at your fingertips.
Narrator: 00:00:43
Welcome to AI50 Connect, your gateway to the transformative world of artificial intelligence and its profound impact on the lives of seniors. In today's data driven business landscape, organizations are increasingly turning to powerful platforms like Microsoft Fabric to unlock the true potential of their data. And that's exactly what we'll
Narrator: 00:01:03
be exploring in this episode. Joining us is AI Luminary and your host Hanh Brown, who is gifted at translating complex AI concepts into everyday terms. Hanh will illuminate the incredible potential of AI across healthcare, commerce, and our daily lives, while also delving into the role of Microsoft Fabric in streamlining data management and analytics workflows.
Narrator: 00:01:28
At AI50, we go beyond just exploring technology. It's an adventure into AI's transformative power. We bring you compelling narratives, explore groundbreaking innovations, and converse with pioneers like Hanh. Our dialogues span AI's diverse applications, from advancing medical care to revolutionizing business practices.
Narrator: 00:01:51
Each episode of AI50 Connect dives deep, examining AI's advancements alongside the ethical and societal. Seattle implications. Our aim is to shed light on a eyes, multifaceted nature and its capacity to drive positive change for older adults. So join us on this enlightening journey as we fuse engaging storytelling, expert analysis and vivid examples
Narrator: 00:02:12
to elucidate a eyes breath in depth. Let's begin unpacking the power of data with Microsoft fabric and discover how it's empowering organizations to make smarter, faster decisions. Hanh, let's get started.
Hanh: 00:02:33
I recently had the privilege of attending the Microsoft Fabric event in Las Vegas from March, uh, 25th to the 28th. And let me tell you, I came away with some incredible insights that I can't wait to share with you. In this episode, we're going to explore the topic of end to end data ingestion with Fabric As the core of
Hanh: 00:02:54
Microsoft's Intelligent Data Platform. Fabric is revolutionizing the way organizations manage and analyze their data. Whether you're a business owner looking to make more informed decisions, or a data professional seeking to streamline your workflows, Fabric has something to offer. During my time at the Las Vegas event, I had the opportunity to
Hanh: 00:03:23
learn from Microsoft experts, connect with other Fabric users, and see firsthand how this powerful platform is transforming industries. I gained a deeper understanding of Fabric's seamless integration capabilities. It's real time analytics features and the collaborative community that's driving its ongoing evolution with intuitive
Hanh: 00:03:44
tools like the metrics layer and AI powered assistance like co pilot fabric is breaking down barriers and making data more accessible than ever before in today's fast paced business world. Data has become the lifeblood of successful companies, but harnessing that data to make informed decisions can be a real challenge. Especially for business
Hanh: 00:04:10
owners who aren't tech savvy. That's why I'm excited to talk to you about Microsoft Fabric, a powerful, all in one platform that's revolutionizing the way organizations manage and analyze their data. We'll dive into how Fabric can help you unlock the true power of your data, no matter your technical expertise. You'll learn about its seamless
Hanh: 00:04:34
integration capabilities, its collaborative community, and And the cutting edge AI features that are making data exploration easier than ever before. So get ready to discover how Fabric can transform the way you do business. Let's get started. As a business owner, you probably know how important data is to the success of your company.
Hanh: 00:05:05
But let me ask you a question, how much time and effort do you and your team spend trying to wrangle all that data and turn it into something meaningful? It can be a real headache, can't it? That's where Microsoft Fabric comes in. Fabric is the central component of Microsoft's Intelligent Data Platform. And it's designed to be a one stop shop for all your data and analytics needs.
Hanh: 00:05:33
Think of it as your own personal data command center, where you can bring together all the information your business relies on, from customer records, to sales figures, to inventory data. Instead of having to jump between multiple software programs and databases, your team can access everything they need right from within Fabric. It's like having a big, organized
Hanh: 00:05:56
filing cabinet for all your important documents, instead of having them scattered across your office. And it's not just about consolidating your data. Fabric also gives you the tools to manage it all more effectively. You can use it to store and process your data, build sophisticated analytics models, And create
Hanh: 00:06:16
customized reports and dashboards. Imagine being able to get a real time, 360 degree view of your business, all from one central hub. That's the power of Fabric. Now, I know what you might be thinking, but I'm not a tech expert. How am I supposed to use all these advanced features? Well, that's the beauty of Fabric.
Hanh: 00:06:44
It's designed to be user friendly, even for those of us who aren't exactly tech savvy. Let me give you an example. Say you run a small retail business and you want to get a better handle on your inventory and sales trends. With Fabric, you can easily connect all your point of sale data, your online sales, and your supplier
Hanh: 00:07:03
information into one central system. From there, you can start building custom dashboards and reports that give you a clear picture of how your business is performing. Maybe you want to see which products are selling the fastest in your business. Or which locations are bringing in the most revenue. Fabric makes it easy to create these types
Hanh: 00:07:25
of reports without you having to be an expert in data analysis or programming. It's all about putting the power of data in your hands in a way that's simple and intuitive. And the best part is, Fabric is designed to grow and evolve with your business as your data needs change and your company expands. Fabric can scale right along with you.
Hanh: 00:07:52
So you never have to worry about outgrowing your data management platform. Think about it this way. Fabric is like having a personal assistant who's always there to help you make sense of your data. They'll gather all the information you need, help you organize it, and even provide insights and recommendations to guide your decision making.
Hanh: 00:08:14
That's the kind of support you need. That can be invaluable for a busy business owner like yourself. So if you're tired of feeling overwhelmed by your data, or if you're just looking for a more efficient way to manage and analyze it all, I highly recommend taking a closer look at Microsoft Fabric. It's a powerful, yet user friendly platform that can truly
Hanh: 00:08:38
transform the way you do business. And with the support of the Fabric community and Microsoft's ongoing innovation, you can be confident that your data is in good hands. As a business owner who's been around the block a few times, I'm sure you've seen your fair share of technology solutions come and go. And I bet you've had your
Hanh: 00:09:05
frustrations with trying to get all those different software programs and databases to work together. That's where Microsoft Fabric really shines. One of the key things that sets Fabric apart is its ability to seamlessly integrate with all the other systems and data sources you're already using in your business.
Hanh: 00:09:25
Think about it like this. Remember back in the day when you had to use a separate filing cabinet for each department? www. microsoft. com And you'd waste so much time trying to find the right information. Fabric is like having one big, centralized filing system that can connect to all
Hanh: 00:09:43
the other cabinets in your office. With Fabric, you can bring all of that together into one unified platform. So your team can access everything they need with just a few clicks. And it's not just about consolidating your data. Fabric also gives you the power to analyze it in real time. Remember how frustrating it used to
Hanh: 00:10:04
be when you'd request a report only to have to wait days or even weeks to get the information you needed? With Fabric, you can get instant, up to the minute insights on what's happening in your business. Let me give you an example that might hit close to home. Think about the last time you went to your local bank to check your
Hanh: 00:10:28
balance or make a transaction. Chances are the teller was able to pull up your account information in just a matter of seconds, right? That's the kind of real time responsiveness that fabric can bring to your business. A large telecommunications company called One nz. experience this firsthand.
Hanh: 00:10:47
Before they started using Fabric, their Power BI dashboards were taking a long time to refresh, which was slowing down their ability to make quick decisions. But after integrating Fabric, they were able to cut their refresh times by over 80 percent from 60 seconds down to just 10 seconds. Can you imagine how much of a game changer that would be for your own business?
Hanh: 00:11:12
Instead of having to wait around for the latest numbers or sales figures, You and your team could be making informed decisions in real time. That kind of agility and responsiveness is priceless in today's fast paced business environment. And the best part is, Fabric makes all of this integration and real time analytics accessible, even for
Hanh: 00:11:30
those of us who aren't tech whizzes. The platform is designed with intuitive, user friendly interfaces that are easy to navigate. No matter your level of technical expertise. So you don't have to worry about your team getting bogged down in complex software and are struggling to make sense of all the data.
Hanh: 00:11:55
I know change can be scary sometimes, especially when it comes to technology, but I can assure you fabric is, uh, the kind of solution that's going to make your life. As a business owner, a whole lot easier. It's like having a personal assistant who's always on top of your data, serving up the information you need when you need it.
Hanh: 00:12:17
And in today's fast paced data driven world, that kind of support can be the difference between staying ahead of the competition or getting left behind. So if you're ready to take your business to the next level and unlock the true power of your data, I highly recommend giving Fabric a closer look. It's a platform that's built to grow and scale with your company so you
Hanh: 00:12:42
can focus on what you do best, running a successful, thriving business. You know, as a business owner, it can sometimes feel like you're operating in a silo, doesn't it? You're so focused on the day to day demands of running your company. That it can be hard to find the time to connect with other professionals who are facing similar challenges.
Hanh: 00:13:09
When you're trying to figure out how to tackle a problem or implement a new strategy, wouldn't it be great to have a network of other business owners and data experts who you could turn to for advice and support? That's exactly what the Fabric community offers. Through online forums, user groups, and even in person events, Fabric users from
Hanh: 00:13:32
all different industries and backgrounds come together to share their knowledge, experiences, and best practices. It's like having your own personal think tank, where you can bounce ideas off of people who truly understand the unique challenges of running a business and In the 21st century, and it's not just about learning from others. The fabric community also gives
Hanh: 00:13:53
you a direct line of communication to the product team at Microsoft. Remember how I mentioned that fabric is designed to be user friendly and intuitive. Well, a big part of that is thanks to the valuable feedback and insights that the community provides. Imagine being able to tell the folks at Microsoft.
Hanh: 00:14:15
You know, it would be really helpful if Fabric could do XYZ and then actually seeing that feature implemented in a future update. That kind of direct collaborative relationship between users and the product team is pretty rare, but it's something that Fabric has really embraced. Say you're a baby boomer business owner like myself and you've been using Fabric
Hanh: 00:14:40
for a while, but you're still struggling to get some of your team members on board. Well, you could reach out to the fabric community and ask, Hey, does anyone have any tips for getting non technical employees to buy into this platform? And chances are you get a bunch of really helpful responses from other boomers. Who have been there and done that, or maybe you're interested in exploring
Hanh: 00:15:05
fabrics, AI powered features like the co pilot assistant, but you're not sure where to start again, the community would be there to guide you with step by step tutorials, best practices, and even live training sessions. And the best part is Microsoft is constantly working to enhance and expand fabric based on the feedback and insights they receive from this community.
Hanh: 00:15:31
Thriving community. It's not like some static software program that you have to keep upgrading every few years. Fabric is continuously evolving to meet the changing needs of businesses like yours. Just think about how much the technology landscape has shifted even in the last decade.
Hanh: 00:15:49
Remember when we used to have to install software on our desktops and update it manually? Nowadays, we're all about cloud based platforms and automatic updates, aren't we? Well, Fabric is, um, very much a product of this new, agile, cloud native world, which means you can count on it to keep pace with the
Hanh: 00:16:12
latest trends and innovations. So, if you're looking for a data management and analytics solution that's not only powerful and user friendly, but also backed by a passionate, engaged community, In a company that's committed to continuous improvement, I highly recommend giving Microsoft Fabric a closer look. It's the kind of platform that can
Hanh: 00:16:33
truly transform the way you do business. And with the support of the Fabric community, you'll never have to feel like you're going it alone. Now, I know what you might be thinking. With all this talk about data and analytics, you're probably wondering, but what about security? How do I know my sensitive information is going to be safe?
Hanh: 00:17:03
And that's a perfectly valid concern, my friend. In today's digital landscape, data security and governance are more important than ever. Especially for small and medium sized businesses like yours. But let me tell you, when it comes to Microsoft Fabric, you can rest easy. You see, Fabric doesn't just give you the
Hanh: 00:17:21
tools to manage and analyze your data. It also comes with some serious security and compliance features. That are designed to give you peace of mind. One of the key things that sets Fabric apart is its tight integration with Microsoft Purview, the company's industry leading data, governance, and security solution.
Hanh: 00:17:46
Now, I know that might sound like a bunch of tech jargon, but bear with me, it's actually a really big deal. Essentially, what this integration means is that Fabric can leverage all of Purview's powerful security and compliance capabilities to protect your sensitive information. Think about it like this. Remember back in the day when you
Hanh: 00:18:05
used to keep your important documents locked up in a filing cabinet with a key that only you and your most trusted employees had access to? Well, Fabric and Purview are kind of like that, but on steroids. For example, Fabric can give you granular control over who has access to your data. And what they're allowed to do with it. So you can have one set of permissions
Hanh: 00:18:31
for your accounting team, another for your sales staff, and yet another for your executive leadership. It's like having a whole team of security guards watching over your most valuable assets. And it's not just about access control. Fabric and Purview also work together to detect and prevent data breaches, compliance violations,
Hanh: 00:18:54
and other security threats. Fabric and Purview Imagine being able to automatically flag any suspicious activity, like an employee trying to download a sensitive customer file or someone attempting to share confidential information outside of your organization. That's the kind of proactive real time protection that Fabric and Purview can provide.
Hanh: 00:19:16
Now, I know what you might be thinking. But I'm just a small business owner. Do I really need all this fancy security stuff? And my answer to that would be a resounding yes. Because in today's world, no business is immune to the risk of data breaches and compliance violations, regardless of size. Just think about the last time you
Hanh: 00:19:35
heard about a major company getting hit with a huge fine or lawsuit because of a data privacy issue. Or how about all the headlines about ransomware attacks shutting down entire businesses? Those kinds of threats aren't just for the big guys. They can impact companies of all shapes and sizes.
Hanh: 00:19:58
And let me tell you, the fallout from a data security incident can be absolutely devastating, both financially and reputationally. But with Fabric and Purview in your corner, you can rest assured that your data is being protected to the highest standards without you having to worry about the technical details. It's like having a personal bodyguard for
Hanh: 00:20:19
your most valuable information assets. And the best part is, all of these security and governance features are designed to be user friendly and intuitive, just like the rest of the Fabric platform, so you don't have to be a tech expert to take advantage of them. Instead, you can focus on what you do best, running your business. And making smart data driven decisions,
Hanh: 00:20:45
confident in the knowledge that your information is safe and secure. So, if you're looking for a data management solution that not only empowers you to unlock the power of your data, but also gives you the peace of mind that comes with ironclad security and governance, I highly recommend giving Microsoft Fabric a closer look. It's the kind of platform that can truly
Hanh: 00:21:11
transform the way you do business and keep you and your company protected, no matter what the future might hold. Because let's be honest, a lot of the data and analytics tools out there can be pretty intimidating, can't they? All those complex menus. Technical jargon in complicated dashboards can make your head spin. But with Fabric, the team at Microsoft
Hanh: 00:21:44
has really made a conscious effort to put the power of data into the hands of everyday business owners and operators. They understand that not everyone is a data scientist or a school wizard, and they've designed the platform to be intuitive, user friendly, and accessible. No matter your level of technical expertise, take the metrics layer. For example, this is a feature that I
Hanh: 00:22:09
think could be particularly useful for business owners like yourself who are looking to get a better handle on your key performance indicators, or KPIs, as U. S. data nerds like to call them. Essentially, the metrics layer allows you to create a library of standardized, predefined metrics that your entire organization can access and use.
Hanh: 00:22:36
Imagine being able to quickly pull up reports on your top selling products, your customer retention rates, or your operational efficiency, without having to worry about the technical details of how that data is being calculated or where it's coming from. The metrics layer does all of that heavy lifting for you, presenting information in a clear, clear way.
Hanh: 00:23:02
Easy to understand way and the best part is you don't have to be the one to define and maintain those metrics fabric gives you the ability to designate trusted creators within your organization, perhaps your CFO, your sales manager or your operations director who can set up and manage the metrics layer on behalf of the rest of the team. So instead of having everyone creating
Hanh: 00:23:24
their own custom reports and calculations. Which can lead to inconsistencies and confusion. You can have a centralized, vetted set of KPIs that everyone can reference. It's kind of like having a playbook for your business's most important data points, all in one convenient location. But the metrics layer is just one example of how Fabric is
Hanh: 00:23:52
designed to empower business users. The platform also features a whole host of other intuitive tools and features that are meant to break down the barriers between data and decision making. For instance, Fabric integrates seamlessly with Microsoft's popular Power BI Business Intelligence platform. Allowing you and your team to create stunning, visually appealing own
Hanh: 00:24:15
reports and dashboards without needing a degree in data science. And with features like the ability to live edit your data models and generate mobile friendly layouts, Fabric makes it easier than ever to access and share crucial insights, no matter where you or your employees are working from. I know what you might be thinking, this all sounds great, but how do
Hanh: 00:24:40
I actually get started with Fabric? I'm not exactly a tech wizard, you know, and that's a totally fair concern, but the beauty of fabric is that it's designed to be approachable and user friendly, even for those of us who aren't exactly digital natives. And if you ever feel like you need a little extra help, well, that's where I might be able to lend
Hanh: 00:25:02
a hand as a fabric consultant. I've helped all kinds of business owners. Just like yourself to get the most out of the platform and unlock the true power of their data. So if you ever find yourself feeling stuck or unsure of where to start, don't hesitate to reach out. I'd be more than happy to give you a hand and show you how Fabric can
Hanh: 00:25:28
transform the way you do business. Because at the end of the day, that's what it's all about, isn't it? Using data and technology to make your life as a business owner. A little bit easier and empowering you to make smarter, more informed decisions that drive real results. And with Microsoft Fabric in your toolbox, I'm confident
Hanh: 00:25:51
you'll be able to do just that. Now, I don't know about you, but when it comes to data and analytics, I'll admit that I used to be a bit of a skeptic. I mean, I understood the importance of using data to drive business decisions, but a lot of those advanced tools and techniques just seem so daunting and complicated. It was like learning a whole
Hanh: 00:26:16
new language, you know? But then I started learning more about the AI powered capabilities that Microsoft has built into Fabric. And let me tell you, it's completely changed my perspective. Because Fabric isn't just about giving you access to data. It's about using cutting edge technology to make that data more
Hanh: 00:26:40
accessible, more intuitive, and more actionable than ever before. Take the CoPilot feature, for example. Now, I know what you might be thinking. An AI assistant. Isn't that just going to confuse me even more? But hear me out. Because CoPilot is actually designed to do the exact opposite.
Hanh: 00:27:01
CoPilot. It's like having a personal data concierge who can guide you through the process of exploring and analyzing your information. Let's say you're trying to get a handle on your sales trends and you want to dig into the data to see which products are performing the best. Normally you might have to spend hours poring over spreadsheets and
Hanh: 00:27:25
trying to write complex But with Copilot, you can simply, uh, ask it questions in plain English, and it'll do the heavy lifting for you. Copilot can help you understand the structure of your data, suggest relevant metrics and KPIs to track, and even write the actual code to generate the reports and visualizations you need. It's like having a data expert right
Hanh: 00:27:50
there by your side, translating all that technical jargon into something that's easy for you to comprehend and act on. And it's not just Copilot. Fabric also has some other AI powered features that are designed to make data exploration and analysis more intuitive and user friendly. Take the Enhanced Explore capabilities, for example.
Hanh: 00:28:18
With this feature, You can get a high level summary of your data assets, including the various tables, columns, and relationships, all presented in a clean, visual format. Now, I know what you might be thinking, but won't I still need to know how to work with all those technical data modeling concepts? And the answer is, not necessarily.
Hanh: 00:28:45
Fabric's Explore feature is built to provide that overview in a way that's easy for even non technical users to understand. It's like having a digital tour guide who can show you around your data without needing a Ph. D. in computer science. And speaking of making
Hanh: 00:29:04
data more accessible. Fabric also has a really exciting feature in the works that I think you're going to love. It's called the Custom QA Experience. And it's basically a conversational interface that allows you to ask questions about your data using plain language and get instant contextual responses. Imagine being able to just type in
Hanh: 00:29:28
something like, Hey, how did our top selling product perform last quarter compared to the same period last year? And having Fabric automatically pull the relevant data, crunch the numbers. and give you a clear, easy to understand answer. No more digging through reports. No more trying to decipher complex visualizations.
Hanh: 00:29:55
Just a simple, natural language interaction that puts the power of your data right at your fingertips. Now, I know what you might be thinking. This all sounds great, but is it really going to work for someone like me, who's not a tech wizard? And that's a totally fair question. But the beauty of Fabric's AI powered features is that they're designed
Hanh: 00:30:19
to be accessible and intuitive. Even for those of us who aren't exactly computer gurus, in fact, I'd argue that these kinds of AI powered capabilities are actually going to be a game changer for business owners like yourself, because they're going to allow you to unlock the full potential of your data without getting bogged down in the technical complexities.
Hanh: 00:30:43
It's about taking all that powerful analytics functionality and making it work for you in a way that's simple, streamlined, and aligned with the way you actually think and operate as a business leader. So if you're ready to take your data driven decision making to the next level, and you want a platform that's going to empower you and your
Hanh: 00:31:08
team to explore, analyze, and act on your information, then In new and innovative ways, I highly encourage you to give Fabric a closer look. With its AI powered features and its commitment to user friendliness, I'm confident that it's going to be a total game changer for your business. As we've discussed, Microsoft Fabric is a pretty remarkable platform.
Hanh: 00:31:39
One that's truly transforming the way businesses like yours work. Can leverage data to drive better decisions and achieve greater success. But you know what's even more exciting? The fact that Fabric is constantly evolving and improving. Thanks to Microsoft's long term commitment to innovation and the valuable feedback from the Fabric community.
Hanh: 00:32:04
I mean, just think about how much the technology landscape has changed over the years. Even in the last few years, remember when we used to have to install software on our desktops and go through these big, clunky upgrade cycles? Nowadays, it's all about cloud based platforms and automatic updates, isn't it? Well, Fabric is very much a product of
Hanh: 00:32:26
this new, agile, cloud native world, which means you can count on it to keep pace with the latest trends. And continue to expand its capabilities. And if you really want to take your Fabric experience to the next level, I'd highly recommend connecting with our team at AI50. As a Microsoft partner, they've got deep expertise in helping businesses like yours
Hanh: 00:32:52
leverage the full power of Fabric and the broader intelligent data platform. We not only can provide you with hands on guidance and support, As you get started with the platform, but we can also work with you to explore innovative use cases and custom integrations that can give you a real competitive edge. I mean, think about it with AI 50 in your corner, you'll have access
Hanh: 00:33:20
to a team of fabric specialists who can help you navigate the platform, unlock new capabilities, and stay ahead of the curve as Microsoft continues to enhance and expand it. As a busy business owner, the last thing you probably want to worry about is trying to figure out all the technical ins and outs of a new data management solution. So, if you're excited about the
Hanh: 00:33:43
prospect of taking your data driven decision making to the next level, and you want to make sure you're staying on the cutting edge of the latest fabric innovations, I'd encourage you to reach out to our team at AI50. We can walk you through the platform, help you identify the best use cases for your business, and even provide ongoing support and training to ensure you're getting
Hanh: 00:34:13
maximum value from your fabric investment. Because at the end of the day, that's what it's all about. Using the power of data and technology to drive real, sustainable growth for your business. And with Fabric and AI50 in your corner, I'm confident that you'll be able to do just that both now and well into the future.
Hanh: 00:34:39
Well, there you have it. A deep dive into how Microsoft Fabric can help unlock the power of data for businesses like yours. I hope that through our discussion, you've gained a better understanding of just how transformative this platform can be. And how it can help you make smarter, more informed decisions to drive your company's success.
Hanh: 00:35:02
Let's quickly recap some of the key takeaways from our conversation. First and foremost, Fabric is the heart of the Microsoft Intelligent Data Platform, providing a comprehensive cloud based solution for all your data and analytics needs. By consolidating everything into a single integrated platform, Fabric can help streamline your workflows,
Hanh: 00:35:24
improve your team's productivity, and ensure you have a reliable, trust source of data across your organization. We also explored Fabric's seamless integration capabilities and real time analytics features, which can enable you to access up to the minute insights and make faster, more agile business decisions. In the platform's collaborative
Hanh: 00:35:45
community, And Microsoft's commitment to continuous innovation mean that Fabric will only continue to grow and evolve to meet your changing needs. Importantly, we discussed how Fabric is designed to empower business users like yourself, with intuitive tools and features that break down the barriers between data and decision making. From the metrics layer to the AI powered
Hanh: 00:36:11
co pilot assistant, Fabric is making it easier than ever for non technical users to unlock the value of their data. Finally, I encourage you to reach out to the team at AI50. We can provide hands on guidance and support to platform's capabilities. And stay ahead of the curve as fabric continues to evolve. So, if you're ready to take your
Hanh: 00:36:40
data driven decision making to new heights, I highly recommend giving Microsoft Fabric a closer look. It's a game changing platform that can truly transform the way you do business. Thanks for listening and feel free to reach out anytime if you have any other questions.
Narrator: 00:37:05
As we wrap up today's AI50 Connect journey, we've not only delved deeper into the vast ocean of AI and data knowledge, But also explore the transformative potential of Microsoft Fabric. Each insight shared today isn't just information. It's a stepping stone to innovation. AI and platforms like Microsoft Fabric are
Narrator: 00:37:22
redefining the way we interact with data. Making it more alive, more insightful, and more transformative. Whether you're in tech or leading a business, these tools are your game changers. Enabling smarter, faster, and more precise decisions. Thinking of leveraging AI and Microsoft Fabric in your business.
Narrator: 00:37:46
Picture this, streamlined processes, advanced analytics, minimized errors. And a team in synergy. It's not just about profit growth. It's a business evolution. At AI50, we're more than just a podcast. We're your AI compass. Our mission is to empower your business journey with bespoke AI and data strategies.
Narrator: 00:38:09
We're crafting solutions that don't just innovate, they resonate with your unique ambitions. Curious about how AI50 can help transform your business? We're just a conversation away. Reach out, and let's explore how we can turn your data into your most powerful ally. Keep the AI50 conversation going
Narrator: 00:38:26
on LinkedIn, where our community is always sharing cutting edge news and deep dives into the world of AI. And for even more insights, be sure to follow your host, Hanh Brown, on LinkedIn, too. It's your go to source for the latest AI trends and expert perspectives. If you enjoyed today's episode, hit subscribe on AI50 Connect, available
Narrator: 00:38:51
on your favorite podcast platforms. Stay with us for more explorations into the exciting realm of AI and data, with new experts joining us every week. For a visual feast, follow us on YouTube, where you'll find podcast highlights, exclusive interviews, and so much more, all waiting to inspire and amaze you. And if you're ready to take the next step in your AI journey, contact us.
Narrator: 00:39:15
We're here to guide you towards smarter decision making and enhanced efficiency through the power of AI and platforms like Microsoft Fabric. Thank you for joining us on AI50 Connect. As you navigate this ever evolving landscape of artificial intelligence, remember, you're not just keeping pace, you're shaping the future. Until next time, keep exploring, keep
Narrator: 00:39:33
connecting, and keep leading with AI50. See you on the next wave of innovation.
Hanh: 00:00:05
The bottom line is this, AI is not the future, it's the present, and the organizations and individuals who embrace it, adapt to it, and leverage it strategically will be the ones who thrive in the years to come. So are you ready to be part of the AI revolution?
Narrator: 00:00:29
Greetings to all our listeners and welcome to AI50, your portal to the extraordinary world of artificial intelligence or AI. Each episode is a tapestry woven with the threads of AI's influence, particularly highlighting its role in enriching the lives of the senior community. Today, we're embarking on a thrilling exploration of AI's presence in our
Narrator: 00:00:50
daily lives and the revolutionary changes it's bringing to various industries. We'll be discussing how AI is already integrated into our routines, often in ways we might not even realize, and how it's poised to shape the future of work and society. Joining us is Hanh Brown, a luminary in the AI landscape. Hanh has a gift for translating
Narrator: 00:01:10
the language of AI into everyday terms, revealing its incredible potential in fields ranging from health care to commerce and it's subtle presence in our daily lives. AI50 isn't just about exploring technology. It's an adventure into the heart of AI's transformative power. We bring you compelling narratives.
Narrator: 00:01:32
Explore groundbreaking innovations and converse with pioneers in the field. Our dialogue span a broad array of AI applications, how it's advancing medical care, revolutionizing business practices, and seamlessly integrating into our daily habits. Throughout this episode, we'll be diving deep into the most exciting AI trends and developments on the
Narrator: 00:01:53
horizon, offering insights and advice on how individuals and businesses. Can prepare for a eyes growing presence will also be addressing common concerns and ethical questions surrounding a I providing expert perspectives on responsible a I development and deployment embark with us on this enlightening journey. We promise a fusion of engaging
Narrator: 00:02:15
storytelling expert analysis and vivid examples to bring the vibrant world of AI to life. This approach is crafted to enhance your understanding of a eyes breath in depth. Let's start unwrapping the layers of today's intriguing AI topic the revolution that's already here Hanh Let's get started
Hanh: 00:02:43
We're going to explore the fascinating world of artificial intelligence and how it's already transforming our daily lives in ways you might not even realize Imagine this, you wake up in the morning and your smart home assistant greets you with a personalized news briefing and weather report. As you scroll through your social media feed, AI algorithms curate
Hanh: 00:03:09
content tailored to your interests. On your way to work, your smartphone's AI powered navigation app helps you avoid traffic jams and find the fastest route. These are just a few examples of how AI has become a ubiquitous presence in our modern world, quietly enhancing our experiences and shaping the way we live, work, and interact. But have you ever stopped to
Hanh: 00:03:34
consider the full extent of AI's impact on businesses and industries? From healthcare and finance to manufacturing and retail, AI is disrupting traditional models and creating new opportunities for innovation and growth. As a business owner or professional, are you prepared for this technological revolution? Do you have the skills and
Hanh: 00:03:56
knowledge to navigate an increasingly AI driven landscape? In this episode, we'll dive deep into these questions and more. We'll explore real world examples of AI's transformative power, examine the latest trends and breakthroughs, And discuss practical strategies for embracing AI in your own organization. Whether you're a tech savvy
Hanh: 00:04:18
entrepreneur or simply curious about the future of work. This episode will provide you with valuable insights and actionable advice. So, are you ready to embark on a journey into the heart of the AI revolution? Join me as we uncover the ways in which artificial intelligence is already reshaping our world. And discover how you can harness its
Hanh: 00:04:42
power to stay ahead of the curve. Let's dive in. Think about your typical day for a moment. How many times do you interact with artificial intelligence? Often without even realizing it. It might surprise you just how ubiquitous AI has become in our daily lives. Did you know an average person interacts with AI powered
Hanh: 00:05:13
technology over 100 times per day? Often, without even realizing it, take something as simple as your morning routine. When you wake up and check the weather on your smartphone, that weather app is likely powered by AI algorithms that analyze complex meteorological data to provide you with an accurate forecast. And when you ask your voice assistant
Hanh: 00:05:37
to play your favorite music or add an appointment to your calendar. You're tapping into the power of AI driven natural language processing. Think about the last time you use the voice assistant on your smartphone to set a reminder or look up the weather. That's just one small example of how AI has become an integral part of our daily routines.
Hanh: 00:06:04
Even our driving experiences are being transformed by AI. Modern vehicles are equipped with intelligent safety features like lane keeping assist. An automatic emergency braking, which use computer vision and predictive analytics to enhance our driving and keep us safe on the roads. And let's not forget about the AI
Hanh: 00:06:24
that's quietly working behind the scenes to improve our online experiences. When you browse products on e commerce sites, the recommendations you see are generated by sophisticated machine learning models. That analyze your browsing history and preferences. And when you scroll through your social media feeds, the content
Hanh: 00:06:44
you're presented with is carefully curated by AI algorithms designed to keep you engaged and entertained. The truth is, AI has become so deeply integrated into our daily lives that it's easy to take it for granted. But when you step back and think about it, the level of intelligence and automation that AI brings to even the most mundane tasks is truly remarkable.
Hanh: 00:07:10
Just consider how much time and effort we used to spend manually sorting through weather data and data. Curating playlists or sifting through product catalogs. AI has streamlined and optimize these processes, freeing us up to focus on the more important and fulfilling aspects of our lives. And as AI continues to evolve, its
Hanh: 00:07:30
presence in our daily routines is only going to become more pronounced. We're already seeing the rise of intelligent personal assistance, autonomous vehicles, and even AI powered healthcare solutions. That are transforming the way we live, work, and access essential services. So the next time you breeze through your morning routine, take a moment
Hanh: 00:07:57
to appreciate the AI power technology. That's making your life a little bit easier because this revolution isn't just coming. It's already here and it's only just the beginning. Microsoft has reported that their enterprise customers deploying AI powered solution. have seen an average of 20 percent
Hanh: 00:08:21
improvement in operational efficiency. Let me share a few examples of how the tech giant is empowering organizations across various industries to leverage this transformative technology. One area where Microsoft has seen great success is in using computer vision and predictive analytics To optimize manufacturing operations, for instance, they've worked with customers in the
Hanh: 00:08:48
automotive and aerospace sectors to deploy a I powered quality control systems. These solutions can continuously monitor production lines. spot defects in real time, and make automated adjustments to improve yields and reduce waste. By integrating these AI driven quality assurance capabilities, Microsoft's customers have reported significant
Hanh: 00:09:12
gains in operational efficiency. They're able to identify and address issues much faster than relying on manual inspections alone, leading to higher product quality and greater supply chain stability. Microsoft has also made strides in applying natural language processing to enhance customer service experiences. Many of their enterprise clients
Hanh: 00:09:36
have implemented AI powered chatbots and virtual agents to handle routine inquiries and free up human agents to focus on more complex problem solving. The benefits have been twofold. Not only do these conversational AI systems provide prompt, around the clock support for customers, But they also improve the productivity and job satisfaction of the service teams.
Hanh: 00:10:01
Employees can devote more time to delivering personalized, high value interactions, rather than getting bogged down in repetitive tasks. In the retail sector, Microsoft is leveraging computer vision to help businesses automate inventory management, and track customer foot traffic patterns. By applying these AI powered analytics, retailers can gain critical insights to
Hanh: 00:10:26
optimize their operations and enhance the overall shopping experience. And in the healthcare industry, Microsoft's predictive analytic solutions are helping providers improve patient outcomes and streamline administrative processes. By identifying trends and patterns in patient data, these AI systems can assist with everything from
Hanh: 00:10:46
early disease detection to resource allocation and scheduling optimization. Of course, rolling out these AI powered solutions hasn't been without its challenges. Thanks. Microsoft has spoken openly about the change management hurdles their customers have faced in getting employees comfortable with the new technology.
Hanh: 00:11:12
There is often initial skepticism and resistance with concerns that AI will replace human jobs. To address this, Microsoft has emphasized the importance of framing AI as a tool to augment and empower human workers. Not replace them. They work closely with clients to provide extensive training, highlight the tangible benefits, and foster a culture
Hanh: 00:11:33
of continuous learning and adaptation. Additionally, Microsoft has stressed the critical need for robust data governance and security measures to support successful AI deployments. These intelligent systems are only as effective as the quality of the data they're trained on. So, investing in data management infrastructure, access controls, and
Hanh: 00:12:02
bias mitigation has been a key focus. Looking ahead, Microsoft sees enormous potential in applying AI to transform business forecasting and decision making. Their work in areas like predictive analytics, natural language processing, and computer vision could revolutionize how companies analyze market trends, optimize operations, and anticipate customer needs.
Hanh: 00:12:26
By sharing these real world examples of Microsoft's AI success stories, I hope I've given you a better sense of Of how this technology is already making a tangible impact on organizations today, while the journey may have its challenges, the benefits of embracing a I are becoming increasingly clear. As we've seen, it's clear that a I is already making a significant
Hanh: 00:12:57
impact on businesses across a wide range of industries. But the truth is, we're still just scratching the surface of what this transformative technology can do. According to a recent report by a respected research firm, advancements in natural language processing and computer vision are expected to be the most transformative AI
Hanh: 00:13:16
trends over the next five years. Natural language processing, NLP, the ability of AI systems to understand, interpret, and generate human language has come a long way in recent years. We're seeing increasingly sophisticated chatbots and virtual assistants that can engage in remarkably natural sounding conversations, answering questions, and even providing
Hanh: 00:13:42
personalized recommendations. But the potential of NLP goes far beyond just customer service. Imagine AI powered tools that can automatically summarize long documents, translate between languages in real time, or even assist with creative writing tasks. The implications for productivity, collaboration, and knowledge
Hanh: 00:14:07
sharing are truly profound. Predictive analytics, AI's capacity for rapidly processing and analyzing massive data sets, makes it an incredibly powerful tool for forecasting and predictive modeling. Imagine an AI system that can scan your sales data, market trends, and customer behavior to identify patterns and predict future outcomes
Hanh: 00:14:32
with a high degree of accuracy. This kind of predictive intelligence could revolutionize everything from inventory management and financial planning to targeted marketing and risk mitigation. Organizations that can harness the power of AI driven predictive analytics will gain a significant competitive edge. Computer Vision The ability of AI to perceive, analyze, and make sense
Hanh: 00:14:58
of visual information is another area that's seen rapid advancements. We're already seeing AI powered applications in industries like manufacturing, healthcare, and transportation that can detect defects, diagnose medical conditions, and even navigate autonomous vehicles. But the applications of computer vision go far beyond just
Hanh: 00:15:19
these specialized use cases. Imagine an AI system that can automatically categorize and organize your digital photos, or one that can parse complex architectural drawings or satellite imagery to glean valuable insights. The potential to automate visual tasks and unlock new sources of data is truly exciting.
Hanh: 00:15:42
And these are just a few of the emerging AI trends that we're keeping a close eye on. As the underlying technologies continue to advance, We're likely to see AI become an even more integral and ubiquitous part of our daily lives and business operations. Just imagine a future where AI powered personal assistants can anticipate our needs.
Hanh: 00:16:07
Predictive analytic systems can help us make smarter decisions. And computer vision unlocks new frontiers of automation and insight. It's an AI driven world that's not just on the horizon. It's already beginning to take shape all around us. As we've seen, artificial intelligence is already deeply woven into
Hanh: 00:16:34
the fabric of our daily lives. In business operations and the pace of AI innovation shows no signs of slowing down. So the question is, how can you as a business owner or professional prepare for this increasingly AI driven future? The first and most important step is to embrace a mindset of lifelong learning and adaptability. The reality is the skills and knowledge
Hanh: 00:16:59
that are valuable today may look very different even just a few years from now. So it's crucial that you and your team are committed to continuously upskilling and expanding your capabilities. Look for opportunities to learn about the latest AI tools and techniques. Whether that's through online courses, industry events, or simply reading up on the latest developments.
Hanh: 00:17:26
The more you can understand how AI works and how it's being applied in your field, the better equipped you'll be to leverage it effectively. And it's not just about learning the technical aspects of AI. It's also important to think about the human side of the equation. As AI becomes more prominent in our workplaces, it's We'll
Hanh: 00:17:47
need to develop the soft skills that allow us to work seamlessly alongside these intelligent systems. Things like critical thinking, problem solving, and emotional intelligence will become increasingly valuable as we navigate this new reality. On the organizational side, it's essential that you start laying the groundwork for AI integration within your business.
Hanh: 00:18:10
Consider conducting an AI readiness assessment to identify the specific pain points or inefficiencies in your operations that AI could help address. Maybe it's automating repetitive administrative tasks, enhancing your customer service capabilities, or optimizing your supply chain logistics by pinpointing the strategic use cases up front.
Hanh: 00:18:37
You can start building the foundation to unlock AI's transformative potential. And let's not forget the importance of upskilling your existing workforce. As AI becomes more prevalent, your employees will need to adapt and develop new skills to work effectively alongside these intelligent systems. Offering training programs, mentorship opportunities, And incentives for
Hanh: 00:19:03
continuous learning will be crucial for cultivating an AI ready team. You can also explore opportunities to connect with local universities, tech incubators, or industry groups that may offer AI adoption support programs for small and medium sized businesses. These partnerships can provide valuable resources, expertise, and even funding to help you
Hanh: 00:19:25
integrate AI into your operations. Of course, as AI's influence continues to grow, there will undoubtedly be concerns and ethical questions that need to be addressed. Issues around data privacy, algorithmic bias, and the displacement of human jobs will all require careful consideration and stakeholder engagement. But rather than shying away from
Hanh: 00:19:52
these challenges, I encourage you to lean in and be part of the solution. By staying informed, advocating for responsible AI development, and proactively addressing potential risks, You can help shape the future of this transformative technology in a way that benefits both your business and society as a whole. The bottom line is this, AI is
Hanh: 00:20:15
not the future, it's the present. And the organizations and individuals who embrace it, adapt to it, and leverage it strategically will be the ones who thrive in the years to come. So are you ready to be part of the AI revolution? As we've discussed, the rise of artificial intelligence presents tremendous opportunities for businesses and society
Hanh: 00:20:46
as a whole, but along with the exciting potential, there are also valid concerns. And, and ethical questions that need to be addressed. One of the most prominent issues is the impact of AI on employment in the workforce. There's a legitimate fear that as AI systems become more advanced, they could automate or displace a significant
Hanh: 00:21:09
number of human jobs, particularly those that involve repetitive routine tasks. However, the reality is that the relationship between AI and employment is much more nuanced. While certain job functions may become obsolete, AI will also create new types of jobs and roles that we can scarcely imagine today. The key is ensuring that we proactively
Hanh: 00:21:35
prepare the workforce for this transition. Investing in retraining and upskilling initiatives to help people adapt. Another major concern is around data privacy and algorithmic bias. As AI systems become more widely integrated into our everyday lives, there are valid worries about how our personal information is being collected, used, and safeguarded.
Hanh: 00:22:04
And if the data used to train these AI models is skewed or biased, It can lead to unfair or discriminatory outcomes. This is why it's so critical that organizations deploying AI solutions have robust data governance and security measures in place. Transparent policies around data usage, strict access controls, and ongoing audits for bias are all essential for building
Hanh: 00:22:28
trust and ensuring AI is used responsibly. The EU's recently proposed AI Act is aimed at establishing clear guidelines and regulations To ensure the responsible development and deployment of AI systems by addressing issues like data privacy, algorithmic fairness, and human oversight. This legislation aims to foster a trustworthy AI ecosystem. We're also seeing growing discussions
Hanh: 00:22:56
around the ethical considerations of AI, particularly as it relates to high stakes decision making in areas like health care, criminal justice. Thank you An autonomous transportation, how do we ensure the systems making fair, unbiased and accountable choices and who is ultimately responsible when things go wrong? These are complex nuance
Hanh: 00:23:22
questions without easy answers. But what's clear is that we need to approach the development and deployment of AI with a deep sense of ethical responsibility. That means engaging a diverse range of stakeholders, establishing clear guidelines and frameworks, and continuously monitoring the impact of these intelligent systems.
Hanh: 00:23:47
Fortunately, there are already organizations and initiatives working to tackle these challenges head on. Groups like the Partnership on AI, the IEE, and the European Union are all spearheading efforts to define principles and best practices for trustworthy, ethical AI. Ultimately, the rise of artificial intelligence is an inevitability.
Hanh: 00:24:08
But how we shape and steward this technology will be one of the defining challenges of our time. By approaching AI with a keen eye toward ethics, accountability, and the greater good, we can unlock its transformative potential while mitigating the risks. It won't be easy, But the rewards of getting it right are immense. So let's roll up our
Hanh: 00:24:29
sleeves and get to work. Well, there you have it a deep dive into the AI revolution. That's already here and shaping our daily lives. Both at home and in the workplace throughout our discussion, we've explored how artificial intelligence has become firmly integrated into the fabric of our modern world from the
Hanh: 00:24:54
smart devices we use every day to the A. I. Powered business solutions, transforming entire industries, we examined some of the most exciting emerging AI trends, including advancements in natural language processing, predictive analytics, and computer vision, and discuss how these technologies are poised to revolutionize the way we work and live.
Hanh: 00:25:21
Importantly, we also acknowledge the valid concerns and ethical questions surrounding AI issues around data privacy. Algorithmic bias and the displacement of human jobs. But we emphasize the critical importance of proactively addressing these challenges rather than shying away from them. But the reality is AI is not going anywhere.
Hanh: 00:25:45
In fact, it's only going to become more pervasive and influential in the years to come. So, the key is to embrace this technological transformation, prepare yourself and your organization for the changes ahead, and work to ensure AI is developed and deployed responsibly. If you're ready to take the next step in leveraging AI for
Hanh: 00:26:10
your business, sign up today. Feel free to reach out to me directly. I'd be happy to discuss how you can get started and connect you with the right resources and support because the AI revolution isn't just coming. It's already here. The question is, are you ready to be a part of it?
Narrator: 00:26:33
As we wrap AI50 Connect. Let's take a moment to reflect on the exhilarating journey we've just undertaken. We've explored the profound ways in which AI is already integrated into our daily lives, and the transformative potential it holds for the future. The insights shared today underscore the fact that AI is not merely
Narrator: 00:26:54
a technologist's talking point. It's a game changing force that's reshaping industries, reinventing business processes, and redefining what's possible. For leaders across all sectors, harnessing the power of AI is no longer optional. It's a strategic imperative. Imagine the possibilities. With AI as your ally, you can streamline operations, uncover hidden opportunities,
Narrator: 00:27:19
minimize errors, and empower your team to achieve extraordinary results. This isn't just about incremental improvement. It's about fundamentally reimagining what your business can achieve. At AI50, we're committed to being your trusted guide on this AI journey. Our mission is to equip you with the knowledge, strategies, and inspiration you
Narrator: 00:27:41
need to leverage AI for maximum impact. We make complex concepts accessible, actionable, and reliable. Curious about how AI50 can help you unleash the full potential of AI in your business? We're just a conversation away. Reach out to us and let's explore how we can transform your data into your most valuable asset.
Narrator: 00:28:03
To stay at the forefront of the AI revolution, be sure to connect with AI50 and Hanh Brown on LinkedIn. We're constantly sharing cutting edge insights, provocative ideas, and practical advice to help you navigate the AI landscape with confidence. Transcribed If you found value in today's episode, we invite you to hit the subscribe button on
Narrator: 00:28:22
your favorite podcast platform. We have a lineup of extraordinary guests and game changing ideas in store for you. For an even more immersive AI experience, check out our YouTube channel, where you'll find a treasure trove of engaging videos from podcast highlights to exclusive interviews with AI pioneers. Ready to put AI to work for your business? Let's talk.
Narrator: 00:28:46
We're here to help you harness the full potential of AI to drive smarter decisions, boost efficiency, and unleash innovation. Thank you for being a part of the AI50 community. As we conclude this episode, remember, with AI as your co pilot, you're not just keeping pace with change, you're driving it.
Narrator: 00:29:04
Embrace the revolution and let's build the future together. Until next time, keep learning, keep innovating, and keep pushing the boundaries of what's possible with AI.
Hanh: 00:00:05
AI isn't just about automation and optimization, it's also about creating more engaging and effective marketing content. With AI powered content optimization tools, businesses can analyze data on customer preferences and behavior to create content that resonates with their target audience. For example, let's say you're a
Hanh: 00:00:25
fitness brand trying to create a new blog post about healthy eating. With AI powered content optimization, you could analyze data on which topics and keywords are most popular among your target audience.
Narrator: 00:00:48
Welcome to AI50 Connect, your gateway to understanding the transformative power of AI for the baby boomer generation in business. Our host, Hanh Brown, specializes in demystifying AI and analytics, making them relatable and accessible to baby boomer entrepreneurs and leaders. In today's episode, Hanh will explore predictive analytics, AI powered chatbots,
Narrator: 00:01:13
and AI driven marketing automation, showcasing how these technologies can be leveraged to streamline operations, enhance decision making, and drive growth in businesses led by baby boomers. Hanh's insights will reveal the potential of AI to revolutionize the way baby boomers approach business, turning complex data into actionable strategies. Join us as we navigate the exciting
Narrator: 00:01:36
intersection of artificial intelligence and the rich experience of the baby boomer generation, unlocking new opportunities for innovation and success. Hanh, let's dive into the AI 50 connect.
Hanh: 00:01:57
Welcome to AI 50 connect. I'm Han Brown, your host. Today, we're focusing on AI Unleashed, boosting business for baby boomers. This episode is a nod to the baby boomer generation. The pioneers who've not only shaped historical milestones, but are now steering through the digital age's complexities.
Hanh: 00:02:19
As business owners, baby boomers are uniquely positioned to harness AI, merging decades of experience with cutting edge technology to redefine the business landscape. While these insights apply universally, we're zooming in on how baby boomers can lead this digital charge.
Transcribed by https: 00:02:38
otter. ai Blending their enduring legacy with the transformative power of AI. Let's delve into this exciting intersection of wisdom and innovation. Are you ready to unleash the incredible power of AI and analytics to take your business to new heights? This podcast is your gateway to understanding how AI can
Transcribed by https: 00:03:00
revolutionize your operations. Offering smarter decision making, unparalleled customer experiences, and unprecedented growth. Today, we'll delve into the world of predictive analytics, AI powered chatbots, and AI driven marketing automation. These technologies are not just about numbers and graphs, they're your crystal ball into the future of your business,
Transcribed by https: 00:03:22
simplifying complex processes and paving the way for success without needing a PhD. So, buckle up as we decode the magic of AI and analytics. Making it accessible and actionable for every seasoned entrepreneur and curious executive out there. So what exactly is predictive analytics? In a nutshell, it's using data, statistical algorithms, and
Transcribed by https: 00:03:59
machine learning techniques to identify the likelihood of future outcomes based on historical data. It's all about taking the data you already have and using it to make smarter decisions for your business. One of the biggest ways predictive analytics can help your business is by forecasting demand. Imagine being able to predict
Transcribed by https: 00:04:20
how much of a product you'll need in the coming months. Based on past sales data, customer behavior, and market trends. With predictive analytics, you can do just that. By analyzing all this data, you can create accurate demand forecasts. Which means you'll always have the right amount of stock on hand.
Transcribed by https: 00:04:42
No more running out of popular items or having too much inventory gathering dust on your shelves. But forecasting demand is just the tip of the iceberg. Predictive analytics can also help you optimize your inventory levels. By analyzing data on sales, shipping times, and supplier lead times, You can create a well oiled
Transcribed by https: 00:05:03
inventory management machine. You'll know exactly when to order more stock, how much to order, and even which suppliers are most likely to deliver on time. This not only helps you reduce costs by avoiding overstocking or stockouts, But also keeps your customers happy by ensuring you always have what they need when they need it.
Transcribed by https: 00:05:31
Now, I know what some of you might be thinking. This all sounds great, but how do I know if predictive analytics is right for my business? Well, let me give you a few real world examples. of companies that have used predictive analytics to improve their bottom line. Take Amazon, for instance.
Transcribed by https: 00:05:52
They use predictive analytics to forecast demand, optimize inventory, and even predict which products will be popular in the future. By analyzing customer data, including search queries, page views, and purchase history, Amazon can create highly accurate demand forecasts for millions of products. This not only helps them keep the right products in stock, but also
Transcribed by https: 00:06:18
enables them to offer faster shipping times and better customer service. Another great example is Coca Cola. They use predictive analytics to optimize their supply chain and reduce costs. By analyzing data on everything from weather patterns to social media sentiment, Coca Cola can predict demand for their products in different regions and adjust their production
Transcribed by https: 00:06:41
and distribution accordingly. This has helped them reduce waste, improve efficiency, and keep their customers happy. But the benefits of predictive analytics don't stop there. By using data to make smarter decisions, businesses can reduce costs, increase efficiency, and improve customer satisfaction.
Transcribed by https: 00:07:05
Predictive analytics can help you identify which customers are most likely to churn, so you can take proactive steps to keep them happy. It can also help you optimize your pricing strategy by analyzing data on competitor prices, such as, the Customer willingness to pay and market trends. In short, predictive analytics is a powerful tool that can help businesses
Transcribed by https: 00:07:29
of all sizes and industries make better decisions and improve their bottom line. And the best part? You don't need to be a math whiz or have a PhD, uh, in statistics to get started. There are plenty of user friendly tools and platforms out there. that make it easy to start using predictive analytics in your business. Now, let's take a closer look
Transcribed by https: 00:07:55
at what's happening under the hood of predictive analytics. At its core, predictive analytics relies on two main components. Data and algorithms. The data is what businesses collect about their customers, sales, inventory, and other key metrics. This data can come from a variety of sources, such as point of sale systems,
Transcribed by https: 00:08:22
customer relationship management, CIM, software, and even social media. The algorithms are what take all that data and turn it into meaningful insights and predictions. These algorithms use complex mathematical models to identify patterns and relationships in the data that might not be immediately obvious to the human eye. When we talk about predictive analytics,
Transcribed by https: 00:08:46
we're really talking about using different types of recipes or algorithms to predict what might happen in the future. Think of these like different ways to bake a cake. Each method giving you a unique result. Let's do a deep dive into these technical terms. First up is linear regression. Imagine you're trying to figure out how
Transcribed by https: 00:09:11
spending more on ads affects your sales. Linear regression is like drawing a straight line through all your past spending and sales data to predict future sales. Based on your ad spend. Then we have logistic regression. This one's a bit like flipping a coin, but much smarter. It helps us predict yes or no outcomes.
Transcribed by https: 00:09:36
For example, it can help guess whether a customer will stick with your service or decide to leave, which is super useful for keeping your customers happy and loyal. Now, let's talk about decision trees. Picture a branching tree. At each branch, You make a choice that leads you down a different path. Decision trees work similarly by mapping out the possible decisions
Transcribed by https: 00:10:03
and their outcomes, helping you make the best choice at each step. Lastly, there are neural networks inspired by how our human brain works. They're fantastic at recognizing patterns in heaps of data. Just like our brain learns from experience, neural networks learn from past data to make predictions. They're like the brainiacs of the
Transcribed by https: 00:10:24
algorithm world, great at spotting trends and making complex forecasts. So these are some of the tools we use in predictive analytics to help businesses make smarter decisions. They're like our crystal ball, giving us a glimpse into the future based on what we know today. But algorithms alone aren't enough to make predictive analytics work.
Transcribed by https: 00:10:50
Businesses also need to have the right infrastructure in place to collect, store, and process all that data. Once the data and algorithms are in place, businesses can start using predictive analytics to make more informed decisions. For example, a retailer might use predictive analytics to forecast demand for a particular product based on historical sales data, customer
Transcribed by https: 00:11:17
demographics, and even weather patterns. By accurately predicting demand, the retailer can optimize their inventory levels and avoid costly stock outs or overstocks. But the benefits of predictive analytics go beyond just demand forecasting. By analyzing customer data, businesses can also identify patterns and preferences that can help them tailor
Transcribed by https: 00:11:41
their marketing and sales strategies. For example, a bank might use predictive analytics to identify customers who are most likely to respond to a particular offer, like a low interest credit card or a high yield savings account. Thank you. Of course, implementing predictive analytics isn't without its challenges. One of the biggest challenges is ensuring
Transcribed by https: 00:12:04
the quality and accuracy of the data. If the data is incomplete, inconsistent, or biased, the predictions generated by the algorithms will be flawed. That's why businesses need to invest in data, governance, and quality control processes to ensure that their data is accurate and reliable. The benefits of predictive analytics are clear.
Transcribed by https: 00:12:31
By harnessing the power of data and algorithms, businesses can make more informed decisions. optimize their operations, and ultimately improve their bottom line. And as the volume and variety of data continues to grow, the possibilities for predictive analytics are only going to expand. With the right data, algorithms,
Transcribed by https: 00:12:51
and infrastructure in place, You can unlock valuable insights and make smarter, more confident decisions about the future of your business. Let's talk about a topic that's been buzzing in the world of customer service, AI powered chatbots. Now I know some of you might be thinking chatbots, aren't those just annoying pop ups on websites that
Transcribed by https: 00:13:21
never really helped me with anything, but hear me out because AI powered chatbots are a whole different ballgame. First off, let's define what we mean by AI powered chatbot. These are sophisticated computer programs that use artificial intelligence and natural language processing to understand and respond to customer inquiries. They can handle a wide range of tasks,
Transcribed by https: 00:13:50
from answering basic questions to helping customers troubleshoot problems, All without the need for human intervention. So, how can AI powered chatbots help your business? Well, one of the biggest advantages is that they can handle routine customer inquiries, freeing up your human agents to focus on more complex issues. Think about all the times a customer
Transcribed by https: 00:14:15
has reached out with a simple question, like what are your hours of operation? Or how do I reset my password? These are the types of inquiries that chatbots excel at handling. By automating these routine tasks, you can significantly reduce the workload on your customer service team. This means your human agents can spend more time tackling the tougher
Transcribed by https: 00:14:41
issues that require a personal touch. Plus, chatbots can work 24 7 so your customers can get help, even when your team is off the clock. Another big advantage of AI powered chatbots is that they can provide faster response times. We've all been there, waiting on hold for what feels like forever, only to have our call dropped or be told that we
Transcribed by https: 00:15:04
need to call back during business hours. Customers can get instant responses to their questions, no matter what time of day or night it is. This can be a huge relief for customers who are trying to solve a problem or make a purchase decision quickly. But the benefits don't stop there. AI powered chatbots. Can also help your business save
Transcribed by https: 00:15:27
money by automating routine tasks and providing faster response times. You can reduce the need for additional customer service staff. This can add up to significant cost savings over time, especially for businesses with high volumes of customer inquiries. Now, I know some of you might be thinking, but what about the human touch?
Transcribed by https: 00:15:53
Won't customers miss talking to a real person? And that's a valid concern. While chatbots can handle many tasks, there will always be situations where a human agent is needed. That's why it's important to have seamless handoffs between chatbots and human agents. The best AI powered chatbots
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are designed to recognize when a customer's inquiry is too complex for them to handle on their own. In these cases, the chatbot can quickly transfer the conversation to a human agent who can provide more personalized assistance. This ensures that customers always have access to the level of support they need, whether it's through a chatbot or a human.
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It's also important to remember that chatbots are not meant to replace human agents entirely. They're meant to work alongside them, handling the routine tasks, so that humans can focus on the more complex issues that require empathy, creativity, and problem solving skills. Another common concern about chatbots Is that they might make mistakes
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or provide inaccurate information. And while it's true that no technology is perfect, the best AI power chatbots are designed with multiple layers of error checking and human oversight. This helps ensure that customers are getting accurate, helpful responses to their inquiries. So how can you get started with AI power chatbots in your own business?
Transcribed by https: 00:17:27
The good news is that there are many options available from off the shelf solutions to custom built chatbots tailored to your specific needs. The key is to do your research and find a solution that fits your budget, your customer service goals, and your overall business strategy. One thing to keep in mind is that implementing an AI powered chatbot
Transcribed by https: 00:17:53
is not a one and done process. It requires ongoing training, monitoring, and optimization to ensure that it is providing the best possible experience for your customers. This means regularly reviewing chatbot transcripts, analyzing customer feedback, and making adjustments as needed. But the payoff can be huge. By automating routine tasks, providing
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faster response times, and In freeing up your human agents to focus on more complex issues, AI powered chatbots can help your business provide better, more efficient customer service, and in today's fast paced, always on world, that's a key differentiator that can set you apart from the competition. Let's understand what is behind these chatbots.
Transcribed by https: 00:18:50
At the heart of these chatbots are two key components. Natural Language Processing, NLP, and Machine Learning. NLP is what allows chatbots to understand and interpret human language, even when it's complex or colloquial. It breaks down sentences into their individual parts, like nouns, verbs, and adjectives.
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And looks for patterns and meanings. Machine learning, on the other hand, is what allows chatbots to get smarter over time. As a chatbot interacts with more and more customers, it can learn from those conversations and improve its responses. This is done through a process called training, where developers feed the chatbot large amounts of sample
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conversations and help it understand how to respond appropriately. One of the most exciting developments in chatbot technology is the rise of generative AI models, like GPT 3. These models can generate human like text based on a given prompt or context, allowing chatbots to engage in more natural, free flowing conversations. Instead of just pulling from a
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predefined script, generative AI chatbots can create unique responses on the fly, making the conversation feel more authentic and engaging. But even with all this advanced technology, chatbots still require human oversight and intervention. Developers need to regularly review chatbot transcripts to ensure that the responses are accurate, appropriate, and
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in line with the company's brand voice. They also need to be on hand to step in when a conversation gets too complex or sensitive for the chatbot to handle on its own. So, while AI powered chatbots are incredibly powerful tools, They're not a complete replacement for human customer service agents. Instead, they're best used as a
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complement to human agents handling the routine inquiries and freeing up humans to focus on the more nuanced, complex issues that require a personal touch. As you can see, the technology behind AI powered chatbots. Transcripts provided by Transcription Outsourcing, LLC. Faster and more efficient customer service by understanding the key components of
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NLP machine learning in generative AI. Businesses can make informed decisions about how to implement chatbots in a way that best serves their customers and their bottom line. There's something that's been making waves in the world of marketing, AI powered marketing automation. Now, I know some of you might be thinking AI in marketing?
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Isn't that just a bunch of robots trying to sell me stuff, but trust me, AI in marketing is so much more than that. First off, let's define what we mean by AI in marketing automation. Essentially, it's the use of artificial intelligence and machine learning, be one to automate and optimize marketing tasks and campaigns. This can include everything from
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email marketing and social media advertising, to marketing to content creation and website personalization. One of the biggest benefits of AI in marketing is that it can help businesses personalize their marketing efforts like never before. By analyzing customer data, such as demographics, behavior, and purchase history, AI algorithms can create
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highly targeted marketing messages that speak directly to each individual customer's needs and preferences. For example, let's say you're an online retailer selling clothing with AI powered marketing automation. You could analyze a customer's browsing and purchase history to create personalized product recommendations just for them.
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If a customer has a history of buying mostly athletic wear, your AI system could automatically suggest new workout gear or running shoes that they might like. But personalization is just the tip of the iceberg. AI can also help businesses target the right customers at the right time with the right message. By analyzing data on customer behavior
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and engagement, AI algorithms can predict which customers are most likely to convert and when they're most likely to make a purchase. This means that instead of blasting out generic marketing messages to everyone on your email You can create highly targeted campaigns. That reach the right people at the right time.
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This not only improves the effectiveness of your marketing efforts, but also helps you avoid annoying customers with irrelevant or poorly timed messages. Another way AI is transforming marketing is through dynamic pricing. By analyzing data on supply and demand, competitive pricing, and customer behavior, AI algorithms can automatically adjust prices in real
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time to maximize revenue and profits. Thanks. For example, let's say you're a hotel owner trying to fill rooms during a slow season. With AI powered dynamic pricing, you could automatically adjust your room rates based on factors like occupancy rates, competitor pricing, and even weather forecasts.
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This means you can offer lower prices during slow periods to attract more bookings while still maximizing revenue during peak seasons. But AI isn't just about automation and optimization. It's also about creating more engaging and effective marketing content with AI powered content optimization tools. Businesses can analyze data on customer
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preferences and behavior to create content that resonates with their target audience. For example, let's say you're a fitness brand trying to create a new blog post about healthy eating with AI powered content optimization. You could analyze data on which Topics and keywords are most popular among your target audience and use that information to create a post that's more
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likely to engage and convert readers. The benefits of AI in marketing are clear, increased conversion rates, higher customer engagement, and more efficient use of marketing budgets. By automating routine tasks and optimizing campaigns based on data, businesses can free up time and resources to focus on more strategic initiatives. But implementing AI in marketing
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isn't without its challenges. One of the biggest challenges is ensuring that the data used to train AI algorithms is accurate, unbiased, and representative of the target audience. If the data is flawed or biased, the insights and recommendations generated by the AI system will be flawed as well. Another challenge is integrating AI into existing marketing workflows and systems.
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Many businesses already have complex marketing tech stacks and adding AI into the mix can be a daunting task. It requires careful planning, testing, and training to ensure that the AI system is working seamlessly with other tools and platforms. Despite these challenges, the potential benefits of AI in marketing are simply too big to ignore.
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As customer expectations continue to rise and competition continues to intensify, businesses that don't embrace AI risk falling behind. So if you're a business owner looking to take your marketing to the next level, it's time to start exploring the world of AI powered marketing automation. With the right tools, data, and strategy in place, you can create
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more personalized, targeted, and effective marketing campaigns tools. That drive real business results, but don't just take my word for it. The proof is in the numbers. Studies have shown that businesses that use AI in their marketing, see an average of three times more leads and five times more sales than those that don't. And with the rapid advancements in
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AI technology, those numbers are only going to grow, whether you're a small business owner or a marketing executive, the At a large corporation. Now is the time to start exploring how AI can help you achieve your marketing goals and drive real business growth. Let's take a closer look at what's happening behind the scenes of AI powered marketing automation.
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At the heart of AI in marketing are two key components, data and algorithms. The data is what businesses collect about their customers, such as demographics, behavior, purchase history, and more. This data can come from a variety of sources, including website, analytics, social media, customer surveys, and even offline sources like in store purchases. Algorithms turn data into
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insights and tips we can use. They find patterns in the data using math and machine learning. This helps us see things that aren't obvious at first glance. In AI powered marketing, we use smart tools called algorithms. They help us understand customers better. First, we have clustering algorithms. Think of them as party planners.
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They group customers by interests. This helps tailor marketing to what people like. Next are predictive algorithms. They're like fortune tellers. They use past data to guess future actions, like buying or leaving. This helps keep customers happy. Then, recommendation algorithms act like thoughtful friends.
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They suggest products that customers will love. It makes shopping easier and more personalized. Lastly, optimization algorithms are the strategists. They tweak marketing campaigns in real time, aiming for the best results. They use data, like ad clicks, to improve campaigns and save money.
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These tools make marketing smarter and more connected to customers. It's all about using data to make better decisions. But algorithms alone aren't enough to make AI powered marketing work. Businesses also need to have the right infrastructure in place to collect, store, and process all of that data. This often involves investing in
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cloud based solutions and big data technologies that can handle the massive volumes of data generated by today's digital marketing campaigns. Once the data and algorithms are in place, businesses can start using AI to automate and optimize their marketing efforts. This can include everything from personalizing email campaigns and website content to optimizing ad
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targeting and bidding strategies. For example, let's say you're an e commerce business looking to improve your email marketing. With AI powered marketing automation, you could analyze customer data to create highly personalized email campaigns that feature products and offers tailored to each individual customer's interests and preferences.
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Or maybe you're a B2B company looking to optimize your lead generation efforts. With AI powered predictive analytics, you could analyze data on past leads, and And customers to identify the characteristics and behaviors that are most likely to result in a sale. You could then use that information to create the more targeted lead generation campaigns and sales outreach.
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Of course, implementing AI in marketing isn't without its challenges. One of the biggest challenges is ensuring the quality and accuracy of the data used to train the algorithms. If the data is incomplete, inconsistent, or biased, the insights and recommendations generated by the AI system will be flawed. Ensuring AI transparency is key.
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The system processes vast data using complex algorithms. This complexity can obscure its decision making for marketers. It's crucial for building trust, especially in sensitive areas like pricing and added targeting. Despite these challenges, the benefits of AI in marketing are simply too big to ignore.
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By automating routine tasks, optimizing campaigns based on data, and delivering more personalized and relevant marketing experiences, businesses can drive real results and stay ahead of the competition. So, if you're a business owner looking to take your marketing to the next level, it's time to start exploring the world of AI powered marketing automation. With the right data, algorithms,
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and infrastructure in place, you can unlock valuable insights and deliver marketing experiences that truly resonate with your customers. But as with any new technology, it's important to approach AI and marketing with a strategic and thoughtful approach. Take the time to understand your data, your customers, and your marketing goals, and work with experienced partners
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who can help guide you through the process with the right approach and the right tools, AI powered marketing automation can be a game changer for businesses of all sizes and industries. We've explored the mind boggling potential of predictive analytics. AI power chatbots and AI driven marketing automation as baby boomers. You've seen countless technological
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revolutions in your time, but this one is truly special. By embracing AI and analytics, you can take your business to heights you never thought possible. But remember, success isn't just about having the flashiest tools. It's about understanding your data. Your customers and your unique journey. So whether you're ready to dive in
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headfirst or just dipping your toes, know that the power to transform your business is within your grasp. Take a deep breath, trust in your experience and wisdom, and let's show the world what the baby boomer generation can achieve with the power of AI and analytics.
Narrator: 00:34:26
Our journey today on AI 50 Connect. Has been an exhilarating exploration of AI's impact, especially tailored for the baby boomer generation. Each insight and discovery has unveiled the vast potential of Ai. To revolutionize how we approach business and data. Think of Ai.
Narrator: 00:34:43
As the master key that unlocks unprecedented levels of data intelligence, driving a revolution in business acumen and efficiency. It's an invaluable tool for anyone in the business realm. Mhm. Offering the means to make decisions that are not just faster and smarter, but also more visionary.
Narrator: 00:35:00
Imagine the transformation within your business as AI streamlines operations, clarifies trends, minimizes errors, and invigorates your team, leading to not just growth, but a complete evolution of your business landscape. AI50 Connect isn't just a voice in the Vast Sea of Podcasts. We are your dedicated guides in the AI journey.
Narrator: 00:35:22
Committed to equipping you with bespoke AI and data strategies that ignite your vision and propel your business forward. Curious about how AI50 can revolutionize your business approach? We're here to chat. Let's collaborate to transform your data into a dynamic engine of strategy and innovation. Keep in touch with the pulse of AI through
Narrator: 00:35:41
AI50 on LinkedIn, where we continuously share the latest news, insights, and advancements in AI, ensuring you remain at the forefront of the AI evolution. Follow Hanh Brown on LinkedIn for a consistent flow of AI knowledge and trends, keeping you ahead in the dynamic world of AI. Be an active part of our AI50 Connect community by subscribing on
Narrator: 00:36:06
your preferred podcast platforms. Join us as we uncover the mysteries of AI, delivering expert insights directly to you. For a visual experience, visit us on YouTube, where we offer podcast summaries and exclusive interviews, providing a window into the AI universe. If you're poised to integrate AI into your business, AI50
Narrator: 00:36:27
is ready to ascend with you. Contact us, and together, we'll harness AI to redefine your business strategy. And operational efficiency. Thank you for joining AI50 Connect today. You're not just observing the AI revolution. You're leading it. Until our next episode, stay inquisitive, stay engaged and
Narrator: 00:36:45
lead the change with AI50. We eagerly anticipate embarking on the next phase of AI discovery with you.
Hanh: 00:00:05
Raise your hand if you wrestle with this dilemma before, whether for yourself or a loved one, that pivotal crossroads. Should I stay in my home as I grow older or move into a senior living community? It's one of the biggest decisions you'll ever face in the later chapters of life, and man does it come packaged with complex layers of emotion. On one side, you've got the
Hanh: 00:00:31
comfort, familiarity, and autonomy of aging in place. Staying rooted in the home that cradled a lifetime of memories. The sacred sanctuary where you raise kids. Loved ones gathered, traditions were built. There's this deep psychological pull to that environment, right? A sense of security control
Hanh: 00:00:54
and ego preservation in the four walls that know you best. So the prospect of leaving that behind can feel like a shattering. a fracture in your identity and sense of self as an independent person.
Narrator: 00:01:15
Welcome to the AI50 Connect podcast, where we address AI and its influences on businesses and daily lives. Today, we'll be exploring a different yet equally vital subject, navigating choices and challenges in the later years. While not directly related to artificial intelligence, this poignant topic represents one of the most profound chapters of AI50 Connect.
Narrator: 00:01:36
In the human experience, the realities of our aging populations, as societies evolve and life expectancies rise, we must confront the intricate emotional landscape surrounding the twilight years with profound wisdom and care. The later years bring a sea of profound choices and complex challenges where and how to live out this precious phase of life.
Narrator: 00:02:00
This delicate decision carries tremendous weight, shaped by fears, longings, and an innate desire for belonging. We'll navigate the soulful depths of senior living options with Hanh Brown as our guide. Moving beyond just practical logistics, we'll uncover the nuanced emotional dimensions that profoundly influence each decision.
Narrator: 00:02:21
From the comforting familiarity of lifelong surroundings to the embracing folds of care focused communities, every path is richly lined with meaning. This conversation honors the vast experience and hard won wisdom carried by our elders. It's about ensuring their twilight emanates dignity, cherished connection, and heartfelt joy.
Narrator: 00:02:43
Join us as we tread this sensitive terrain with empathy and reverence, amplifying the voices that truly matter most. Hanh, let's get started.
Hanh: 00:02:58
Hello and welcome. I'm Hanh, your host for today's episode, Older Adults Navigating the Choices and Challenges of the Later Years. Today we'll explore this topic with courage and compassion. We'll discuss affordability challenges, emotional complexities, innovative solutions. Whether you're considering aging in
Hanh: 00:03:18
place, moving in with family or exploring other options, this episode is for you. Thank you. We'll hear from inspiring individuals, redefining what it means to create a home as we age. We'll learn about groundbreaking ideas. Transforming the landscape of living well in later life. But more than anything, this
Hanh: 00:03:41
episode is an invitation. An invitation for you to become an agent of change. The challenges facing older adults are deeply personal to all of us. It will take all of us working together to create a society where every senior can thrive. With dignity, with purpose, with joy, let's open our hearts and minds.
Hanh: 00:04:09
Let's embark on this transformative journey together. You are not alone. We are here to support you every step of the way. We're here to talk about something deeply personal, something that touches all our lives. The journey of growing older, of watching our parents, grandparents,
Hanh: 00:04:33
friends, navigating their golden years. The It's a universal experience, one that brings both joy and struggle, memories cherished, but also hard choices faced, questions about living situations, about care, about maintaining independence, dignity, joy. This isn't just numbers and statistics. It cuts to the core of what matters most. How do we ensure our loved ones live
Hanh: 00:04:58
with comfort, respect, quality of life? That's the heart of living options for older adults today. The landscape is shifting rapidly, more options than ever for housing care services, but also escalating costs, complicated decisions around paying for it all. Do you renovate and stay put move to a retirement community, get in home support?
Hanh: 00:05:27
The choices can feel overwhelming, especially when combined with care needs. Memory care, skilled nursing, end of life services, these are sensitive issues. Emotional, financial, legal. How do families make informed choices amid it all? It's a kaleidoscope of stakeholders, too. Older adults, their loved ones, care providers, policy
Hanh: 00:05:52
makers, technology companies. We're all interconnected in this, but behind every number, every data point, there are human stories, stories of resilience, of families rallying together, honoring loved ones wishes as they grow older, like the daughter who became her mother's primary caregiver, managing medications, appointments, daily needs, all while raising her
Hanh: 00:06:16
own kids, holding down a job, or the husband and wife married 60 years. Determined to live independently at home as long as possible with help from caregivers. These stories humble us, remind us that living options for older adults isn't just about housing units and costs, it's about preserving humanity, respecting the individuals behind it all.
Hanh: 00:06:44
Technology and innovation are shifting the landscape too. Smart homes, monitoring health remotely, robotics supporting daily tasks, virtual reality for memory care. These advances could improve quality of life, help older adults age in place longer, reduce costs over time. But they raise ethical questions too. How do we ensure technology
Hanh: 00:07:08
prioritizes human connections, privacy, security, accessibility? We have to get it right. Put human needs first as we build the future of living options for older adults. No discussion of housing for older adults. It's complete without addressing the economic challenges many face. The retirement savings shortfalls, spiraling care costs, affordable,
Hanh: 00:07:43
high quality options out of reach. This isn't just about finances. It's about human dignity and equality. Every older adult deserves respect, quality care, regardless of means. Policymakers must step up. Individuals, employers, government all have a role because senior poverty is unacceptable in a just society. So where do we go from here?
Hanh: 00:08:10
How do we meet the challenges the human needs ahead? With courage, with innovation, but also compassion. By working together across sectors, bringing diverse voices to the table, listening to older adults perspectives as we shape the path forward. And by remembering why we're here, to uphold the humanity in the journey of
Hanh: 00:08:35
aging, to ensure our loved ones live their later years with grace, comfort, and joy. It won't be easy, but if we approach it with open hearts and minds, we can create a future of housing for older adults that honors us all. Let's get real for a moment. We're diving into some heavy topics here, issues that get complicated. Quickly.
Hanh: 00:09:06
But that's exactly why we need to talk about them. These seniors, they're our parents, grandparents, neighbors, our community. So we can't shy away from the hard stuff. We have to dig deeper, shine a light on root causes, on implications across society. This won't be surface level chatter. We're going in depth, pulling back
Hanh: 00:09:29
the curtain, getting raw, honest perspectives from those living it. Straight talk from older adults themselves, caregivers pushed to the brink, policy makers trying to solve crises. Yeah, it'll get emotional at times. Personal stories that hit home for many of us, glimpses into daily realities we may never see.
Hanh: 00:09:56
But that's exactly why we're here, to understand on a deeper level, to spark new mindsets, new dialogues about the way forward. We can't just treat aging as an afterthought anymore. We need concrete solutions for housing, care, cost, quality of life. So expect a no holds barred look at these issues.
Hanh: 00:10:20
The good, bad, and woefully overlooked in between. We'll examine potential reforms from every angle, ambitious alternatives being tested, big swings, and long range visions. Because older adults, they deserve our boldest thinking, our passion for change, for creating a future where we all can age with dignity, get ready to be challenged,
Hanh: 00:10:46
to feel outraged, but also to thrive. Hope, this is the start of an honest conversation, one long overdue. Let's talk about the affordability crisis in housing for older adults. This is one of those jaw dropping, gut punch realities, the kind that makes you question how we got here. How we let this happen, right under our noses, because the truth is, affordable,
Hanh: 00:11:19
quality senior housing is massively out of reach for millions of older Americans. Plain and simple. Yeah, we toss around words like crisis a lot these days, but when you see the actual numbers, you'll agree that term fits here. More than 10 million seniors today struggle to pay rent or mortgages. Let that statistic land for a moment.
Hanh: 00:11:45
10 million people are seniors, potentially homeless. Rents skyrocketed 50 to 100 percent in some areas since 2005, yet median income for households 65 plus is only around 45, 000. How does that math work exactly? See, here's the ugly reality we tend to overlook. Seniors typically live on fixed
Hanh: 00:12:10
incomes that barely budge over time. While housing costs keep climbing rapidly. So, for many, it means forfeiting other essentials. Cutting pills in half. Skipping meals. Shivering in underheated homes to save on bills. Just to keep roofs over their heads, to avoid the terror and undignified
Hanh: 00:12:35
conditions of homelessness. Can you imagine your grandparents in that situation? Of course not. No one would wish that on loved ones who worked hard their whole lives, yet that's the twisted reality for so many seniors today. Spending over half their income just on rent or mortgages,
Hanh: 00:12:56
making impossible trade offs. Now, pile on soaring health care, utility, and food costs too. It's a recipe for losing everything in retirement, for perpetual instability and fear. So what's causing this tidal wave? Years of public policy failures that failed to prioritize affordable senior housing.
Hanh: 00:13:18
It's that simple. Tax incentives allowed housing developers to chase higher profits. Building luxury units for affluent retirees instead of modest units for the masses. We let greed outpace human need in our housing system. Rules rigged so housing became a commodity, not a basic right for all.
Hanh: 00:13:40
Health issues also financially cripple many seniors. Medical debt haunting their final years, steep care costs, draining savings and assets. All this stems from systemic policy failures over decades. Mistakes piling up like compound interest. Look around your city. See those high rises filled
Hanh: 00:14:03
with vacant luxury condos? That's literally housing that could shelter our seniors. Instead, it's a harsh symbol of an upside down system, tilted away from those most in need of affordable homes. Does that sit right with you? It sure doesn't with me. Not when I think of seniors shivering in cold homes.
Hanh: 00:14:30
Or skipping medications just to stay housed because at its core, this affordability crisis robs our seniors of safety, health, and basic dignity in their later years. It forces impossible sacrifices on those who guided us, nurtured us, and supported us. Those who quite literally built the communities we live in.
Hanh: 00:14:54
So yeah, we need urgent solutions here. Policies to course correct decades of failure to make senior housing affordable again. But first we have to feel the human impact of this crisis. Allow that reality to shake us at our core to spark outrage and action because our seniors. They deserve far better than being
Hanh: 00:15:16
priced out of housing stability in the spirit years of life. We owe them so much more. Let's talk solutions for a minute here. CCRCs and reverse mortgages. Solving the cost of housing for older adults. These two biggies that always come up. Continuing care retirement communities and reverse mortgages.
Hanh: 00:15:46
Both position themselves as potential lifelines against the staggering costs of aging, pathways to financial stability, and long term care access. But are they all they're cracked up to be? Or are they just modern twists on the same old tricks of profiting off our seniors? Let's start with the CCRC model. You know, those massive campuses that offer Housing Plus care services?
Hanh: 00:16:15
The whole continuum of care thing on the surface. Yeah, CCRC seem like a smart concept for aging in place, independent living to start, then higher care levels when needed, all bundled into one community to simplify that progression, theoretically saving money versus piecing it together separately. Heck, some luxury CCRCs even
Hanh: 00:16:38
resemble swanky resorts. With spas, activities galore. The stuff of retirement dream brochures, right? But here's where reality kicks in. Those communities come at a massive price tag most can't afford. Entry fees alone can reach 1. 500k or more. Not just money, though.
Hanh: 00:17:04
That buy in often requires selling your home, too. Liquidating assets to fund the CCRC golden ticket, then you've got monthly fees, typically starting over 3, 000 and escalating sharply for higher care levels like assisted living. So unless you're just rolling in retirement cash, that CCRC lifestyle is merely an illusion
Hanh: 00:17:28
out of reach for the masses. Sure, the facilities are very nice. If you can afford them, but at what point do you question the basic ethics here? Are CCRCs really deploying care models for human good? Or just exploiting our fears about aging to rake in massive profits. It's a similar dynamic with reverse mortgages.
Hanh: 00:17:56
These loan products let seniors tap home equity for cash while still living there. Sound useful for paying expenses, right? A rare chance to age at home without the expense of assisted living? Well, yes. But only in the short term. You're still racking up debt fast, eating away at that home equity pot over time. So, reverse mortgages can help stretch
Hanh: 00:18:20
finances for a bit, but they're far from any permanent solution to America's elder care crisis. And getting a reverse mortgage is no cakewalk either. It's a maze of rules, fees, interest rates that can burn you hard. Plus, you're still responsible for taxes, insurance, repairs on that aging home as time goes on.
Hanh: 00:18:46
More costs hidden behind the curtain. Look, I'm not trying to be all doom and gloom here. Just laying out the realities. Many families face in paying for housing for their loved one, because throwing your life savings, home equity, your entire nest egg at short term band aids like these products, it only delays the inevitable affordability
Hanh: 00:19:12
crisis coming down the road when that money inevitably runs dry. Then what? So sure, CCRCs and reverse mortgages have their place for some affluent seniors, but they're not realistic solutions for the masses, if anything. They exemplify an elder care system rigged for profits over affordable, quality care access for all.
Hanh: 00:19:38
We can't keep kicking. That human can down the road any longer. It's time to finally overhaul this broken system from the ground up to explore bolder solutions not built on exploiting our loved one's fears about their final years. Our seniors deserve so much better. Let's talk about the choice aging at home or moving to a community, raise your hand.
Hanh: 00:20:08
If you wrestle with this dilemma before, whether for yourself or a loved one, that pivotal crossroads. Should I stay in my home as I grow older or move into a senior living community? It's one of the biggest decisions you'll ever face in the later chapters of life. And man, does it come packaged with complex layers of emotion. On one side, you've got the
Hanh: 00:20:33
comfort, familiarity, and autonomy of aging in place. Staying rooted in the home that cradled a lifetime of memories. The sacred sanctuary where you raise kids, loved ones gathered, traditions were built. There's this deep psychological pull to that environment, right? A sense of security, control,
Hanh: 00:20:56
and ego preservation in the four walls that know you best. So, the prospect of leaving that behind can feel like a shattering loss, a fracture in your identity and sense of self as an independent person, I get it, I really do. The home isn't just sticks and bricks, it's where you became you over all those decades, an extension of yourself,
Hanh: 00:21:21
which is why aging in place holds such powerful allure for so many seniors. A natural instinct to stay tethered to the familiar as long as humanly possible. We can't have this talk without addressing those big buts, too, because pursuing that path gets increasingly harder over time. Homes eventually become prohibitive money pits to maintain and modify for mobility needs.
Hanh: 00:21:54
The stairs, narrow hallways, lack of accommodations. Then there's the social isolation factor as neighbors move away. Local family spread across the country for jobs. Your world slowly constricting. And don't get me started on the stress and burnout risks for family caregivers trying to make aging
Hanh: 00:22:13
in place sustainable long term. That's an issue of its own we'll dive into. So while that independence is enticing, we have to recognize the compounded challenges too. The potential for loneliness, lack of social outlets, activities, which is where senior living communities can provide compelling alternatives.
Hanh: 00:22:35
and amenities to consider. These communities offer low maintenance living, scalable personal care, social integration, security, all in one safe, thriving neighborhood. No more home repairs, cooking, yard work. Just time to actually enjoy retirement how you envision, through activities, classes, trips with people your age. Some of the nicest communities these days
Hanh: 00:23:00
resemble all inclusive resorts, putting golf courses, Fitness centers, pools, all the amenities right at your fingertips. You can maintain your independence too in the right communities, well designed spaces, while getting a subtle level of personal care to make life easier. Now don't get me wrong, I'm not saying these communities are utopian fantasy lands either.
Hanh: 00:23:28
The quality spans a massive range as we all know. Some can feel more like holding pens or hospitals. There are more than enriching environments with institutional facilities and subpar care that should be criminal. That's why exploring any community's philosophy, care models, and staff culture is so vital.
Hanh: 00:23:49
You've got to do your homework as a family because, at their best, they're Well run communities can be priceless for an older adult's holistic well being, staving off depression, loneliness, rapid mental and physical decline. They offer safety, peace of mind, and engagement that home alone often cannot, as care needs increase over time. If you can navigate the cost, at least.
Hanh: 00:24:18
Which always leads us back to one of those fun realities. The prices of housing options for older adults these days. Am I right? Thousand upon thousands per month for those nice communities. Out of reach for many moderate or lower income households. Which is why for many families, the choice
Hanh: 00:24:37
becomes more about which sacrifices or compromises they're forced to accept. Do you burn through your assets and home equity to temporarily afford higher quality community living or do you make do and white knuckle it out through aging in place for as long as physically possible, slowly depleting resources. These are the punishing decisions no family should face.
Hanh: 00:25:06
But so many do, because here's the cold truth. There are no perfect solutions when it comes to this stage of life, just constantly shifting trade offs and prioritization exercises. Maybe it's me, but I can't help feeling we're failing as a society when these remain the best options available for our seniors.
Hanh: 00:25:27
But as a whole, the system is badly broken, from costs to market imbalances to fragmented care delivery. It's a massive structural problem, which is why I push all of you to get educated early on these issues. Do your research as families. Talk to real residents for honest insights, because this isn't just about which housing box to check.
Hanh: 00:25:52
It's about examining the pros, cons, and value propositions through an intensely personal lens. What environment will honor your goals, identities, and enrichment meets best in your truth years ahead? That's the guiding light to follow here. There's no universally right answer, just the path forward that stays truest to who you are and how you want to live
Hanh: 00:26:13
out this final chapter on your own terms. So, keep asking questions, speak up about what you need and value before making this transition, whenever it comes. Because this deeply personal choice, it'll set the tone for your life's greatest experiences and memories still ahead. Let's go to the darkest truth about housing for older adults. Okay, it is extremely uncomfortable, but
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crucial place with this conversation. A place that may shatter some illusions about where we're really at as a society. Because for as much as we extol things like honoring our seniors and celebrating long lives well lived, the brutal reality is that elder abuse and discrimination remain utterly jarring epidemics. Yeah, I know, it's grim stuff we try to avoid thinking about.
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Bearing our heads, pretending it's just flu cases or isolated incidents. Anything to keep up appearances, but the numbers tell a different story. One that should make us absolutely sick to our cores with outrage, guilt, and shame. Nearly 1 in 10 seniors face some form of abuse or neglect annually in the United States alone. Let that statistic sear itself
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into your mind for a moment. We're talking millions of older adults each year enduring physical mistreatment, sexual assault, emotional anguish. Financial exploitation by the very people they depend on, often at the hands of their own loved ones or caretakers, in sickening betrayals of trust and human dignity. It's utterly gut wrenching to confront,
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but we cannot flinch or shy away from this ugly truth any longer. Our willful ignorance and inaction has nurtured this systemic crisis for far too long. The signs are all around us if we just open our eyes, like the skyrocketing rates of seniors being admitted for injuries from care facility neglect, or seniors showing up in
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ERs malnourished, dehydrated, with preventable bed sores and infections from substandard assisted living conditions. These aren't isolated cases, folks. They're chilling indicators of how deeply this abuse crisis runs through housing and care systems nationwide. And you know the most disturbing part? How normalized and entrenched these human rights violations against
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seniors have become in our societies. We've cultivated cultures of indifference, of turning blind eyes to even the most abhorrent mistreatment of aging adults happening openly all around us. Are seniors being belittled, robbed, left in their own filth, suffering alone in plain sight, chalked up as the unavoidable ugliness of growing old? Well, I'm sorry, but no,
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absolutely none of this should be acceptable or tolerated, period. Not in any society with human decency as its core value. Because make no mistake, this widespread abuse is but the ultimate symptom of how profoundly our society devalues and discriminates against older adults. From workplace ageism, sabotaging careers, and financial security, to outright
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rationing of healthcare and support services based on age, to dismissive attitudes painting all seniors with demographics based stereotypes of frailty. or irrelevance. It's a multi layered bigoted reality. One that systemically robs millions of the basic dignity, autonomy, and human rights they're entitled to across their full lifespan.
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No exceptions. So when we talk about choices in housing for older adults, the sad truth is too many of our seniors are being forced into unthinkable scenarios By these converging crises, like the staggering numbers entering into poverty and homelessness later in life due to financial insecurity, discrimination, and drain resources for them.
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The choice is between destitution or suffering the indignities of under regulated profit obsessed senior care facilities. Talk about a rock and a hard place. Then you have seniors choosing to remain in dangerously isolating or abusive home situations. Out of pride, fear, or lack of any better options.
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While still, others resign themselves to placement in wretched institutional facilities, simply to have any roof over their heads at all as the years dwindle. These agonizing decisions no person should ever have to face are playing out every single day across this country. Replicated in millions of hushed stories. So, if these realities don't stir a profound sense of moral conviction in
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you, to finally take action, to spark seismic reforms, I don't know what will. Because this systemic indignity, this greed driven normalization of dehumanizing our seniors, It renders hollow every last value we profess to uphold, justice, compassion, integrity, mere lip service in a society utterly failing its most vulnerable and venerable population in real terms.
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But we have the power to finally break these cycles, to course correct from generations of shameful wrongs and willful negligence. It starts by raising our voices collectively in outrage. Over the ubiquity of elder abuse and age discrimination in all its dehumanizing forms. By casting harsh light on the deep rooted,
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intersecting policy failures allowing these crises to fester and grow more acute over decades, and by demanding new frameworks for housing, care, and societal integration that place human dignity and thriving, not profits, As the inviolable priority, we're safe, enriching, and to compassionate living environments aren't just exclusive luxuries for the few, but guaranteed
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basic rights for every older adult. Rights baked into policies, funding streams, community designs, and cultural values, elevating rather than discarding our seniors from equal stakes in society. It's an utterly transformative paradigm shift from where we are today. One necessitating bold, sustained action across all sectors over years, but a change that must start right here, right
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now with a profound refusal to accept anything less than comprehensive reforms. Our seniors deserve no less than our fullest conviction to ensuring their final chapters unfold with utmost respect, security, and celebrated quality of life. No caveats, compromises, or deferring that obligation to someday down the line when it's too late for so many already suffering.
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This is the ultimate test of our humanity and conscience as a society. One demanding we finally start treating our seniors as precious and equals, not problems. Let's move on to dementia care. Preserving identity and human connections. Close your eyes for a moment. Imagine gradually losing your grip on reality.
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Your most cherished memories, amplified whispers fading away. The people, places, core experiences that shaped your unique identity, day by day, becoming unrecognizable as that lifelong connection to self, to essence, slowly frays. For millions of older adults and families, this heart rending journey into cognitive decline isn't just a hypothetical,
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it's a mourned reality playing out in slow, agonizing progression. Dementia, a cruel fracturing of the mind and spirit, one that can leave even our most vibrant loved ones bafflingly adrift in the final years. So if that visualization essence guts you even a little as it does me, then let it purify our resolve to fundamentally rethinking how we approach dementia
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care because the traditional models of warehousing these individuals. Allowing identity erosion? Well, that path is rooted in systemic dehumanization. We can no longer accept. When someone develops dementia, it doesn't erase their cellular makeup as a human being deserving utmost dignity, connection, and selfhood.
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For however long days remain, yet far too often, our approach has been to systemically extinguish personhood at first symptom, stripping seniors of their right to recognize themselves in secure, enriching environments. Instead, we shuffle them into facilities, treating cognitive decline as one size fits all diseases. To merely subdue and medicate
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into bland, passive, existing. Can you imagine anything more desolate and undignified than being unseen and unacknowledged as your true self in those final years? Weeks, days, well I for one refuse to accept that as an adequate or moral endgame for how we care for those with dementia. As a society, we must finally
Hanh: 00:36:15
draw that bright human line. And thankfully, an inspiring renaissance is taking root across pockets of the care world. A grassroots paradigm shift, putting personhood and human connections at First, in dementia care, it's a beautiful concept centered on preserving the individual's spark memories, experiences, spirit through highly
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customized, multi sensory approaches. In these models, care teams deeply study each person's lifelong histories, interests, identities through intensive biography work to create individualized care plans. So, instead of standardized routines in sterile halls, It's dynamic, sensory rich activities synced directly to each person's core selfhood and
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memory triggers, like creating an immersive 1, 950 S styled household for someone who lived through that era, personalized to their lived experiences and ability levels. or filling a room's sounds, smells, and decor with elements from the person's treasured cultural identity or occupational background as anchors. These programs arc based therapies
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and sensory cues on sustained identity preservation as dementia progresses, never losing sight of who each person innately is and was, and the human impact It's utterly night and day from those heartbreaking images of hollowed, unstimulated souls in corrido warehouses we've allowed. Person centered dementia care cultivates engagement, joy, human connections
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in ways standardized models cannot. In these environments, you'll encounter vibrant laughter, movement, presence from seniors reveling in immersive settings. The contrasting humanity and quality of life is so palpable, you're left wondering, why on earth did it take this long for such enlightened care philosophies to emerge? Well, the grim answer has been
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our society's historically low prioritization of dementia care overall. Our willful detachment and underfunding of it. After all, these person centered programs cost exponentially more to develop and operate than standard nursing homes. They're incredibly staff intensive, which is precisely why we can no longer allow finances or bureaucratic inertia to
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justify substandard, dehumanizing dementia care models persisting any longer. Our own loved ones facing this diagnosis deserve to be prioritized. With utmost urgency for the highest achievable care aimed at preserving their identities, not just in pockets of innovation or for those who can afford lavish arrangements, but as a guaranteed human and societal duty to all.
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It's a cresting paradigm shift as crucial as any human rights reformation. One elevating the basic dignity of dementia care from afterthought to inviolable priority. An evolution is already underway, but gasping for oxygen from public funding, workplace policies accommodating caregivers, and broader community education.
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So I implore all of us to dig deeper on this front, to get educated on what person centered dementia care truly embodies at the Crook standard, then to activate around advancing those pioneering models into mandated care norms. Not just in specialized private homes, but society wide. This is our chance to get it right for once.
Hanh: 00:40:16
To honor the human worth of every person navigating dementia's cruel progression until their certainty end. With courage rooted in morality over economic constraints, we can universally enshrine identity and human connection as cornerstones of the dementia care experience. So, when that diagnosis, Dage, comes for our own parents, loved ones, potentially
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even ourselves someday, we uphold their truest essence amid the falter years, that fleeting opportunity to move them, soothe them, and let their core identities resonate fully until those interior lights do not extinguish. It's the ultimate demonstration of love rooted in unflinching humanity, a societal right we can't afford to get wrong any longer.
Hanh: 00:41:10
Alongside the housing affordability crisis, older adults face another dire issue that demands our attention. The silent epidemic of elder abuse. Well, we have previously discussed its surface. The complexities and nuances of elder abuse warrant a closer examination. I want you to picture someone you cherish deeply.
Hanh: 00:41:34
A grandparent, parent, mentor, any elder who's touched your life profoundly. Hold that person's image vividly in your mind. Now imagine, discovering they've been subjected to unspeakable abuses. Physical assaults, leaving them battered and bloody, sexual violations, stripping away their dignity, willful neglect of basic human needs
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like food, hygiene, medical care. The sheer horror and rage you'd feel? Multiply it by millions. Because that's the scale of the silent epidemic raging across communities today. Elder abuse isn't just some abstract concept or occasional headline. It's a pervasive human rights crisis hiding in plain sight, scarring the bodies, minds, and souls of
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our most vulnerable population. The statistics are gutting. Over 5 million older Americans abuse each year. One study finding 24. 3 percent of residents sampled experiencing at least one instance of physical abuse while in a nursing home. And those are just the reported cases in a system.
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Notorious for obscuring the true depth and severity of this violence. Countless more suffering in silence, unseen. Behind each number, a human being subjected to unfathomable trauma and indignity at the hands of their supposed caregivers. Bruises and bed sores. Malnutrition and medication errors.
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Forced isolation and squalid living conditions. This is the gruesome reality festering behind those sterilized facility facades. We entrust with our seniors care, a shame on us all for allowing it to metastasize this long unchecked, but how did we get to this harrowing point as a society where the systemic abuse of our seniors became a normalized epidemic?
Hanh: 00:43:39
Just another sad inevitability of aging. The grim truth lies in a toxic cocktail of factors. Grossly inadequate regulation and oversight of the long term care industry, chronic understaffing, and under training of workers. Cultures of silence and cover up within facilities. Let's start with the regulatory failures.
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Despite nursing homes being entrusted with the health and safety of acutely vulnerable adults, accountability is appallingly lax. Inspection processes are piecemeal. Penalties for violations, often a mere slap on the wrist. Enforcement mechanisms have no teeth, leaving facilities to flout standards with impunity.
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The result? A patchwork system stacked to prioritize cost cutting and profit margins over the most basic human dignity and welfare of residents, where abuse festers in the cracks. And understaffing? Don't even get me started. The reality is, many nursing homes operate on bare bones personnel
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stretched impossibly thin. Leaving gaping holes in care and supervision. Overwhelmed, under trained workers resort to dangerous shortcuts. Rough handling, even willful neglect of residents essential needs. All stemming from staffing levels not fit for purpose. Then, there's the wall of silence.
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The unwritten code among too many facilities to conceal rather than confront abuse head on. Whistleblowers ignored or retaliated against viciously claims of mistreatment buried in bureaucracy families stonewalled or placated with empty assurances a maddening culture of self preservation over human life. These intersecting failures have
Hanh: 00:45:35
nurtured a perfect storm for elder abuse atrocities occurring daily without restraint or reprisal behind those deceptively manicured facility grounds. So make no mistake, this is a full blown human rights catastrophe demanding nothing less than complete systemic upheaval, radical uncompromising reform in how we regulate, staff, and culturally transform elder care.
Hanh: 00:46:04
It starts with enacting ironclad federal standards for all nursing homes, comprehensive guidelines governing everything from staffing ratios to abuse prevention protocols, vigorously enforced through rigorous inspection and hefty violation penalties. We need a total overhaul of hiring and training practices industry wide, exhaustive background
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checks, intensive training in abuse prevention and reporting. A new baseline for workforce quality and accountability, anonymous reporting hotlines, and ironclad protections must be instituted for staff, residents, and families to safely come forward about abuse without fear. Whistleblower retaliation outlawed and prosecuted to the fullest extent.
Hanh: 00:46:52
Then there's the deepest work of shifting toxic institutional cultures. Replacing secrecy and neglect with ironclad ethics of safety, dignity, and compassion for residents as the inviolable norm. This is going to take a Herculean united push from all of us. Advocating relentlessly to policy makers for landmark reforms.
Hanh: 00:47:16
Partnering as families and advocates to whole facilities and communities. Mercilessly, accountable, demanding a complete paradigm shift in how we conceive of and deliver elder care. Because until we approach this as the human rights emergency, it is, the abuse will only continue to fester more vulnerable seniors, degraded, traumatized, lives destroyed or ended.
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This is our defining test as a society. To decide if we truly value the inherent dignity and worth of those who cared for us in our own vulnerable years, or if we'll keep betraying that trust. The reform path forward is clear, the moral imperative undeniable. It's on us to finally heed the silent cries of our abused seniors and act today, not tomorrow.
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To say with the full might of law, culture, and conscience. Never again will we allow our most vulnerable to be violated. In nursing homes or anywhere, your pain ends now. Only then can we begin to expiate the societal shame to forge a future where all seniors receive the reverent care and protection they deserve as a birthright.
Hanh: 00:48:36
No exceptions. The most important endeavor we could ever undertake for our loved ones and the fearful unknowns in our own aging. It starts with me and you. Now, let's get to work. Now, we're moving on to reverse mortgages. A double edged sword for seniors. Picture this scenario. You've reached your golden years,
Hanh: 00:49:03
but find yourself house rich and cash poor, struggling to cover basic living expenses on a fixed income. Sound familiar to anyone? It's a predicament faced by millions of older Americans. Equity? Tied up in homes? They've spent lifetimes paying off, yet tapping it seems an impossible labyrinth.
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Enter the reverse mortgage. On the surface, it sounds almost too good to be true, right? Convert that idle home equity into tax free cash without selling or moving. Supplement retirement income by simply deferring repayment until you pass away or relocate. Suddenly, those mounting medical bills Needed home modifications,
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even bucket list dreams, seem within reach, all while remaining comfortably rooted in your family home. What's the catch? You might be thinking. As with most financial products targeting seniors, The devil is in the details, and those details can carry significant, often poorly understood implications for your estate and heirs down the line.
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You see, reverse mortgages are essentially rising debt loans. Each payment you receive adds to your loan balance. With compounding interest rates silently ballooning what you owe each month, fail to maintain the property or fall behind on property taxes or insurance. That's a contractual default potentially triggering immediate loan repayment.
Hanh: 00:50:43
Then, there is what happens to any remaining equity after you pass on. The loan balance gets settled first before heirs can inherit the property, if there's anything left. In far too many cases, reverse mortgages wind up eroding, if not wiping out that core source of generational wealth, leaving children and grandchildren grappling with evaporated inheritance.
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Now, this isn't to say reverse mortgages are inherently predatory or without valid use cases. For some cash strapped seniors, it can be a vital lifeline to afford aging, in place when no other options exist. The problem lies in how they're often sold to vulnerable seniors, glossy brochures touting newfound financial freedom and security, while glossing
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over the long term debt ramifications. Thanks. Worse yet, reports abound of brokers preying on cognitively impaired seniors, pressuring them into loans they scarcely understand, saddling them with ruinous terms that jeopardize everything they've worked for. So how do we protect our loved ones from falling victim to
Hanh: 00:52:01
reverse mortgage pitfalls? It starts with arming ourselves with clear eyed knowledge of exactly how these loans can impact our finances and estates. If you or a family member are considering a reverse mortgage, it's absolutely crucial to consult with a trusted financial advisor or elder law attorney first, someone who can objectively break down your
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unique situation and long term goals. Run the numbers on worst case scenarios. What happens if you exhaust your loan payments and still have years of living costs ahead? How much debt would, could you be leaving your spouse or family to settle? Is a lump sum or structured payment plan wiser? Don't let slick sales pitches
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make the decision for you. Weigh the full legal and financial implications against other options like downsizing or cashing out investments first. If you do proceed with a reverse mortgage, have an attorney review every line of that contract with a magnifying glass. Ensure you clearly understand your obligations and the consequences
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of default before signing anything. And most importantly, involve your whole family in the decision making process early on. Have candid discussions about how a reverse mortgage could impact inheritance and estates. Make contingency plans together. Because at the end of the day, this decision doesn't just affect you.
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It ripples out to the financial security of those you love most, your children and grandchildren who stand to inherit the fruits of your life's labors. That's not to say their inheritance should necessarily come before your own needs and quality of life. in your final years. But they deserve a voice and clear understanding of how this choice
Hanh: 00:54:01
could shape their own futures. Ultimately, the decision to take on a reverse mortgage is a deeply personal one with no universally right answer. It depends on your unique financial picture, family dynamics, and values around legacies. The key is to approach it with eyes wide open, to fully educate yourself on the mechanics and implications, not
Hanh: 00:54:25
just for you, but for your family tree. To make this choice purposefully, not under duress or false assurances. Because your home equity, it's not just a number on paper, it's often your most sacred asset. The physical embodiment of a lifetime of work, memories, and love. And how you leverage it matters immensely. So if you're grappling with this
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decision, know that you're not alone. This is the ultimate conversation so many seniors wrestle with as they navigate the financial unknowns of longevity. But by being proactive, seeking trusted guidance, and involving your family every step of the way, you can make the most informed, clear eyed choice for your specific needs and goals. One that balances your own financial
Hanh: 00:55:18
security and dignity with preserving the legacy you've spent a lifetime building for those you hold most dear. A legacy of love, wisdom, and generational wealth in all its forms. Imagine you are considering a reverse mortgage to fund your housing expenses. What factors would influence your decision? That's the heart of
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conscious estate planning. Ensuring your final chapters unfold on your terms. While still safeguarding the seeds you've planted for generations to come, and it's never too early or late to start, let's transition to a topic that is often difficult but necessary to address, navigating end of life decisions. I want you to take a moment and
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reflect on the most profound question we all face as mortal beings. How do you want to live out your final days when that time comes? It's a question that strikes at the very core of our humanity, one that forces us to confront our deepest values, fears, and hopes about what makes a life worth living. And a death worth dying.
Hanh: 00:56:37
And yet, it's a conversation we so often avoid, like the plague, pushing it off as some distant hypothetical for another day, another version of ourselves. But the truth is, none of us are promised tomorrow. The time to grapple with these weighty questions is now, while we still have the clarity and autonomy to make our voices heard.
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To advocate for our most sacred right to die with dignity on our own terms, because make no mistake, end of life decisions are the ultimate expression of personal sovereignty. The fundamental human right to chart our own life's course right up until the very end, but far too often that right gets stripped away amidst the chaos and emotion of a health crisis.
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Family members left guessing at their loved one's wishes. Medical team defaulting to maximum interventions. It's a recipe for robbing individuals of their most basic agency when they're already at their most vulnerable. Subjecting them to invasive treatments and diminished quality of life they may never have wanted.
Hanh: 00:57:49
That's why the single greatest gift The best advice you can give yourself and your loved ones is to make your end of life preferences known in writing and in candid conversations with those who matter most. It starts with educating yourself on the full spectrum of medical decisions that may arise. CPR, mechanical ventilation, feeding tubes.
Hanh: 00:58:15
These are just some of the realities you may face. But this isn't just about medical procedures. It's about deeply examining your core values and beliefs. What level of physical and cognitive function would you find acceptable? What treatments align with your goals and philosophy?
Hanh: 00:58:35
There's no universal right answer. Some may prioritize prolonging life at all costs, while others prize comfort and natural passing above heroic interventions. The key is to discern what matters most to you. Once you've gained that clarity, it's time to codify those wishes through legal instruments, like
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advanced directives and living wills. Think of these as love letters to your future self and family, a way to make your voice indelibly heard. Even if you can no longer speak for yourself, to spare your loved ones the anguish of agonizing over what you would have wanted. But simply having documents isn't enough. The real power lies in the courageous
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conversations you initiate with your inner circle about your end of life philosophy. Share with them your hopes and fears, your non negotiables, and open questions. Welcome their own reflections and concerns. Create a shared understanding that can guide them if they're ever called to advocate on your behalf. And if you find yourself in the role
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of surrogate decision maker for a loved one, honor their wishes with the same conviction you'd want shown to your own. Even if it means letting go when every fiber of your being wants to hold on, because that's the essence of respecting autonomy. Recognizing that each of us is the ultimate arbiter of what a good life and good death mean to us.
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It's not about imposing our own beliefs, but upholding theirs. Now this isn't to oversimplify the profound ethical complexity surrounding end of life care. Debates rage on about the delicate balance between preserving life and alleviating suffering. Questions of when, if ever, withdrawing treatment or even physician aid
Hanh: 01:00:33
in dying can be morally justified. Of how to weigh individual autonomy against societal impacts and the integrity of the medical profession. These are the thorniest of philosophical quandaries with no easy answers. They require ongoing, rigorous dialogue among ethicists, policy makers, spiritual leaders, and medical professionals. But at the heart of it all must be a
Hanh: 01:00:59
commitment to honor the intrinsic human right to self determination, to empower individuals with the information, tools, and platforms to make their values known. So that no one faces their final passage feeling powerless or voiceless, stripped of their most basic agency and identity in the face of systems more concerned with heartbeats than human dignity. The way we die reflects the way we live.
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It's the ultimate mirror held up to a society's deepest values and priorities. And we have a long way to go to build a culture of dying that truly reveres autonomy. But it can start with each of us. Right here. Right now. By courageously embracing these conversations in our own lives,
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normalizing death not as some unspeakable taboo, but as life's most sacred rite of passage. One that challenges us to distill our most authentic essence and deepest priorities. And to fight for a future where everyone gets to live and die in alignment with their truest self. That's the transformative power of end of life planning.
Hanh: 01:02:18
The ultimate act of self actualization and love for those we hold most dear. A legacy that transcends any inheritance. So don't wait for a crisis to force the issue. Start the conversation today. And those you cherish advocate for policies and systems that empower everyone's right to a dignified death. It won't be easy.
Hanh: 01:02:45
It'll require facing our deepest fears and vulnerabilities head on, but there's no more important endeavor than claiming our most fundamental human right to author our own life story right up until the very end, as we confront the challenges faced by older adults. We must also address another pressing issue that demands our attention.
Hanh: 01:03:14
The caregiving crisis, a clarion call for transformative change. Picture this, you spent your whole life pouring your heart and soul into caring for others. Raising children, tending to aging parents, being the rock of your family. And now, as you enter your own golden years, you find yourself on the other side of the equation.
Hanh: 01:03:39
In need of care and support yourself, you'd think that after a lifetime of giving society would ensure a soft place for you to land, right? Caregivers who are valued, supported, and equipped to provide the quality, compassionate care you deserve. Well, I hate to be the bearer of harsh reality, but that's far from the truth. The fact is we're hurtling towards a
Hanh: 01:04:02
caregiving crisis of epidemic proportions, a perfect storm of demographic shifts. economic realities, and policy failures that threaten to leave millions of seniors without the care they need to live with dignity. Let's start with the numbers. By 2030, all baby boomers will be over 65, meaning 1 in 5 U. S.
Hanh: 01:04:28
citizens will be of retirement age. And as lifespans continue to increase, more and more seniors are living with chronic conditions and disabilities that require intensive long term care. But here's the kicker. There is a massive shortage of caregivers to meet this skyrocketing demand. In fact, estimates suggest that by 2040, there will be 11 million unfilled
Hanh: 01:04:55
caregiver positions in America. 11 million seniors potentially left without the care and support they need to age with quality of life. And this isn't just a numbers game. It's a human rights crisis. But how did we get here? How do we allow such a critical role in society, the caring for our most vulnerable to reach a breaking point?
Hanh: 01:05:20
The answer lies in a toxic cocktail of factors. That have long undervalued and unsupported caregiving labor. For starters, caregiving has historically been viewed as women's work. Unpaid labor that's taken for granted as a natural extension of family roles. And even when it is paid, it's often minimum wage work without
Hanh: 01:05:43
benefits, job security, or opportunities for advancement. The message this sends is clear. Caregiving isn't real work deserving of real economic value. Nevermind that it's absolutely essential to the functioning of our entire society. But the financial piece is just the tip of the iceberg. Caregiving is also emotionally and
Hanh: 01:06:06
physically demanding labor that takes a heavy toll on those providing it. Burnout, stress, and health issues are rampant among caregivers who often sacrifice their own well being for others. And for family caregivers, juggling work and other responsibilities? The burden can be crushing. In fact, one in five family caregivers have left the workforce entirely
Hanh: 01:06:33
to provide care, putting their own financial futures at risk. Now, let's zero in on caregiving in nursing homes, where these challenges reach a fever pitch. The reality is that many nursing homes are chronically understaffed. Leaving caregivers stretched to the breaking point and residents suffering the consequences.
Hanh: 01:06:55
Federal regulations require a minimum staffing ratio of 4. 1 hours per resident per day for long stay units. But even that is considered woefully inadequate by experts. And it's not being met consistently. In fact, studies show that staffing levels can vary wildly from day to day and shift to shift.
Hanh: 01:07:19
The result? Caregivers forced to rush through tasks, cut corners, and prioritize efficiency over human connection. Residents left waiting for basic needs. Like toileting, feeding, and repositioning higher rates of pressure, ulcers, malnutrition, falls, and preventable hospitalizations. And here's where the story takes an
Hanh: 01:07:42
even darker turn because behind these staffing challenges lies a broken business model that puts profits over people. The vast majority of nursing homes are for profit entities beholden to investors and shareholders. And in the relentless drive to maximize margins, caregiver wages and benefits are often the first on the chopping block. It's a vicious cycle.
Hanh: 01:08:09
Low pay and the poor working conditions lead to high turnover and difficulty attracting qualified staff, which leads to even more understaffing and burnout, all while residents pay the ultimate price in substandard care. And let's be clear, this isn't just an economic issue. It's a moral failing of the highest order because when we allow a system to persist
Hanh: 01:08:36
that devalues and degrades those doing the sacred work of caregiving, we erode the very humanity of those they serve. But here's the good news. It doesn't have to be this way. We have the power to write a different story. To create a future where caregiving is valued as the skilled essential labor it is, where caregivers are
Hanh: 01:08:56
supported, empowered, and equipped to provide the highest quality care. And it starts with bold policy solutions, like increasing Medicaid reimbursement rates for nursing homes with the requirement that those funds go directly to staffing and care improvements. Like mandating higher minimum staffing ratios. and imposing stiff
Hanh: 01:09:20
penalties for noncompliance. Like providing tuition assistance and career ladders for caregivers to increase their skills and earning potential. Like ensuring pay family and medical leave so caregivers don't have to choose between their loved ones and their livelihoods. But policy alone won't solve this crisis. We also need a fundamental culture shift in how we view and value caregiving.
Hanh: 01:09:49
And that starts in our own communities. We can volunteer our time and resources to support local caregiver advocacy groups fighting for change. We can amplify the voices and stories of caregivers to raise awareness of their vital role. We can educate ourselves and others about the realities of aging and caregiving to break down stigmas.
Hanh: 01:10:13
And we can demand transparency and accountability from the nursing homes in our own backyards. We can ask the tough questions about staffing levels. Caregiver compensation and turnover rates. We can shine a light on substandard conditions and be relentless in advocating for change. Because here's the thing, the caregiver
Hanh: 01:10:31
crisis isn't someone else's problem. It's deeply personal for every single one of us. Whether we're caring for a loved one now, we'll need care ourselves in the future. Or simply, believe in the fundamental human right to age with dignity. We all have a stake in building a society that values and supports caregivers. And it's going to take all of us
Hanh: 01:10:56
rolling up our sleeves So let this be our clarion call, our wake up call to action because the crisis is already at our doorstep and the clock is ticking. But if we rise to meet this moment with the urgency and moral conviction, It demands. I believe we can be the generation that turns the tide, that forges a future in which no caregiver is
Hanh: 01:11:24
left behind, and no senior is denied the care and support they deserve. It won't be easy. It will require difficult conversations, hard fought battles. And a willingness to challenge the status quo, but the alternative, a society that fails its most vulnerable when they need us most is simply unacceptable. So let's choose the path
Hanh: 01:11:49
of courage and compassion. Let's be the advocates, the change makers, the voices for the voiceless. That our caregivers and seniors so desperately need. And let's hold fast to the belief that a society is only as strong as its commitment to caring for its most vulnerable. That's the true test of our humanity.
Hanh: 01:12:15
And it's one we cannot afford to fail. The journey ahead will be long and the obstacles formidable, but if we band together in solidarity and purpose, I have no doubt that we can be the architects of a better future. One built on the bedrock of dignity, justice, and compassion for all. So let's get to work friends. Let's roll up our sleeves, join hands,
Hanh: 01:12:39
and be the change we wish to see. For ourselves, for our loved ones, for the caregivers who hold our society together with their tireless devotion. The time is now. The need is great. And together, we have the power to meet this moment and forge a brighter tomorrow for us all. Here's a challenge for you.
Hanh: 01:13:10
Over the next week, Have a conversation with a loved one about their housing preferences and experiences. Next segment, we'll discuss what you learned from those conversations and how they've shaped your own thinking. We've covered a lot of ground today, haven't we? From the heart wrenching realities of elder abuse to the transformative
Hanh: 01:13:33
potential of age friendly technology. From the dire consequences of the caregiver shortage to the imperative of reframing aging itself. And if there's one thread that weaves through it all, it's this. The challenges facing housing for older adults are as complex as they are urgent. There are no easy answers, no quick fixes, no silver bullets.
Hanh: 01:13:57
For But that doesn't mean we're powerless. Far from it. Because the flip side of that complexity is that there are a myriad of points of entry for making a difference. Countless. Opportunities, big and small, for each of us to be part of the solution. And that's really the crux of it, isn't it?
Hanh: 01:14:20
That improving the lives of seniors isn't just the job of policymakers or industry leaders or advocacy groups. It's the responsibility of every single one of us who believes in the fundamental human right to age with dignity. Because let's be real. The issues we've grappled with today. They're not abstract policy debates or distant hypotheticals.
Hanh: 01:14:43
They're deeply personal, deeply human stories unfolding in our own families and communities every single day. The grandmother suffering in silence from the unspeakable trauma of abuse. The devoted caregiver pushed to the brink of physical and emotional exhaustion. The brilliant elder slowly losing their sense of self to the fog of dementia. The vibrant senior languishing
Hanh: 01:15:07
in the isolation and indignity of an understaffed nursing home. These are our parents, our grandparents, our neighbors, our friends, and one day, they may well be us. We all have a stake in building a society that values and supports its seniors. And we all have a role to play in making it happen. If there's one thing I hope you take away
Hanh: 01:15:32
from our time together today, it's this. Your voice matters. Your actions matter. Your advocacy matters. Whether you're 18 or 88, Whether you have a platform of millions or an audience of one, because change happens when ordinary people decide to do extraordinary things. When we choose to speak out against injustice, to challenge the status quo,
Hanh: 01:16:03
To be the pioneers of a new paradigm. And that can start right here, right now with each of us committing to being a change agent in our own spheres of influence. Here are a few ways you can get started. Educate yourself and others about the realities of aging and housing for your loved one. Break down the stereotypes and
Hanh: 01:16:24
stigmas that perpetuate ageism and keep these issues in the shadows. Advocate for policies. That prioritize the well being of seniors. Right to your representatives, attend town halls, make your voice heard, support organizations on the front lines of fighting elder abuse, advocating for age friendly communities, and pioneering innovative models of care.
Hanh: 01:16:55
Volunteer your time and talents to make a difference in the lives of seniors in your community. Whether it's visiting a lonely elder, delivering meals, Or lending your skills to a local senior center. And most importantly, start the conversation in your own family and social circles. Have the tough, but essential
Hanh: 01:17:15
discussions about your loved ones wishes for their later years. Make a plan together to ensure they can age with autonomy, dignity, and joy. Because here's the thing, a significant demographic shift is coming, whether we're ready or not. The demographic shifts that will reshape our society are already well underway, and we have a choice.
Hanh: 01:17:44
We can be reactive, waiting for the crisis to reach a breaking point before we're spurred to action. Or, we can be proactive. Seizing this moment as an opportunity to reimagine what's possible for senior housing, to create a future where aging is celebrated as a vital stage of life, rich with meaning, purpose, and possibility, where every senior has access
Hanh: 01:18:10
to the care, support, and resources they need to thrive, where the wisdom and contributions of seniors are valued as the precious social capital they are, that's the world I want to live in. The world I want to grow old in. And I have to believe it's the world you want too. So let this be our rallying cry. Our call to action to be
Hanh: 01:18:31
the change we wish to see. Because if not us, then who? And if not now, then when? The choices we make today will ripple out for generations to come. Let them tell the story of a society that rose to meet the moral challenge of its time with courage, compassion, and unwavering commitment to the dignity of all.
Hanh: 01:18:57
That's the legacy we have the power to build together. So let's get to work, shall we? The road ahead may be long and winding, but with hope in our hearts and purpose in our step, there's no limit to what we can achieve. Our seniors are counting on us. Our future selves are counting on us. Let's make them proud.
Narrator: 01:19:25
As we bring this profound conversation to a close, Let's reflect on the depth and wisdom we've encountered today. The journey through the later years of life is one that demands utmost respect, empathy, and care from society. While this discussion didn't directly involve artificial intelligence, AI50 remains committed to uplifting all
Narrator: 01:19:45
aspects of the human experience through innovative technology solutions. Our mission extends beyond just business ROI to encompass societal needs and quality of life improvements. AI50 is your guide to ethical, impactful AI implementation. We bring strategies that not only boost operational intelligence, but create meaningful change aligned with
Narrator: 01:20:08
your organization's greater mission. Imagine using AI to enhance senior care services, streamline resource allocation, or even analyze population data to better accommodate our elders evolving needs. The possibilities are boundless when the right expertise is applied. Stay connected with AI50 on LinkedIn, where we share the latest breakthroughs in human centric AI applications, all
Narrator: 01:20:33
distilled into easy, consumable insights. Be sure to follow Hanh Brown for her profound perspectives on technology's role in uplifting society. Subscribe to AI50 Connect across major platforms, and explore our YouTube channel. We'll continue bringing you thought provoking discussions on using AI as a powerful force for good.
Narrator: 01:20:57
for listening. If ethical AI integration is a priority for your organization, we're here to make it a reality. Reach out and allow us to maximize technology's potential to create a better world for all. Let this episode be a reminder that society's greatest strengths are measured by how we care for our most vulnerable.
Narrator: 01:21:18
AI50 stands ready to be the empathetic innovator. Helping address society's most complex challenges. Thank you for joining us on this insightful journey. Together, we can build a future where compassion, dignity, and cutting edge solutions ensure our elders live out their days in comfort, joy, and celebration.
Hanh: 00:00:02
By leveraging AI solutions tailored to address these complexities. Older adults can receive personalized guidance, streamlined administrative processes, enhanced care coordination in cost effective recommendations. Ultimately, improving their ability to navigate the intricate
Hanh: 00:00:20
world of Medicare coverage.
Narrator: 00:00:25
Welcome to AI50, where we delve into AI's transformative power in our world, particularly in the complex Medicare system for seniors. Our host, Hanh Brown. Navigates through intricate AI topics, making them accessible and relatable. She bridges the gap between technical jargon and our everyday experiences. AI50's episodes offer a deep dive into
Narrator: 00:00:46
AI's broad impacts, featuring real life stories, breakthrough innovations, and insights from leading experts. We showcase AI's significant role in evolving healthcare practices. And reshaping businesses, aiming to foster a deep understanding among our audience. In this episode, we spotlight AI's potential to unravel the
Narrator: 00:01:07
complexities of Medicare. We'll explore how AI can revolutionize elder care by refining diagnosis processes, tailoring treatments, and boosting overall system efficiency. Our discussion will uncover AI's ability to navigate the intricate layers of Medicare, promising a
Narrator: 00:01:27
future where care for seniors is both advanced and compassionate. We'll also tackle AI's practical applications in Medicare, scrutinizing the ethical dimensions alongside. Our comprehensive analysis aims to equip you with a nuanced perspective on how this technology is shaping
Narrator: 00:01:43
the landscape of elderly care. Prepare for an enlightening journey filled with compelling narratives, expert insights, and concrete examples that bring the intersection of AI and Medicare to life. With Hanh as our guide, we delve into the promising realm of AI in Medicare, envisioning a pathway where advanced technology meets
Narrator: 00:02:06
the nuanced needs of senior care. Let's get started on this conversation. Expect narratives, insights, and real examples, making AI's world relatable. Hanh, let's explore today's AI topic.
Hanh: 00:02:23
Hello and welcome to AI50 Connect. I'm your host, Hanh Brown. Today, we're embarking on a fascinating journey into the heart of Medicare's complexities. Medicare with AI. Tailored specifically for older adults. Have you ever felt lost in the maze of healthcare options? Well, you're not alone.
Hanh: 00:02:41
Together, we'll unravel these intricacies and discover how cutting edge AI technology can be your compass in this journey. So, if you're ready to simplify your healthcare experience with the power of AI, let's get started. In this episode, brace yourself for an eye opening exploration. We're delving into the top five
Hanh: 00:03:02
challenges faced by older adults in Medicare, from decoding the puzzle of plan selection to effectively managing multiple chronic conditions. But that's not all. We're also unveiling the transformative role of AI. Imagine having a virtual assistant that knows your healthcare needs as well as you do.
Hanh: 00:03:24
helping you make informed decisions with ease and confidence. It's not just the future, it's happening now, and we're here to guide you through it. Let me share a story of someone I met recently. Susan, a retired teacher, found herself lost in the maze of Medicare. Despite her years of experience
Hanh: 00:03:42
managing a classroom, Medicare's complexities felt like a puzzle with too many missing pieces. Today, just like Susan did, we'll unravel this puzzle, breaking it down into digestible pieces as we dive into the world of Medicare's different parts. Imagine you're navigating a maze. That's Medicare for many. It's complex, but why?
Hanh: 00:04:05
There are four main parts. Part A, B, C, and D. Ever wondered what these parts cover and how they impact your wallet? Now let's take a moment. Think of someone you know, maybe a family member or a close friend, navigating this maze. How do they feel? Anxious?
Hanh: 00:04:22
Confused? This isn't just a journey of understanding, it's an emotional one, filled with questions and concerns. Beyond simplifying navigation, AI's influence extends to the very heart of healthcare, the patient doctor relationship. By integrating AI tools, We can significantly enhance communication
Hanh: 00:04:45
between doctors and their senior patients, ensuring that medical advice is both understood and actionable. AI can help in translating complex medical terminology into simpler language, aiding seniors in making informed decisions about their health care. AI driven analytics can provide physicians with a more comprehensive view of a patient's health history, enabling a more
Hanh: 00:05:09
personalized and effective treatment plan. This synergy between AI and healthcare professionals is pivotal, as it fosters a collaborative environment where where the focus is on delivering patient centered care that respects the needs and preferences of each individual within the Medicare system. Let's start with Part A, Hospital Insurance.
Hanh: 00:05:36
Think of it as your safety net for hospital stays. But have you considered what happens if you need long term care? Does Part A cover it? Here's a thought. How do you plan for unexpected hospital costs? Transitioning to Part B, the medical insurance.
Hanh: 00:05:51
This covers doctor visits and outpatient care. But it's not all encompassing. Ask yourself, what gaps might you find in Part B coverage? How would you manage expenses not covered? Now, on to the often misunderstood Part C, Medicare Advantage plans. These are bundled alternatives to original Medicare offered by private companies.
Hanh: 00:06:14
But here's a question. How do these plans differ from Parts A and B? Are they more cost effective in the long run? Lastly, Part D, prescription drug coverage. Essential, isn't it? But have you ever been puzzled by the coverage tiers and varying costs?
Hanh: 00:06:31
How do you decide which plan best fits your medication needs? The complexity doesn't end there. Each part has its rules, coverage limits, premiums, deductibles, and copayments. Navigating this can be daunting. Think about your own healthcare needs. How would you determine which Medicare parts best suit you? Now that we've seen the intricate
Hanh: 00:06:51
layers of Medicare, let's pivot to a solution that's reshaping how we navigate this complex system. To appreciate the sophistication of AI in Medicare navigation, go It's important to understand the technical underpinnings that make these systems so effective. At the core, AI tools integrate diverse data sources, from patient medical records to insurance plant databases,
Hanh: 00:07:17
creating a comprehensive data set. These tools employ advanced security measures to protect sensitive health information, using encryption and secure data access protocols. The algorithms driving these AI solutions are designed for transparency and accountability, ensuring that decisions can be traced and explained, which is crucial for building trust
Hanh: 00:07:40
and ensuring ethical compliance in healthcare decision making. Delving deeper into the AI technologies at play, let's explore how predictive analytics and machine learning models are revolutionizing Medicare navigation. These tools analyze vast data sets, identifying patterns and trends that are invisible to the human eye. For example, machine learning algorithms
Hanh: 00:08:05
can predict which Medicare plan options are most suitable for individuals based on their medical history. lifestyle, and even genetic predispositions. This is not just about choosing the right plan. It's about foreseeing potential health issues and preventing them proactively. By integrating these advanced
Hanh: 00:08:26
technologies, Medicare can offer not only personalized plan recommendations, but also predictive insights. leading to early interventions and better health outcomes for seniors. Traditionally, navigating Medicare has been a daunting task, characterized by complex paperwork, confusing eligibility criteria, and a plethora of plan options that can overwhelm
Hanh: 00:08:53
even the most diligent individuals. In contrast, AI Enhanced Medicare Navigation streamlines this process, offering a user friendly interface that simplifies decision making. While the conventional approach often requires navigating through dense informational resources, AI systems synthesize this data. Presenting it in an accessible
Hanh: 00:09:17
format and providing personalized recommendations based on the user's unique healthcare profile. But what sets them apart? It's their ability to engage in natural language conversations, making them accessible and user friendly. Especially for older adults. How would this change your experience with healthcare?
Hanh: 00:09:40
Imagine a chatbot that knows your health history and can offer advice based on that information. Let's consider the case of John, a 68 year old with multiple health concerns. He was initially overwhelmed by Medicare choices. Then, he used an AI tool that reviewed his medical history and current needs. John found a plan that not only covered
Hanh: 00:10:02
his medications, but also saved him money. This wasn't just convenient, it was life changing. How could this personalized assistance impact your healthcare decisions? Based on the individual's chosen plans and anticipated healthcare utilization, they provide a clearer financial picture. How helpful would it be to have an AI estimate your
Hanh: 00:10:31
potential healthcare expenses? As we embrace these technological advances, it's crucial to consider their implications. AI in healthcare, particularly for Medicare, offers unprecedented support and convenience. But let's not overlook the elephant in the room. The concerns about privacy and
Hanh: 00:10:48
data security in an age where data breaches are not unheard of. How can we ensure that these AI tools safeguard our most sensitive health information? It's vital to have stringent data protection measures and transparent policies in place. How would you feel about sharing your health data with an AI system?
Hanh: 00:11:08
What assurances would you need to trust it? However, it also brings up questions about data security and privacy. How do we balance innovation with the protection of sensitive information? The integration of AI into Medicare navigation represents a significant step forward in making healthcare more accessible and
Hanh: 00:11:29
less overwhelming for older adults. It's a shift towards a future where technology and healthcare work hand in hand to provide better, more personalized care. Let's talk about choosing the right Medicare plan. It is a pivotal decision that looms large for older adults. Choosing the right Medicare plan.
Hanh: 00:11:53
Picture standing at a crossroads. Each path representing a different Medicare plan, with crucial health and financial implications. Have you ever stood at such a crossroads? Choosing between original Medicare, encompassing Parts A and B, and Medicare Advantage plans, known as Part C, is not just a choice. It's a strategic decision.
Hanh: 00:12:15
Each path has its unique landscape, varying premiums, deductibles, provider networks, and additional benefits. And let's not forget the winding trail of Part D, the prescription drug plan. With an array of paths, how do you pick the one that leads to the best outcome for your health and wallet? Now, imagine having a personal guide at this crossroads, an AI algorithm equipped
Hanh: 00:12:40
to navigate you through these choices. Picture this AI as a lantern in the dark, illuminating your unique health profile, your chronic conditions, medication needs, preferred doctors, and budget. How would it feel to have such a beacon of clarity? This AI isn't just a guy, it's a personalized advisor. It doesn't just show you the
Hanh: 00:13:01
paths, it walks you through them, highlighting the pros and cons tailored to your health narrative. Think about the relief of seeing a clear comparison with the AI spotlighting the best options based on your specific needs. Would you trust this AI guide to lead you to the right choice? But with great technology comes great responsibility.
Hanh: 00:13:24
How much trust would you place in an AI's recommendation? What factors would weigh heavily in your decision? Cost efficiency, comprehensive coverage, or access to your preferred healthcare providers? And let's consider inclusivity. In a world where technology is king, how do we ensure these AI tools are
Hanh: 00:13:44
accessible to everyone, especially those less familiar with digital gadgets? How do we protect the treasure trove of personal health information in this digital realm? Choosing the right Medicare plan is more than navigating a maze. It's about crafting a personal health journey that aligns with your unique needs and aspirations.
Hanh: 00:14:03
With AI poised to revolutionize this journey, we stand on the brink of a new era in healthcare decision making. One that promises personalization, but also challenges us to think critically about trust and trustworthiness. accessibility and privacy. As we consider the personal benefits of AI in Medicare navigation, it's crucial to also recognize its
Hanh: 00:14:24
capacity for broader societal impact. AI's advanced data analysis can forecast demographic shifts in healthcare trends among the aging population, enabling policymakers and healthcare providers to anticipate and address future challenges. This foresight can lead to more effective resource distribution, ensuring that Medicare remains robust and responsive to the evolving needs of its beneficiaries.
Hanh: 00:14:57
By analyzing patterns in healthcare usage and outcomes, AI can inform more strategic decisions in Medicare policy and funding, helping to sustain the program's financial health, And service quality for future generations. Let's now discuss a critical issue. Many older adults face managing multiple chronic conditions. It's a challenge akin to
Hanh: 00:15:18
juggling several balls at once. Each condition, be it heart disease, diabetes, arthritis, or respiratory disorders, requires its own specific care plan involving various health care providers, treatments, and medications. How do older adults ensure their Medicare coverage encompasses all these necessities considering the varying coverage rules and restrictions?
Hanh: 00:15:42
Imagine the complexity of this task. It's not just about tracking appointments and medications. It's about understanding how Medicare interacts with each condition and treatment. Could your current Medicare plan be missing vital elements of your health care puzzle? Enter Aya, the game changer
Hanh: 00:15:58
in managing this intricate dance of chronic conditions. These AI models can be likened to personal health detectives. They dive into your medical records, claims history, and even social factors, unearthing potential gaps in care or risk of adverse events. How would it feel to have such a vigilant guardian overseeing your health care?
Hanh: 00:16:22
The A. I. doesn't stop there. It steps up as your healthcare strategist recommending ways to optimize Medicare coverage for your unique health scenario. This might include suggesting supplemental plans or alternative medication options that are more economically viable under Medicare.
Hanh: 00:16:40
How much peace of mind would you gain knowing that your health coverage is being maximized in every aspect? But perhaps the most groundbreaking role of AI in this context is as a coordinator. It acts as a bridge connecting your myriad healthcare providers. This ensures a harmonious care plan where every aspect of your chronic condition management is known, understood, and
Hanh: 00:17:00
covered under your Medicare plan. How would this level of coordinate care impact your health and well being? As we explore these AI solutions, we also grapple with important considerations. How do we balance the benefits of AI in healthcare management with concerns over privacy and data security? And how do we ensure these AI tools are accessible and user friendly for all,
Hanh: 00:17:31
regardless of their tech savviness? Managing multiple chronic conditions under Medicare is a complex, yet critical task for many. With AI's emerging role in this field, we're looking at a future where managing supplemental Medicare coverage could become more straightforward, personalized, and efficient. Let's not just be a listener,
Hanh: 00:17:54
but an active participant in your healthcare journey. Explore AI options available for Medicare Navigation. Seek out resources, ask questions, and make informed choices. Remember, your healthcare is in your hands and with the right tools. You can navigate this journey with confidence in addition to managing
Hanh: 00:18:16
physical health conditions, we must not overlook the mental well being of our senior population. AI can be instrumental in this domain by detecting early signs of mental health issues such as depression or anxiety through pattern recognition in behavior and communication. Furthermore, AI powered platforms can provide accessible mental health
Hanh: 00:18:37
support, offering resources like digital therapy or connecting seniors with mental health professionals. These interventions can be vital in mitigating feelings of isolation and improving the overall quality of life, making AI a comprehensive ally in the healthcare journey of Medicare beneficiaries. Let's move on to an
Hanh: 00:19:00
issue that touches many. The challenge of managing high out of pocket costs. It's a concern that can weigh heavily on your mind, isn't it? Imagine standing at a pharmacy counter, facing a decision between medication and other essentials due to cost. It's a scenario far too many encounter. Consider the intricate web of
Hanh: 00:19:21
Medicare's financial demands. Premiums, deductibles, copayments, and coinsurance. These are not just terms. They are real expenses that can add up quickly, varying significantly based on your chosen plan and healthcare needs. Picture balancing on a financial tightrope where every health decision has a cost implication.
Hanh: 00:19:43
Have you experienced this balancing act? How did it make you feel? Now, imagine a world where AI intervenes as a financial navigator in this complex health care journey. Envision AI algorithms not as cold calculations, but as your personal health care financial advisors tuned to your unique income level and health requirements.
Hanh: 00:20:04
They sift through Medicare plan options, supplemental coverages, and even financial assistance programs. How would it change your life to have such personalized data driven guidance at your fingertips? Learn This AI isn't just about numbers. It's about your life and well being. It provides recommendations aimed at minimizing your out of pocket expenses
Hanh: 00:20:26
while ensuring you don't compromise unnecessary healthcare coverage. Think of it as having a vigilant guardian overseeing your healthcare finances, constantly seeking the most beneficial options for you. How reassured would you feel knowing your healthcare expenses are being optimized in the background? These AI systems offer personalized
Hanh: 00:20:44
cost estimates and projections, shining a light on the often murky waters of future healthcare spending. This is about enabling you to plan, to budget, to plan. Not just for today, but for the long term, how empowering would it be to have a clear picture of your future health care financial landscape as we embrace these AI solutions?
Hanh: 00:21:09
Let's also consider their wider implications. What level of trust are you willing to place in AI for such crucial financial decisions? How do we ensure equitable access to these advanced technologies, especially for those less tech savvy? Dealing with Medicare's out of pocket costs is more than a financial challenge.
Hanh: 00:21:30
It's a significant aspect of your life's journey. With AI's emerging role, we envision a future where managing these costs becomes more transparent, informed, and less burdensome. Now, let's turn our attention to an aspect of Medicare that often goes under discussed, but is crucial. Accessing and utilizing
Hanh: 00:21:52
supplemental coverage. It's a step many find as puzzling as completing a complex jigsaw puzzle, where every piece must fit perfectly to create the complete healthcare coverage picture. Supplemental coverage, such as Medigap policies, or employer sponsored retiree health plans, is often essential to fill the gaps in Medicare. But here's the catch.
Hanh: 00:22:17
Understanding the eligibility requirements, enrollment periods, and specific details of these supplemental plans is no small feat. It's like navigating a labyrinth with rules and restrictions at every turn. Have you ever felt lost in this maze, trying to figure out the best option for your health needs? Imagine coordinating coverage between
Hanh: 00:22:36
Medicare and these supplemental plans. Each plan has its own set of rules, making it a complex task to ensure they complement each other without overlap. How do you determine the best combination of plans to cover all your healthcare needs while avoiding unnecessary expenses? This is where AI steps in, like a skill guide through this maze. Picture AI powered virtual assistants
Hanh: 00:23:01
and chatbots, not just as tools, but as personalized guides offering clarity on supplemental coverage options. These AI systems are trained on the latest regulations and planned details. enabling them to provide precise and up to date information. How much easier would your enrollment process be with such assistance? But the role of AI doesn't
Hanh: 00:23:25
stop at providing information. It extends to analyzing your unique situation. Imagine an AI algorithm that scrutinizes your existing Medicare coverage and potential supplemental plans, identifying gaps, or overlaps in coverage. This isn't just about data analysis. It's about crafting a coverage plan tailored to your specific health
Hanh: 00:23:51
needs and financial situation. How reassured would you feel knowing you have the most efficient combination of Medicare and supplemental coverage? The AI then takes a step further, offering recommendations on effectively coordinating these plans. It's like having a strategist for your health care coverage, ensuring you receive comprehensive care without redundant
Hanh: 00:24:12
coverage or unnecessary expenses. How would this change your approach to managing your health care? As we embrace these AI solutions. Let's consider their broader impact. How do we ensure these technologies are accessible to everyone, particularly those who may not be as tech savvy? And what measures are in place to protect your sensitive health
Hanh: 00:24:39
information in this digital era? Accessing and utilizing supplemental coverage is more than just a bureaucratic process. It's about securing your health and peace of mind. With AI's emerging role in this field, we're looking at a future where managing supplemental Medicare coverage could become more straightforward,
Hanh: 00:24:58
personalized, and efficient. By leveraging AI solutions tailored to address these complexities, older adults can receive personalized guidance, streamlined administrative processes, enhanced care coordination, and cost effective recommendations. Ultimately, improving their ability to navigate the intricate world of Medicare coverage.
Hanh: 00:25:20
As we come to the end of today's episode, let's recap what we've discussed. We started by dissecting the complex structure of Medicare, understanding its different parts A, B, C, and D and their distinct roles. We then ventured into how AI is redefining the way we navigate these complexities, offering personalized, accessible solutions
Hanh: 00:25:43
like virtual assistants and chatbots. From helping John, a 68 year old with multiple health concerns, to providing financial guidance for managing out of pocket expenses, we saw the profound impact AI can have on individual lives. We also discussed the importance of balancing innovation with privacy and security. A crucial aspect of integrating
Hanh: 00:26:05
technology into healthcare. Our journey today has been about more than just understanding. It's been about empowering ourselves with the tools and knowledge to make better healthcare decisions. And with that, we conclude this episode of Medicare with AI. I'm Hanh Brown, and it's been a pleasure guiding you through the complex
Hanh: 00:26:31
yet fascinating world of Medicare and the transformative role of AI. I hope today's discussion has shed light on how technology can be your ally in making informed healthcare decisions and simplifying the journey through Medicare. Remember, understanding your healthcare options is the first step toward empowerment. Keep exploring, stay inquisitive,
Hanh: 00:26:52
and make the most of the resources available to you. Join us next time as we continue to demystify the medical landscape and explore how AI can enhance the well being of older adults. Until then, stay empowered in making informed decisions about your journey towards a fulfilling life in your golden years.
Hanh: 00:27:14
Farewell, and may you thrive in your later years.
Narrator: 00:27:22
Another exciting AI50 Connect episode wraps up, and what a journey it's been. We dove into the world of AI and data, turning complex ideas into easy to grasp gems. AI is not just tech talk, it's a real game changer. For everyone, from tech enthusiasts to business leaders, AI is your go
Narrator: 00:27:41
to for smarter, faster decisions. Now picture AI transforming your business, making everything smoother, finding hidden opportunities, reducing mistakes, and firing up your team. It's not just improvement. It's a total game change. AI50 is more than a podcast. It's your AI guide. We bring you AI strategies that
Narrator: 00:28:04
are not just smart, but also a perfect fit for your business goals. And guess what? We make it simple and exciting. Want to know how AI50 can uplift your business? Let's chat. We're here to turn your data into a superpower. Stay connected with AI50 on LinkedIn.
Narrator: 00:28:23
We're sharing the latest and greatest in AI, all in easy bites. And don't miss out on Hanh Brown's insights on LinkedIn. It's your shortcut to staying ahead in AI. Hit that subscribe button on AI50 will connect on your favorite platform. We've got more great AI talks and tips coming your way. Check us out on YouTube
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for more cool stuff. From podcasts to exclusive interviews, it's all there in fun, engaging videos. Thinking of AI for your business, reach out. We're here to make AI work wonders for you. Thanks for being with us on AI50 Connect. Remember with AI, you're not just keeping up, you're leading the way.
Narrator: 00:29:00
See you next time for more AI excitement.
Hanh: 00:00:02
As AI becomes more integrated into our workplaces and lives, we need to ensure that humans remain at the decision making core. This involves designing AI systems that complement human skills and augment our capabilities rather than replace them. How can we create AI tools that empower workers rather than diminish their roles?
Narrator: 00:00:26
Welcome to AI50, your portal into the extraordinary world of artificial intelligence and its profound impact on the lives of seniors. Today, we're joined by AI Luminary Hanh Brown, gifted at translating AI's
Narrator: 00:00:40
complex concepts into everyday terms. Hanh will illuminate AI's incredible potential across health care, business and our daily lives. AI50 goes beyond exploring technology. It's an adventure into AI's
Narrator: 00:00:54
transformative power. We bring compelling narratives, explore groundbreaking innovations and converse with pioneers. Our dialogues span AI's diverse applications, from advancing medical care to revolutionizing business practices. Each episode dives deep, examining
Narrator: 00:01:11
AI's advancements alongside the ethical and societal implications. Our aim is to shed light on AI's multifaceted nature and its capacity to drive positive change for older adults. Join us on this enlightening journey fusing engaging storytelling, expert analysis, and vivid examples to elucidate AI's breadth and depth. Hanh, let's begin unpacking
Narrator: 00:01:35
today's fascinating AI topic.
Hanh: 00:01:44
In this episode, redefining work in the age of AI. We embark on a thought provoking journey to explore how artificial intelligence is reshaping our workforce in daily lives. From automation of routine tasks to the creation of new job roles, AI's influence is profound and far reaching. We'll go into historical perspectives, address the urgency of adapting
Hanh: 00:02:08
to rapid changes, and discuss the importance of societal involvement in shaping this AI driven future. Join me as we uncover the multifaceted impacts of AI on work, examine the challenges it presents, and envision the opportunities it creates for innovation and growth. In the upcoming podcast, we'll navigate through various dimensions of how
Hanh: 00:02:35
AI is transforming the workforce. We'll start by exploring the monumental impact of AI on jobs and industries. As we progress, we'll discuss the awareness gap in society about AI, delve into historical parallels with past technological revolutions, and address the rapid pace of change AI brings. We will also examine the implications of universal basic income, the
Hanh: 00:03:00
evolving nature of work, and the crucial role of societal participation in guiding this transformation. Each section is designed to provoke thought and encourage a deeper understanding of our AI infused future. Now, imagine your daily job tasks. How many of them could be automated by an AI system? For some, this is an exciting
Hanh: 00:03:21
prospect of efficiency and progress. For others, it's a daunting reality of potential job displacement. The change AI brings isn't just about new technology. It's about a shift in how we perceive and engage in work. Consider the typical roles in industries like manufacturing, customer service, or even health care.
Hanh: 00:03:46
A. I. Systems can handle repetitive tasks, analyze massive data sets or even diagnose diseases with higher accuracy. How does this change the role of the human worker in these fields? Are we looking at a future where human skills are utilized for tasks that AI can't replicate?
Hanh: 00:04:04
Like creativity, empathy, and complex problem solving? The disruption AI brings to the workforce is unlike any we've seen before. It's not just about changing how we work. It's about rethinking the very nature of work. This isn't a slow evolution. It's a rapid transformation that we, as a society, need to prepare for.
Hanh: 00:04:27
How do you think this will impact the job market in the next 10, 20, or even 30 years? How can workers adapt to remain relevant in this new landscape? The challenge we face isn't just technological. It's also about ensuring that the workforce can evolve with these changes. As we contemplate these questions,
Hanh: 00:04:44
remember that with great change comes great opportunity. AI may close some doors, but it will undoubtedly open new ones. Our task is to anticipate these openings and equip ourselves to walk through them. In our next section, we'll delve into the awareness and education gap regarding AI's role in our work lives. Stay tuned as we explore why
Hanh: 00:05:09
many are still uninvolved in this critical conversation and how increasing awareness is the first step towards meaningful adaptation. Moving forward in our series on redefining work in the age of AI, let's address a critical issue, the awareness gap. Despite AI's transformative potential, a significant part of society remains disconnected from the ongoing
Hanh: 00:05:34
dialogue about its impact on work. This isn't just a tech issue. It's a societal one. How can we be on the brink of such a seismic shift, yet have so many unaware of its magnitude? Think about it. When you discuss the future of work with friends or colleagues, how often does AI come up?
Hanh: 00:05:56
For many, AI still feels like a distant, abstract concept, something out of science fiction. But it's here, and its effects are unfolding now. Why, then, is there such a lack of widespread discourse and education on this topic? This gap isn't just about lack of information.
Hanh: 00:06:16
It's about the way AI is presented in media and popular culture. Often, it's either sensationalized as a threat to humanity, or portrayed as a futuristic fantasy. But the reality of AI is much more immediate and practical. How can we shift the narrative to reflect this? Consider this.
Hanh: 00:06:36
Every technological advancement in history brought change, and society adapted. However, the speed and scale of AI's impact are unlike anything we face. It's crucial, then, to educate. And engage people in understanding AI. How can we create more opportunities for learning and discussion? Not just in tech circles, but
Hanh: 00:06:57
in every facet of society. Public discourse needs to encompass AI's implications on job roles, industries and even our daily routines. Think about a cashier at your local supermarket. Are they aware of how automated checkout systems could impact their job?
Hanh: 00:07:15
What about a truck driver? Considering the advancements in autonomous vehicles? It's vital for these conversations to happen across all levels of society. Education plays a key role here. It's not just about tech education, but a holistic understanding of how AI integrates into various fields. How can educational institutions
Hanh: 00:07:34
evolve to prepare the next generation for an AI driven job market? How can current workers be retrained to work alongside AI? As we ponder these questions, let's remember that awareness is the first step towards adaptation. The more we discuss, learn, and understand AI's role in redefining work, the better equipped we'll
Hanh: 00:07:56
be to navigate this new era. In our next section, we'll explore how AI systems like ChatGPT are bringing AI into the public consciousness. And making the technology more tangible and relatable. Next, let's focus on a pivotal moment in AI's journey into public consciousness. The advent of systems like ChatGPT, these AI tools have brought the
Hanh: 00:08:25
conversation out of tech forums and into everyday life, making the abstract concept of AI concrete and accessible. Before ChatGPT, AI was often a distant, somewhat elusive notion for many. But now, with the ability to interact directly with such an AI system, People are witnessing firsthand AI's
Hanh: 00:08:46
capabilities. How many of you have experimented with chat GPT or similar platforms? These experiences are not just novelties. They're eye openers to the practical applications and implications of AI. Let's think about how this direct interaction changes our perception. When you use ChatGPT to summarize a document, generate a creative
Hanh: 00:09:08
story, or even draft code, it's not just a task being done. It's a demonstration of AI's potential impact on various job functions. How does this shape our understanding of AI's role in our professional and personal lives? The beauty of AI systems, like ChatGPT, lies in their versatility. They're not confined to
Hanh: 00:09:29
one sector or profession. Their uses span across fields, hinting at a future where AI integration is ubiquitous. From educators to marketers, programmers to writers, everyone is starting to see how AI can be a tool in their arsenal. What tasks in your job could AI like ChatGPT assist with? These interactions are demystifying AI.
Hanh: 00:09:53
They're showcasing AI's potential not as a replacement, but as a complement to human skills. Imagine a world where your AI assistant handles time consuming tasks, freeing you up for more creative, strategic endeavors. How does this change the traditional job model? It's important to note that AI systems like ChatGPT also bring
Hanh: 00:10:14
AI ethics and responsibility into sharper focus for the average person. As we interact with these systems, questions about bias, privacy, and the ethical use of AI naturally arise. How can we ensure that these technologies are developed and used responsibly? In our next section, we're going to trace the history of technological revolutions and their impact on work.
Hanh: 00:10:39
We'll see how, like the agricultural and industrial revolutions before it, the AI revolution is setting the stage for a new epoch in human history. As we continue our series on redefining work in the age of AI. It's crucial to put this evolution into a historical context. Throughout human history, major technological revolutions have
Hanh: 00:11:05
consistently transformed the workforce. Consider the agricultural revolution, the industrial revolution, and the digital era. Each of these ways brought about significant changes, phasing out certain jobs while creating new ones. This process, often termed creative destruction, is an integral part of technological progress,
Hanh: 00:11:24
Let's travel back in time. The Agricultural Revolution shifted us from nomadic lifestyles to settled farming, drastically changing the nature of work. Centuries later, the Industrial Revolution did it again. Moving us from rural farms to urban factories. Fast forward to the digital age, and we
Hanh: 00:11:44
see a similar pattern with the rise of new industries and the decline of others. Each of these revolutions span roughly 100, 150 years, reshaping society and the job market in profound ways. Jobs that were once essential, like blacksmithing or manual weaving, became obsolete. In their place, new roles emerged, aligned with the new technological landscape.
Hanh: 00:12:11
What does this tell us about the current AI revolution? AI is part of this ongoing narrative of progress. Just as the steam engine or the computer changed the job landscape, AI is poised to do the same. However, the pace is faster and the impact more widespread. How does this acceleration challenge
Hanh: 00:12:27
our ability to adapt and retrain for new kinds of work that AI will create? This historical perspective is a reminder that change is a constant in human history. The jobs that exist today might not exist tomorrow, but new opportunities will arise. The key question is, how do we prepare for these changes?
Hanh: 00:12:49
Can we draw lessons from the past to help us navigate the AI revolution? How can we ensure that the transition to new types of work is smooth and equitable? Understanding history gives us a framework to approach these questions. In the next section, we will discuss the unprecedented speed of AI's impact on the job market. And the unique challenges it presents.
Hanh: 00:13:12
How do we handle a transformation that is set to happen not in centuries, but within just a few generations? As we navigate through our series on redefining work in the age of AI, we now confront the startling velocity at which AI is reshaping the job landscape. Unlike past technological revolutions, AI's wave of change is sweeping across industries at an unprecedented
Hanh: 00:13:36
pace, expected to transform the workforce drastically within just two to three generations. This rapidity is the crux of the challenge we face today. Think about the enormity of this shift. Within the span of a single career, AI is projected to automate a vast array of tasks and roles across sectors. It's not just routine,
Hanh: 00:13:59
manual jobs at stake. AI's reach extends to complex tasks requiring analytical and decision making skills. How do we adapt to a future where the job market of our youth looks drastically different from that of our retirement? Telling people the future will be better is a simplistic approach to a complex problem.
Hanh: 00:14:22
While technological progress often brings long term benefits, the short term disruption can be profound and unsettling. How do we support those whose livelihoods are transformed or displaced by AI? Consider the worker in a factory who sees robotics replace his role, or the office worker whose administrative tasks are taken over by AI. It's not just about finding them new jobs.
Hanh: 00:14:48
It's about understanding the emotional and social impact of such a rapid change. How do they redefine their skills and identity in this new landscape? The key lies in proactive adaptation. Societies need to rethink how we educate, train, and support our workforce. It's not just a matter of learning new skills, but embracing a mindset of continuous learning and adaptability.
Hanh: 00:15:13
What strategies can we implement today to prepare for a future that's arriving faster than any previous technological shift? This unprecedented speed of AI's impact requires more than just optimism about the future. It demands Active planning and thoughtful intervention. How do societies, governments and
Hanh: 00:15:32
educational institutions collaborate to facilitate this transition? In our next section, we'll explore why providing a universal basic income, while helpful, is not a comprehensive solution to the disruption caused by AI. We'll go into the human need for agency and purpose in work and how these elements are critical in navigating the AI revolution.
Hanh: 00:16:01
In our ongoing conversation about redefining work in the age of AI, let's turn our focus to a crucial aspect of adapting to AI's workforce disruption, the concept of Universal Basic Income, UBI, and the inherent human need for agency. While UBI is often proposed as a solution to job displacement caused by AI, it's important to recognize that it addresses only one facet of a much larger issue.
Hanh: 00:16:29
Universal basic income, at its core, is a financial safety net designed to provide a basic standard of living in the face of job loss. But is money enough? What about the deeper human needs that work fulfills? People don't just work for a paycheck. They work for a sense of purpose. For the feeling of contributing to
Hanh: 00:16:47
something larger than themselves, for the structure it brings to daily life, and for the sense of achievement and recognition. The need for agency, the capacity to make choices and influence our life's direction is deeply embedded in human psychology. Work often provides a sense of agency. It's about having control over one's destiny and feeling that one's actions have an impact.
Hanh: 00:17:15
So, what happens when traditional work is disrupted by AI? Can a universal basic income replace the sense of identity and purpose that work provides? Imagine this scenario. AI automates a significant portion of your job. You receive enough income to live comfortably, but you no longer have the
Hanh: 00:17:35
challenges, achievements, and social interactions that your job provided. How would you fill this void? Where would you find purpose in a sense of achievement? Society needs to think beyond just financial compensation. We must consider how to preserve human agency in a sense of purpose as AI transforms the job market.
Hanh: 00:17:56
How can we create opportunities for people to engage in meaningful activities, contribute to their communities, and feel valued? Could the answer lie in redefining work itself? Perhaps the future will see a greater emphasis on creative pursuits, community service, Lifelong learning and other activities that foster a
Hanh: 00:18:16
sense of purpose and fulfillment. As we look to the next section, we'll delve deeper into the idea that simply providing financial support is not enough. We need to explore ways to ensure that as we navigate this AI driven transformation, we maintain our core human needs for creativity. Self expression and purposeful contribution to society.
Hanh: 00:18:39
As we go deeper into redefining work in the age of AI, it's critical to address the inadequacy of merely providing a safety net income, like a universal basic income, without opportunities for meaningful engagement. While financial stability is crucial, it doesn't fulfill our deeper human needs for creativity, Purpose in societal contribution.
Hanh: 00:19:02
Humans inherently seek to create, contribute, and leave a mark. Work in many ways satisfies these urges. It's not just about earning a living. It's about feeling useful, expressing ourselves, and impacting the world. So, in an AI dominated future where traditional jobs may be scarce or transformed, how do we cater to these fundamental human needs?
Hanh: 00:19:25
Let's consider a scenario. You receive enough income to live comfortably. But your job, a source of challenge and fulfillment, is automated by AI. What next? How do you find a sense of purpose? This is where we need to rethink our societal structures and values. The future may need to shift focus
Hanh: 00:19:43
from work as a means of survival, to work as a means of self actualization. Could this lead to a renaissance of arts, crafts, and community service? How about a surge in innovation and entrepreneurship? As people have the freedom to pursue passion projects without the pressure of financial survival. We should also explore how technology
Hanh: 00:20:04
itself can facilitate these pursuits. AI could help match people's skills and interests with community needs. It can create platforms for artistic expression. It can slow offer personalized learning paths for continuous personal and professional development. In a world where AI takes on more tasks, the human touch becomes more valuable.
Hanh: 00:20:28
The care industry, teaching, mentoring, and other roles that require empathy and human connection could take on new significance. Could this be an opportunity to revalue and reinvigorate these often underappreciated sectors? In the next section, we will discuss how, despite AI making certain job types obsolete, history and human
Hanh: 00:20:48
ingenuity show that new forms of work and self expression will emerge. We'll explore the potential evolution of what work might mean and how we can prepare for these changes. Continuing our journey in the series, Redefining Work in the Age of AI, let's ponder the inevitability of new forms of work and self expression emerging as AI reshapes our job landscape.
Hanh: 00:21:20
History teaches us that with every major technological shift, while some jobs become obsolete, new opportunities and modes of work arise, often in ways we couldn't have previously imagined. Think about it. Centuries ago, hunter gatherers might have scoffed at the idea of farming, or early farmers at the concept of office work. Today's professional roles
Hanh: 00:21:41
could very well seem just as peculiar to future generations. AI is poised to automate many current jobs, but this isn't just an end, it's the beginning of a new chapter in human ingenuity and creativity. The question then is, what will this new world of work look like? Could we see a rise in jobs centered around enhancing human AI interaction,
Hanh: 00:22:05
or new industries we can't yet conceive? Perhaps, there will be a greater emphasis on roles that AI can't fulfill, those requiring deep empathy, creativity, and interpersonal skills. This shift offers an opportunity to redefine what we value as work. The future could see a greater appreciation for pursuits often deemed as hobbies or side projects, art,
Hanh: 00:22:27
craftsmanship, community service. In an AI driven society, these activities might not just be leisurely pastimes. They are vital contributions to our collective well being and culture. We must also consider how we can prepare for these changes. How do we educate and train ourselves and future generations for jobs that don't yet exist?
Hanh: 00:22:51
What skills will be most valuable in a world where AI handles much of the computational and analytical work? As we approach this new era, it's crucial to foster adaptability and lifelong learning. Encouraging curiosity, creativity, and a willingness to continually acquire new skills will be key in navigating the AI impacted job market.
Hanh: 00:23:15
In our next discussion, we focus on the risks of an AI work transformation driven solely by market dynamics. We'll consider the need for thoughtful, inclusive planning. This is vital for a seamless societal shift. This segment of our series tackles a crucial issue, the hazards of a workforce evolution guided only by
Hanh: 00:23:36
market forces and economic Darwinism. We emphasize the importance of proactive and collective involvement in this transition. Such a laissez faire approach could exacerbate inequality and lead to societal unrest. underscoring the need for collective engagement in shaping our future. If AI advances focus only on profits
Hanh: 00:23:58
and efficiency, the gap between the adaptable and the left behind will widen. Imagine a world where only a few gain from tech advances, leaving others struggling. This isn't just unfair, it's unsustainable. So how do we navigate this transition more equitably? Society must play a proactive role in this transformation.
Hanh: 00:24:23
It's not enough to react to changes as they come. We should collectively envision and design the future we want. This means fostering a dialogue that includes not just tech developers and businesses, but workers, educators, policymakers, and everyday citizens. What should the future of work look like? How do we ensure that AI serves
Hanh: 00:24:42
the common good, enhancing our lives rather than undermining them? These are questions we all need to ponder and contribute to. Inclusivity in this discourse is key to finding solutions that work for everyone. Policy and regulation are key. Governments and bodies must guide AI's growth, prioritizing ethics and societal good.
Hanh: 00:25:06
We need policies for worker protection, AI responsibility, and inclusion. and equal AI benefits. Education must adapt, too. As AI changes jobs, learning must equip us for this new world. This includes tech skills and nurturing creativity, critical thinking, and adaptability. We must rethink education to
Hanh: 00:25:24
suit these evolving needs. Finally, there needs to be a focus on developing safety nets and support systems for those impacted by AI driven changes. This goes beyond financial assistance. It's about providing resources and opportunities for retraining, re skilling, and finding new paths in an AI transformed world. Next, we'll examine essential
Hanh: 00:25:47
strategies for a smooth shift. Into the AI era. We'll discuss preserving human agency, forming a united vision for the future and updating education to align with AI in the closing part of our series, we focus on navigating towards a beneficial AI future. It's about creating systems that protect human influence, unite
Hanh: 00:26:15
us in our future goals and ensure inclusive support across society. A crucial aspect of this transition is maintaining human agency. As AI becomes more integrated into our workplaces and lives, we need to ensure that humans remain at the decision making core. This involves designing AI systems that complement human skills
Hanh: 00:26:36
and augment our capabilities. Rather than replace them. How can we create a I tools that empower workers rather than diminish their roles. Next, we must cultivate a shared vision in a clear road map for the future. This vision should be inclusive, taking into account the diverse needs and potential impacts on different segments of society.
Hanh: 00:26:59
We need to envision a future where the benefits of a I are equitably distributed. What does this inclusive future look like? And how do we chart a course towards it? To navigate this shift, retraining and reskilling initiatives are vital. The job market is evolving rapidly, and the skills that are in demand today may be obsolete tomorrow. We need programs and policies
Hanh: 00:27:23
that incentivize lifelong learning and make it accessible to all. How can governments, industries, and educational institutions collaborate to provide these opportunities? Our educational models need a fundamental reshaping. The focus should shift to skills that complement AI, like critical thinking, creativity, problem
Hanh: 00:27:43
solving, and emotional intelligence. The goal is not to compete with AI, but to synergize with it. How can we redesign our education systems to foster these skills from an early age? Finally, There is a need for ongoing dialogue and collaboration between various stakeholders, governments, businesses, educational institutions, and workers themselves.
Hanh: 00:28:08
This collaborative approach ensures that the transition to an AI driven future is not just technologically sound, but also socially responsible and ethically guided. In concluding redefining work in the age of AI, we see a complex journey towards an AI driven future. This path brings challenges and immense potential for growth and innovation. It reshapes human creativity and demands
Hanh: 00:28:32
our collective foresight and effort. We need the right frameworks to merge AI with human skills effectively. This way, we direct this change to reflect our values and open new opportunities. Standing at this transformative point, we must shape our AI future. This ensures it benefits all, redefining work to enrich our lives and advance human development.
Narrator: 00:29:04
As we wrap up today's AI50 Connect journey, we've delved deeper into the vast ocean of AI and data knowledge. Each word shared today isn't just information, it's a stepping stone to innovation. AI isn't just a tool. It's a revolution in our hands. It's redefining data, making it more alive, more
Narrator: 00:29:22
insightful, more transformative. Whether you're in tech or leading a business, AI is your game changer. It's about smarter, faster, more precise decisions. Thinking of AI in your business. Picture this, streamlined processes, trend spotting, minimized errors. And a team in synergy. It's not just profit growth.
Narrator: 00:29:43
It's a business evolution at AI50. We're more than a podcast. We're your AI compass, our mission to empower your business journey with bespoke AI and data strategies. We're crafting solutions that don't just innovate. They resonate with your unique ambitions. Curious about AI50's magic for your business.
Narrator: 00:30:04
We're a conversation away, reach out and let's transform your data into your most powerful ally. Keep the AI50 conversation going on LinkedIn. Join our community for cutting edge news and deep dives into AI. Stay ahead of the curve with Hanh Brown on LinkedIn, your go to source for AI trends and insights.
Narrator: 00:30:24
Hit subscribe on AI50 Connect, available on your favorite podcast platforms. Stay with us for more episodes that unravel the mysteries of AI, bringing experts right to your ears. For a visual feast, follow us on YouTube, from podcast highlights to exclusive interviews. It's all there waiting to amaze you. And if AI in your business is
Narrator: 00:30:43
more than a thought, it's a plan. Contact us. We're here to guide your AI journey towards smarter decision making and enhanced efficiency. Thank you for joining AI50 Connect. In this adventure through AI's evolving landscape, remember, you're not just keeping pace, you're defining the future. Until next time, explore,
Narrator: 00:31:03
innovate, and grow. Connect. Lead with AI50. See you on the next wave of innovation.
Hanh: 00:00:02
Our elders who once led active, vibrant lives may find themselves retreating into a shell. wary of the very movements that once were routine. In this episode, we'll not only examine the cutting edge technologies and innovations in fall detection, but also address the psychological and social dimensions of falls in the elderly.
Hanh: 00:00:25
We'll explore how fall detection impacts their mental health, their interactions with family and society, and their sense of security in the places they call home. Together, we'll go through the landscape of senior care, seeking answers and understanding the delicate balance between safety and independence.
Narrator: 00:00:48
Welcome to AI50, where technology's complexities meet daily life. Each episode delves into AI's vast impact, especially on older adults. Today, we explore AI in fall detection for the elderly. This tech is pivotal in elder care, enhancing safety and independence. It's AI as a guardian, alerting instantly during falls, reducing
Narrator: 00:01:12
response times and risks. Our host, Hanh Brown, makes AI clear and relevant. She simplifies complex AI ideas, linking them to everyday life and societal challenges. AI50 is more than just a podcast, it's a story hub sharing insights and AI developments. We cover healthcare innovations, business
Narrator: 00:01:30
strategies, and AI's daily influence. Our talks are enlightening and diverse, shedding light on AI's various roles. Each episode enriches your AI understanding. We discuss AI's uses, ethics, and societal impact. Join us for this engaging journey. We blend expert views, real life examples. And insightful talks.
Narrator: 00:01:55
Let's unravel AI's world together and Hanh, let's explore today's fascinating AI topic.
Hanh: 00:02:04
Welcome everyone to our latest episode in the Healthcare Innovation Series. Today, we address a critical yet often overlooked aspect of senior care, fall detection in older adults. We're committed to exploring this urgent issue and the solutions available to us. Let's start by picturing our loved ones, perhaps your parents or grandparents.
Hanh: 00:02:25
With each passing year, as they gracefully age, their vulnerability to falls increases exponentially. These aren't just minor stumbles. A simple slip can spiral into severe health consequences, robbing them of their cherished independence and impacting their overall well being. This makes understanding and preventing falls not just important, but essential.
Hanh: 00:02:47
However, the repercussions of falls extend beyond the physical injuries. Often, they instill a deep seated fear of falling again, leading to a vicious cycle of reduced mobility and loss of independence. This can significantly diminish the quality of life, leading to isolation and a sense of helplessness. Our elders, who once led active,
Hanh: 00:03:10
vibrant lives, may find themselves retreating into a shell, wary of the very movements that once were routine. Our discussion today transcends the realm of mere technology and methodologies for fall detection. We're delving into the very core of elder dignity and safety. How do we safeguard their autonomy while ensuring their well being?
Hanh: 00:03:34
How do we employ modern solutions without infringing on their right to a dignified life? These questions are fundamental as we explore the intersection of technology, ethics, and elder care. In this episode, we'll not only examine the cutting edge technologies and innovations in fall detection, but also address the psychological and social
Hanh: 00:03:59
dimensions of falls in the elderly. We'll explore how fall detection impacts their mental health, their interactions with family and society, and and their sense of security in the places they call home. Together, we'll go through the landscape of senior care, seeking answers and understanding the delicate balance between safety and independence.
Hanh: 00:04:21
Join us as we venture into this important discussion. Aiming to transform not just the way we detect falls, but how we care for our elders, honoring their journey with the respect and dignity they deserve. We'll explore various technological advances that assist in detecting falls, from wearable devices to advanced home monitoring systems.
Hanh: 00:04:47
Each method comes with its advantages and limitations, which we'll delve into. Through this episode, you'll gain insights into how these technologies work. Their impact on the lives of older adults and the balance between safety and privacy. We'll also address the challenges and limitations of current solutions. So join me as we navigate
Hanh: 00:05:07
through the intricacies of fall detection in older adults. It's a journey towards making our homes safer for our loved ones, and it starts now. In this segment, I'd like to share a personal story that deeply resonates with today's theme. Last year, a close family friend, age 75, experienced a fall.
Hanh: 00:05:31
This wasn't just a minor mishap. It was a moment that unveiled the hidden dangers that lurk in the everyday lives of our seniors. She was at home, a place where we all expect our loved ones to be safe and secure. However, it was there, in her own kitchen, where the unexpected happened. She slipped on a wet spot on
Hanh: 00:05:49
the floor, a seemingly harmless hazard that we all overlook. The fall resulted in a broken hip and a long, arduous journey to recovery. It took months of rehabilitation for her to regain mobility, and even then, the fear of falling again lingered. Casting a shadow over her once independent lifestyle. This incident was more
Hanh: 00:06:10
than a wake up call. It highlighted the fragility that comes with age, the importance of vigilant care and the need for supportive environments for our elderly. It also brought to light the psychological aftermath of such falls, the loss of confidence. The anxiety of moving freely and the dawning realization that their home
Hanh: 00:06:32
might not be as safe as they thought. This story is a poignant reminder of why we are discussing fault detection technologies and solutions today. Our aim isn't just to prevent physical harm, but also to preserve the confidence and independence that our elders cherish so deeply. So as we go further into the technological aspects, let's also keep in mind the human
Hanh: 00:06:59
element, the emotional and psychological impact these falls have on our loved ones. Falls in the elderly can lead to hospitalizations, prolonged recovery, and in some cases, a permanent loss of independence. It's a silent epidemic affecting numerous families. Maybe even yours. Understanding the risks and
Hanh: 00:07:20
preventive measures is paramount. Today's discussion goes beyond just statistics and technology. We're talking about maintaining the dignity and independence of our older generation. It's about creating a safe environment where they can live without fear. Our main focus will be on various methods of fall detection.
Hanh: 00:07:42
We'll explore wearable technologies like smart watches and fitness bands that monitor movement patterns and alert for falls. We'll look into home based solutions like video monitoring and pressure sensors. Each of these technologies offers a way to safeguard our loved ones, but they also bring challenges like compliance, privacy concerns,
Hanh: 00:08:05
and the limitations of technology. Consider this. If it were your loved one, which solution would you trust to protect them? How do you balance the need for safety with the desire for independence and privacy? Let's take a moment to truly personalize our discussion. Imagine a typical day in the life
Hanh: 00:08:22
of an elderly person you care about. Picture them moving around their home, engaging in everyday activities. Now, visualize the moment a fall occurs. This isn't just a theoretical exercise. For many, it's a daily reality. I want you to hold on to that image as we proceed. It's this personal connection that transforms our conversation
Hanh: 00:08:47
from abstract concepts into something palpably real and urgent. To deepen our engagement, I will be introducing interactive segments where you can pause the podcast and reflect. Maybe it's thinking about how the technologies we discussed could fit into the home you've pictured. Or, considering the emotional impacts these falls have on both
Hanh: 00:09:08
the elderly and their families. Your active participation is crucial. I encourage you to jot down your thoughts or even discuss them with friends and family. This isn't just my journey, it's ours collectively. So as we navigate these topics, remember the image you visualize and let that guide your engagement with our discussion.
Hanh: 00:09:30
Join me as we dissect these questions, understanding the importance and complexity of fall detection in older adults. Together, we'll explore how technology can bring peace of mind to families and security to our elders. As we delve into the practicalities of fall detection technologies, let's acknowledge the diversity
Hanh: 00:09:52
in our elderly population. Their lifestyles, health conditions, and living environments vary greatly. A one size fits all solution doesn't exist. Therefore, it's crucial to consider customizable and adaptable technologies. Picture a system that can be programmed based on individual mobility levels, health conditions, and even living spaces.
Hanh: 00:10:16
Imagine wearable devices with adjustable sensitivity levels or home monitoring systems that can be tailored to different room layouts. This level of customization not only enhances effectiveness, but also increases user compliance. It's about creating solutions that respect the individuality and preferences of each older adult.
Hanh: 00:10:39
As we discuss these technologies, think about their adaptability. How can they be molded to fit diverse needs and lifestyles? The future of fall detection lies in smart, flexible technologies that can be as unique as the individuals they aim to protect. As you listen, consider the practical applications of these
Hanh: 00:10:58
systems in various scenarios. Your insights could be invaluable in shaping more personalized and effective fall detection solutions. Before we delve into wearable devices, it's important to reflect on the diverse needs of our elderly population. No single solution suits everyone. Some older adults are tech savvy and active, readily adapting to
Hanh: 00:11:21
smartwatches or fitness bands. Others might find new technology overwhelming. Therefore, it's essential to choose fall detection tools that align with their comfort and lifestyle. As we explore wearable devices, let's keep in mind the need for simplicity. ease of use, and the capacity to customize settings according to
Hanh: 00:11:42
individual preferences and abilities. Let's dive into our first fall detection method, wearable devices. These are gadgets like smartwatches and fitness bands equipped with sensors like accelerometers and gyroscopes. These sensors detect changes in movement patterns. Potentially indicating a fall. Imagine a watch that not only
Hanh: 00:12:05
tells time, but also keeps an eye on your elderly relative's safety. If an unusual movement pattern is detected, like a sudden fall, the device can send an alert to caregivers or family members. This immediate notification can be crucial in providing timely assistance, but wearable devices are not without challenges.
Hanh: 00:12:27
The most significant is compliance. Ensuring that the user consistently wears the device. It's common for older adults who forget to wear these devices or find them uncomfortable. Also, what happens if the battery dies or the device malfunctions? Despite these challenges, wearable devices offer a layer of safety and assurance.
Hanh: 00:12:49
They're particularly useful for active older adults who are still mobile and independent. These devices also often come with additional health monitoring features, like heart rate tracking, which can provide valuable health insights. As we discuss these technologies, I'd like you to think about their practicality. How likely is it for your grandparents
Hanh: 00:13:07
or elderly relatives to use and benefit from such devices? Are there ways to make these gadgets more user friendly and adaptable to their lifestyle? Wearable devices are just one piece of the puzzle in fall detection. Their effectiveness relies on a combination of technology, user compliance, and practical design.
Hanh: 00:13:31
Let's continue to explore more methods as we seek the best solutions for keeping our elders safe. As we transition to discussing video monitoring, let's contemplate the balance between safety and personal space. While continuous monitoring can provide peace of mind, it can also raise concerns about privacy and independence. It's crucial to have open discussions
Hanh: 00:13:52
with our elders, understanding their comfort levels with being monitored. The key is to find solutions that offer security without impinging on the dignity and privacy they deserve. In this next segment, we'll explore how video monitoring works and address the complex interplay of safety, privacy, and autonomy. Moving on to our next fall
Hanh: 00:14:18
detection method, video monitoring. This system uses cameras installed in homes combined with artificial intelligence to monitor and analyze movement. When a fall is detected, alerts are sent to family members or caregivers. The advantage of video monitoring lies in its ability to provide continuous surveillance.
Hanh: 00:14:41
Unlike wearable devices that require the user to wear them constantly, video monitoring works independently. It's especially useful in common areas of the house where falls are likely to occur, like the living room or kitchen. However, the idea of being under constant surveillance can be uncomfortable for many. It raises serious privacy concerns.
Hanh: 00:15:03
Imagine having cameras in your home, watching your every move. How does that make you feel? It's crucial to balance the need for safety with respect for personal privacy. Another point to consider is the effectiveness of video monitoring in detecting falls accurately. Advanced AI algorithms are used to analyze movements and differentiate
Hanh: 00:15:24
between normal activities and falls. But these systems are not foolproof. They can sometimes miss a fall or generate false alarms, causing unnecessary worry. As we discuss video monitoring, reflect on its implications. Would you be comfortable installing such a system in your home? How would your elderly relatives feel about it?
Hanh: 00:15:45
Video monitoring presents a high tech solution to fault detection, but it comes with its own set of challenges. As we explore these technologies, it's essential to weigh their benefits against potential drawbacks, keeping in mind the comfort and dignity of our loved ones. Turning our attention to pressure sensors, we encounter a blend of subtlety and effectiveness.
Hanh: 00:16:10
These sensors, hidden within the home environment, offer a less intrusive approach to fault detection. Yet, their placement in sensitivity need careful consideration. As we explore this method, think about the layout of an elderly person's home. Where are the high risk areas? How can we strategically place these sensors to provide comprehensive coverage
Hanh: 00:16:35
without disrupting their daily life? Let's examine how pressure sensors can be a part of a dignified approach to fall prevention. Our next topic, in fall detection, is pressure sensors. These sensors are placed in strategic locations like floors, beds, or chairs. They detect changes in pressure, which can indicate a fall.
Hanh: 00:17:00
When a sudden pressure change is detected, an alert is triggered. The beauty of pressure sensors lies in their subtlety and non invasiveness. Unlike video monitoring, they don't intrude on personal privacy. They're hidden in everyday objects, seamlessly integrating into the home environment. This makes them an excellent option
Hanh: 00:17:17
for those concerned about privacy. However, pressure sensors have their limitations. Their effectiveness is confined to the areas where they are installed. What happens if a fall occurs away from these sensors? They also can't provide detailed information about the nature of the fall or the person's condition post fall.
Hanh: 00:17:39
Think about the layout of your home or the home of an elderly relative. Where would you place these sensors? How effective would they be in covering all the areas where a fall could occur? While pressure sensors offer a discrete way to monitor for falls, they need to be part of a broader system to be truly effective. They work best in combination with
Hanh: 00:17:58
other methods, covering areas that other technologies might miss. As we consider the use of pressure sensors, it's essential to understand their scope and limitations. They offer a layer of protection, but they're not a stand alone solution. The key is finding the right balance and combination of technologies to ensure comprehensive coverage
Hanh: 00:18:21
and safety for our elders. Next, we look at sound detection. A method that steps away from visual monitoring, offering a different layer of fall detection. This technology hinges on the sensitivity to specific sounds. A break from the eyes of a camera to the ears of a microphone. As we delve into this topic,
Hanh: 00:18:45
Let's consider the balance between effective fall detection and the ambient sounds of a household. How can we fine tune this technology to recognize the critical sounds of a fall while minimizing false alarms that can cause unnecessary distress? Another intriguing method in our exploration of fall detection technologies is sound detection.
Hanh: 00:19:10
This system utilizes microphones and audio analysis algorithms to detect sounds that may indicate a fall, such as a loud thump or a cry for help. Sound detection offers an interesting advantage. It doesn't rely on visual surveillance, thus addressing some privacy concerns associated with video monitoring. It's a less intrusive method.
Hanh: 00:19:32
Listening for specific sounds rather than continuously monitoring visual feeds. However, this method also has its challenges. The primary concern is distinguishing between normal sounds and those indicating a fall. False alarms can be frequent. Especially in environments with varying noise levels and like pressure sensors,
Hanh: 00:19:53
sound detection systems are limited in the information they provide post fall. Consider the practicality of sound detection in a home environment. How effective would it be in differentiating between a fall and other household sounds? How would you react to frequent false alarms? Sound detection adds an interesting
Hanh: 00:20:11
dimension to fall detection. It's a technology that requires fine tuning to be effective, yet offers a promising solution for non invasive monitoring. As we continue our discussion, think about how sound detection could be integrated into a comprehensive fall detection system. Could it be the answer to
Hanh: 00:20:31
balancing safety and privacy? Or is it too unreliable on its own? The goal is to find the best mix of technologies that offers peace of mind without being overly intrusive. In this critical part of our conversation, let's consider the emotional and psychological impacts of fall detection technologies on older adults. It's not just about the
Hanh: 00:20:56
mechanics of detection. It's about how these technologies make them feel. Are they experiencing a sense of constant surveillance or losing their autonomy? Imagine the emotional toll of feeling like your every move is being monitored. This psychological aspect is as important as the technological one. Let's also consider the
Hanh: 00:21:18
caregiver's perspectives. False alarms from these systems can lead to stress and anxiety. Each false alarm might cause unnecessary panic, and over time might lead to desensitization, reducing the effectiveness of these systems. We must strive for a delicate balance. A system sensitive enough to detect real falls, but intelligent
Hanh: 00:21:41
enough to minimize false positives. Think about the trust we place in these technologies and the impact on our mental well being. As we discuss these challenges, I urge you to consider not just the practicalities, but the human side of these technologies. How do they affect the day to day lives and emotions of those we're trying to protect?
Hanh: 00:22:04
Your thoughts on this are crucial. Let's aim for solutions that not only detect falls, but also preserve dignity and peace of mind. Let's address the significant concerns associated with fall detection technologies. First and foremost, privacy issues. In an era where surveillance is a hot topic, how do we ensure
Hanh: 00:22:28
that our safety measures don't infringe on personal privacy? It's a delicate balance between monitoring for safety and respecting personal space. Next, let's talk about false alarms. Imagine getting an alert every time there's a minor mishap at home. These false alarms can cause unnecessary stress and anxiety for both the elderly and their caregivers.
Hanh: 00:22:51
How do we refine these technologies to minimize these instances? There's also the issue of compliance, especially with wearable devices. We need to ensure that these devices are user friendly and comfortable. Encouraging consistent use. What strategies can be implemented to enhance compliance? The cost factor cannot be ignored.
Hanh: 00:23:13
Advanced fall detection systems, especially those requiring comprehensive home installations, can be quite expensive. Is the cost justified by the benefits they provide? Lastly, consider older adults with limited mobility. How effective are these systems for someone who spends most of
Hanh: 00:23:32
their time seated or in bed? We need solutions that cater to varying levels of mobility and activity. As we delve into these drawbacks, think about the practical implications and the real world challenges they present. How would you address these issues if you were designing a fall detection system? Your thoughts and feedback are invaluable. As we navigate this complex topic,
Hanh: 00:23:59
in today's episode, we've explored a range of fall detection technologies and their impact. Now, it's your turn to be part of this vital dialogue. Reflect on your loved ones and the technologies we discussed, which resonated most with you and why your experiences and viewpoints are invaluable. Have you witnessed a fall or
Hanh: 00:24:19
used any of these technologies? Share your stories with us. They're key to shaping the future of fall detection. Connect with us on social media, email, or leave comments on our platform. Your insights will help deepen our collective understanding of these solutions. Thank you for your active
Hanh: 00:24:37
participation in today's episode. Your engagement transforms this podcast into a collaborative journey of discovery and learning. Keep the conversation going by sharing your thoughts on our social media channels. Your perspectives not only enrich our discussions, but also contribute to a broader understanding of elder care.
Hanh: 00:24:58
Let's continue this discussion beyond today. Join our health conscious community. Share your views and interact with fellow listeners. We look forward to hearing from you until our next episode, continue exploring, questioning, and staying connected with us. The journey doesn't end here.
Hanh: 00:25:14
Let's keep learning and growing together. Stay safe and see you next time.
Narrator: 00:25:23
Another exciting AI50 Connect episode wraps up. And what a journey it's been. We dove into the world of AI and data, turning complex ideas into easy to grasp gems. AI is not just tech talk, it's a real game changer. For everyone, from tech enthusiasts to business leaders, AI is your go
Narrator: 00:25:42
to for smarter, faster decisions. Now, picture AI transforming your business. Making everything smoother, finding hidden opportunities, reducing mistakes, and firing up your team. It's not just improvement. It's a total game change. AI 50 is more than a podcast. It's your AI guide.
Narrator: 00:26:03
We bring you AI strategies that are not just smart, but also a perfect fit for your business goals. And guess what? We make it simple and exciting. Want to know how AI50 can uplift your business? Let's chat. We're here to turn your data into a superpower.
Narrator: 00:26:20
Stay connected with AI50 on LinkedIn. We're sharing the latest and greatest in AI, all in easy bites. And don't miss out on Hanh Brown's insights on LinkedIn. It's your shortcut to staying ahead in AI. Hit that subscribe button on AI50 Connect on your favorite platform. We've got more great AI talks and tips coming your way.
Narrator: 00:26:40
Check us out on YouTube for more cool stuff from podcasts to exclusive interviews. It's all there in fun, engaging videos, thinking of AI for your business, reach out. We're here to make AI work wonders for you. Thanks for being with us on AI 50 connect. Remember with AI, you're not just
Narrator: 00:26:57
keeping up, you're leading the way. See you next time for more AI excitement.
Hanh: 00:00:03
Consider Martha, a 78 year old who cherishes her independence. Living alone, she finds an empowering ally in AI driven smart home technology. Each morning, her home gently wakes her up with gradual lighting and the thermostat adjusts to her preferred temperature, creating a cozy atmosphere. As she moves through her day, if she forgets to turn off the stove, the
Hanh: 00:00:25
system sends her a gentle reminder. Offering not just comfort, but peace of mind. It's a testament to how AI can uphold dignity and independence in the golden years.
Narrator: 00:00:40
Welcome to AI 50, where we explore how artificial intelligence or AI is changing our world, especially for older adults. Each episode we take a close look at how this amazing technology is used in real life. Our host, Hanh Brown, is here to guide us through the world of AI. Hanh has a knack for explaining complex
Narrator: 00:00:58
ideas in a way that's easy to understand. She connects the dots between advanced AI and the ways it helps us in our everyday lives and work. AI50 is more than just talk about technology. We share stories and talk about the latest AI discoveries. We chat with experts to give you a full picture of how AI is being used today.
Narrator: 00:01:20
We cover everything from how it's changing healthcare to how it's used in businesses and how it touches our daily routines. In each show, we aim to make you think more about AI, not just the good stuff, but also the tough questions it brings up. We look at all sides to show how AI can be a positive force in our lives and for our older generations. Let's start this journey together.
Narrator: 00:01:44
We're going to mix in stories. Expert opinions and real world examples to make the world of AI clear and interesting. Hanh, let's dive into today's AI topic.
Hanh: 00:01:57
Thank you for that introduction. Hello and welcome everyone to AI50. I'm Hanh Brown, and it's great to have you with us today. In this episode, we're diving into revolutionizing business strategies, AI, data, and unified ecosystems. In this digital era, the landscape of business is undergoing a seismic shift. With the advent of artificial
Hanh: 00:02:23
intelligence, we are witnessing a revolution not seen since the dawn of the internet. AI is not just a tool. It's a visionary force that's redefining how we analyze data, make decisions and connect with one another. Today, we'll explore how AI and unified ecosystems are not just transforming the way businesses operate, but
Hanh: 00:02:45
also how they're influencing global markets and shaping entire industries. We're talking about a world where data isn't just numbers, but a narrative that tells us where we've been and where we're going. Join me. As we unravel the intricate tapestry of AI data, learning how it's woven into the very fabric of modern business strategies,
Hanh: 00:03:07
we'll dive into real world applications, the challenges and opportunities they present, and what this all means for the future of business and technology. We'll also be looking at the human side of this technological revolution. How does it affect the workforce, consumer behavior, and most importantly, our daily lives? From small startups to multinational
Hanh: 00:03:29
corporations, the ripple effect of AI's influence is vast and profound. So, whether you're a tech enthusiast, a seasoned entrepreneur, Or simply curious about the future of business in an AI driven world, this episode promises to offer valuable insights and thought provoking discussions. So sit back, relax, and let's embark on this journey of
Hanh: 00:03:55
discovery together on AI50. Let's plunge into the vibrant world of our first key element. Data integration and management. Imagine navigating the bustling digital universe where businesses are inundated with a deluge of data from a myriad of sources. This is the arena where AI emerges, not just as a game changer.
Hanh: 00:04:22
But as a masterful conductor orchestrating a symphony of information, it's like having a super efficient assistant who can quickly sift through mountains of data, integrate it, and present it in a way that's not just understandable, but also actionable. Imagine various data streams, customer interactions, sales figures, market trends, all coming together seamlessly.
Hanh: 00:04:47
This unified view is invaluable for businesses, helping them make informed decisions timely. Now, let's turn the lens towards older adults. How does this all tie in? In a world where isolation is a real concern for the older adults, AI driven data integration can help. It can enable social services and
Hanh: 00:05:05
family members to stay informed and engaged in the care process. Fostering a sense of community and support. You see, data integration and management powered by AI is not just a business tool. It's a beacon of hope for enhancing the quality of life for our aging population. But before we leap into the future with predictive analytics,
Hanh: 00:05:29
let's reflect for a moment. How many times have we wished for a glimpse into what's ahead? This next segment shows us how AI is making that wish a reality. Next, let's go into the realm of predictive analytics. It is like a modern day oracle for businesses, offering a glimpse into the future with the clarity of a crystal ball.
Hanh: 00:05:55
This AI driven tool analyzes past data to forecast future trends. It's like having a time machine that helps businesses anticipate market changes, consumer behavior, and potential risks. This foresight is invaluable for making strategic decisions that keep a business ahead of the curve. This means preventive measures can be taken much earlier, potentially
Hanh: 00:06:18
preventing hospital visits. Imagine wearable devices that alert healthcare providers about abnormal changes in vital signs, enabling prompt response to medical emergencies. You see, predictive analytics isn't just about forecasting sales for businesses. It's about forecasting a healthier, more engaged life for our seniors. Let's consider a scenario
Hanh: 00:06:42
that brings this to life. Imagine Emily, an 82 year old widow living in a small town. She has always been fiercely independent. But her Children worry about her health. Enter the world of AI driven predictive analytics. Emily wears a smart watch that monitors her vitals in activity. One day while gardening, her heart
Hanh: 00:07:02
rate shows irregular patterns. Something Emily is unaware of, but the AI system analyzing her data picks up on this anomaly. It immediately alerts her and her doctor, leading to early intervention that prevents a major heart episode. This is not just technology at work. It's a guardian angel invisibly and seamlessly protecting Emily, allowing her
Hanh: 00:07:28
to enjoy her independence without fear. Having seen how predictive analytics can safeguard health, let's now explore how AI's personalization creates unique experiences, not just in customer service, but in enhancing the lives of our senior community. Moving to our third element, personalization and customer experience. This is where AI really shines, creating
Hanh: 00:07:55
unique experiences for each customer. In the business world, it's about understanding individual customer preferences and tailoring services or products accordingly. This approach leads to higher satisfaction and loyalty, a win win for both businesses and consumers. AI driven personalization is not just a business strategy.
Hanh: 00:08:20
It's a way to ensure our aging population receives the attention and care they deserve in a manner that respects their individuality and dignity. For instance, consider Martha. A 78 year old who cherishes her independence. Living alone, she finds an empowering ally in AI driven smart home technology. Each morning, her home gently wakes
Hanh: 00:08:40
her up with gradual lighting and the thermostat adjusts to her preferred temperature, creating a cozy atmosphere. As she moves through her day, sensors discreetly monitor her activity, ensuring her safety without intrusion. The AI learns her routines like when she usually makes tea or watches her favorite shows, and it seamlessly adjusts lighting, sound, and temperature to her liking.
Hanh: 00:09:06
Even more, this technology isn't just about reacting to Martha's actions. It anticipates her needs. If it's unusually cold, the heating turns up a notch. If she forgets to turn off the stove, the system sends her a gentle reminder. It's as if her home understands her offering not just comfort, but peace of mind.
Hanh: 00:09:26
This personalization extends beyond mere convenience. It's a testament to how AI can uphold dignity and independence in the golden years for Martha and many like her. AI in her home isn't just a series of gadgets, it's a companion, an extension of her ability to live her life to the fullest on her own terms. Now let's discuss our fourth crucial
Hanh: 00:09:52
element, efficiency and automation. In the realm of business, AI is the powerhouse driving efficiency. It automates routine tasks, streamlines operations, and frees up human resources for more complex and creative tasks. This automation leads to cost savings, increased productivity, and a higher level of consistency in business processes. But how does this translate to
Hanh: 00:10:18
benefits for our aging population? Well, efficiency and automation hold great promise in enhancing the daily lives of older adults. Consider smart homes equipped with AI technology previously discussed. They can automate tasks like adjusting thermostats, turning off lights, or even monitoring for safety hazards. This not only makes life easier for
Hanh: 00:10:40
seniors, but also safer, allowing them to maintain their independence longer. Efficiency and automation through AI can also aid caregivers by reducing their workload and stress, ensuring they can provide better care. From automated appointment scheduling to tracking health metrics, these technologies can enhance the caregiving experience.
Hanh: 00:11:04
Efficiency and automation are not just business optimizations. They are vital tools in supporting the autonomy, health, and well being of our senior citizens. Our fifth key element is real time decision making. In the digital era, AI has empowered businesses to make decisions at an unprecedented speed.
Hanh: 00:11:27
Real time data analysis means companies can respond instantly to market changes, customer feedback, and operational challenges. This agility is crucial in staying competitive and meeting customer expectations efficiently. For older adults, real time decision making powered by AI can have profound implications.
Hanh: 00:11:47
Especially in health care and emergency response. Imagine a system that instantly analyzes health data from wearable devices, detecting anomalies like irregular heartbeats or sudden falls. This immediate analysis can trigger timely medical interventions, potentially saving lives. In a population where quick
Hanh: 00:12:07
response can be critical, this aspect of AI is invaluable. Real time decision making can enhance the daily lives of seniors through smart home technologies. From automatically adjusting lighting and temperature for comfort and safety, to providing immediate assistance through voice activated systems, These technologies can make independent living
Hanh: 00:12:28
safer and more enjoyable for the elderly. You see, real time decision making through AI is more than a business efficiency tool. It's a lifeline for our aging population, offering safety, independence, and peace of mind. While AI streamlines business processes, its role in personalizing the customer experience showcases its versatility.
Hanh: 00:12:52
Let's go into how AI tailors services to individual needs, transforming both customer engagement in businesses and daily life for the older adults. Moving on to our sixth element, market intelligence and competitive analysis. Here AI acts as a powerful ally for businesses. It sifts through vast amounts of market data to provide insights on
Hanh: 00:13:18
consumer trends, competitor strategies, and emerging market opportunities. This intelligence is crucial for businesses to stay ahead, adapt strategies, and seize new opportunities. When it comes to older adults, the application of AI in market intelligence can lead to more age inclusive products and services. By analyzing trends and preferences
Hanh: 00:13:38
within the senior demographic, businesses can tailor their offerings to better meet the needs of this group. This could range from healthcare products and services to leisure and technology offerings. Also, competitive analysis through AI can encourage innovation in fields particularly relevant to seniors, such as assistive technologies,
Hanh: 00:14:01
senior friendly transportation options, and accessible entertainment. By understanding the gaps and needs in the market, businesses can develop solutions that significantly improve the quality of life for older adults. Let's talk about risk management and security. Thank you. In the business world, AI is a crucial
Hanh: 00:14:23
ally in identifying and mitigating risk. From financial fraud to cybersecurity threats, AI systems can detect patterns and anomalies that might indicate a risk, allowing businesses to act timely to protect their assets and reputation. For the aging population, this aspect of AI can provide a significant safety net. As seniors become more reliant on technology, they also become
Hanh: 00:14:51
more vulnerable to cyber threats. AI can offer enhanced security measures to protect their personal and financial information online. It can detect unusual activities in bank accounts or alert them to potential scams, which older adults often fall prey to. You see, AI driven security systems in homes or senior care communities can ensure a safer living environment.
Hanh: 00:15:16
These systems can monitor for hazards like gas leaks, fires, or intruders, providing peace of mind for both seniors and their families. Risk management and security through AI, therefore, extend beyond business benefits to play a vital role in safeguarding the well being and dignity of our senior citizens. Our eighth topic is employee safety.
Hanh: 00:15:41
Productivity and Training. AI is revolutionizing the workplace by enhancing employee productivity. It offers tools for better task management, provides insights for optimizing workflows, and even personalizes training programs to improve employee skills and knowledge. Now, when we think of older adults in the workforce, AI's
Hanh: 00:16:03
role becomes even more impactful. For seniors still in the job market or those seeking to re enter it, AI driven training programs can be a boon. These programs can be tailored to their learning pace and style, making it easier for them to acquire new skills or update existing ones. This is especially important in a rapidly changing job market
Hanh: 00:16:24
where staying current is crucial. Remember, AI tools can assist older employees in managing their tasks more efficiently, reducing physical strain and mental stress. Ergonomic AI solutions can adapt work environments to the unique needs of older workers, promoting a healthier, more inclusive workplace. In this way, AI's contribution to employee
Hanh: 00:16:45
productivity and training is not just about enhancing business performance. It's about empowering an often overlooked segment of our workforce. The older adults ensuring their valuable experience and wisdom are not lost. Now, let's talk about innovative business models. Our ninth topic. AI is not just changing existing
Hanh: 00:17:10
business practices, it's paving the way for entirely new models. From subscription services to on demand platforms, AI is enabling businesses to innovate, offering customized and flexible solutions to their customers. For the aging population, these innovative business models can offer services and products that cater specifically to their needs.
Hanh: 00:17:35
Think of subscription based healthcare services or on demand transportation tailored for seniors. These models provide convenience and accessibility, which are crucial for older adults, especially those with mobility or health issues. AI driven platforms can connect seniors with various services, from grocery delivery to home care.
Hanh: 00:17:57
All accessible with a simple click. This not only fosters independence, but also ensures that the older adults have access to the services they need in a timely and efficient manner. Basically, AI's role in driving innovative business models is creating a more inclusive and accessible world for our seniors. ensuring they have the resources
Hanh: 00:18:16
and support they need to thrive. Our final topic for today is sustainability and environmental impact. In this era of climate change, AI is a powerful tool in promoting sustainable practices. It helps businesses reduce waste, optimize energy use, and lower their carbon footprint. AI's ability to analyze vast data sets
Hanh: 00:18:41
can lead to more environmentally friendly business operations and product designs. For older adults, the environmental benefits of AI have direct and indirect implications. Cleaner air, reduced pollution, and healthier ecosystems contribute to a better quality of life for everyone, including seniors. Also, AI driven sustainability efforts
Hanh: 00:19:03
in urban planning can lead to more senior friendly cities, with green spaces and pollution free environments. Sustainable practices in healthcare and product design ensure that the needs of the elderly are met without compromising the health of our planet. This balanced approach is key in building a future that is both age friendly and environmentally conscious.
Hanh: 00:19:29
So let's look ahead. Imagine a world just a few years down the line where AI has evolved beyond our current imagination. We might see AI systems that not only manage health and wellness for the older adults with precision, but also offer companionship, simulating human empathy and understanding. In business, think of AI that can not
Hanh: 00:19:49
only analyze current market trends, but also creatively predict new ones, shaping industries in ways we've yet to conceive. The fusion of AI with emerging technologies, like quantum computing and nanotechnology, could revolutionize how we approach everything from urban planning to personal health care. It's a future ripe with possibilities, challenges, and opportunities.
Hanh: 00:20:16
As we continue to innovate and integrate AI into our lives, Let's consider how can we ensure these advancements benefit, not just the business world, but also enhance the lives of our older adults. The future of AI is not just about technological prowess. It's about building a world that is inclusive, Thoughtful and forward looking where technology serves every generation.
Hanh: 00:20:40
As we conclude this episode, let's reflect on our discussion today. We explored data integration's role in transforming senior healthcare, converting vast data into empowering insights. Through predictive analytics, we saw AI's dual role in business forecasting and as a protector for our seniors health. We discussed into A. I.
Hanh: 00:21:01
S. Realm of personalization and customer experience, highlighting its impact beyond business, enriching the lives of our elderly. We observed AI driven efficiency and automation, underlining its support for the independence and dignity of older adults. From intelligent homes adapting to
Hanh: 00:21:19
their inhabitants, to healthcare services designed for comfort, AI has proven to be an invaluable ally for a better life in the golden years. Today's discussion paints a vivid picture. A future where A. I. Is deeply interwoven with our lives. It's not just about business growth. It's about nurturing care and
Hanh: 00:21:39
support, especially for our seniors. This narrative goes beyond technology. It's about an A. I. Empowered world that enriches life for every age. As we move forward in the AI era, let's embrace its potential and challenges, always mindful of its profound influence on society.
Hanh: 00:21:59
Thank you for joining me on AI50, where we unravel the complexities of technology and its impact on our world. Until next time, keep exploring, keep questioning, and keep envisioning a future where technology and humanity harmoniously coexist. And now we turn to you, our listeners. How do you see AI impacting your life or the lives of those around
Hanh: 00:22:22
you, especially our older adults? We invite you to share your thoughts and stories. Reach out to us on AI50 and let's continue this important conversation. Together, we can shape a future where technology serves all generations.
Narrator: 00:22:40
And so we conclude another insightful episode of AI50 Connect, your trusted source for insights into AI and data. Today's episode has hopefully expanded your understanding and piqued your interest in the transformative world of artificial intelligence, especially in its application to business and beyond. In the realm of AI, we're not just
Narrator: 00:22:59
observers, we're active participants. This technology is revolutionizing our approach to data, making it more intuitive. Insightful and impactful. Whether you're a tech enthusiast or a business leader, AI's ability to enhance data driven decision making, provide instant insights, and boost analytical efficiency is something
Narrator: 00:23:21
that can truly change the game. For those envisioning the integration of AI in your business strategy, Think about its potential to streamline operations, identify emerging trends, reduce errors, and foster a collaborative work environment. These benefits go beyond just improving your bottom line. They're about transforming
Narrator: 00:23:43
your business's core dynamics. At the heart of this podcast is AI50, your ally in navigating the AI landscape. Our passion lies in empowering businesses with AI and data driven strategies. We're committed to developing solutions that not only drive innovation and efficiency, but also align with your unique business goals. Curious about how AI50 can
Narrator: 00:24:05
revolutionize your business? We're just a conversation away. Reach out and let's explore how AI can turn your data into a strategic asset. Keep in touch with AI50 on LinkedIn for the latest news, insights, and a behind the scenes look at our podcasts. Join a community that's leading the conversation on AI advancements and applications.
Narrator: 00:24:28
Remember to follow Hanh Brown on LinkedIn. Stay connected with Hanh's valuable insights and stay at the forefront of AI developments and discussions. And don't forget to subscribe to AI50 Connect on your favorite podcast platform. Stay tuned for more episodes where we dive into exciting AI topics, bringing expert voices and actionable insights to your ears.
Narrator: 00:24:51
For more visual content, follow us on YouTube. We have an array of engaging content waiting for you, from podcast episodes to exclusive interviews and much more. It's a fantastic way to engage with our content visually. Lastly, if you're considering leveraging AI in your business operations, don't hesitate to contact us.
Narrator: 00:25:11
We're here to assist you in harnessing AI for data driven decision making, gaining real time insights, and enhancing your business efficiency. Thank you for listening to AI50 Connect. It's been a pleasure having you with us on this journey through the evolving world of artificial intelligence. Remember, in this data driven age with AI, you're not just following
Narrator: 00:25:33
trends, you're setting them. Until our next episode, keep exploring, stay connected, and lead the way with AI50 Connect. See you next time.
Hanh: 00:00:03
AI's ability to analyze data in depth raises questions about customer privacy and data security. Baby boomers having built businesses on customer trust must navigate these concerns carefully, ensuring that their use of AI
Hanh: 00:00:17
respects and protects customer privacy. You see, the ethical use of AI in data analysis is not just a technical challenge, but a moral one.
Narrator: 00:00:31
Welcome to AI50, where the complexities of technology intersect with practical, everyday applications. In each episode, we embark on an insightful journey into the world of artificial intelligence, exploring its significant impact across various sectors, and notably on the lives of older adults. Join us as our host, Hanh Brown, brings clarity and relevance to AI topics.
Narrator: 00:00:56
Hanh's grounded approach makes even the most complex AI concepts both understandable and applicable to our daily lives in the broader societal challenges. AI50 is more than a podcast. It's a platform for sharing stories, insights, and exploring the latest developments in AI. Whether we're discussing advancements in healthcare, Innovative
Narrator: 00:01:17
business strategies or AI's subtle influences on our daily routines. Our discussions are as enlightening as they are varied. Each episode is an opportunity to deepen your understanding of AI and its multifaceted role in today's world. We'll look at AI's practical uses, ethical considerations, and its evolving place in our society.
Narrator: 00:01:41
Let's begin this engaging journey together. With a mix of expert opinions, real world examples, and insightful discussions, we're set to demystify AI and bring its wonders closer to you. Hanh, let's dive into today's topic.
Hanh: 00:02:00
Welcome to AI50 Connect, the podcast where we dive deep into the intersections of technology, business, and our daily lives. I'm your host, Hanh Brown, and today we're exploring a fascinating topic that's reshaping the business world, human AI collaboration with a special focus on baby boomer entrepreneurs. Imagine stepping into a world
Hanh: 00:02:24
where technology wasn't just a part of everyday life, but shaped it. That's the world baby boomers grew up in. Now they're at the forefront of a new era where AI is not just a tool, but a partner in business. What does this collaboration look like? It's not about AI taking over, but enhancing the human element. For Baby Boomer entrepreneurs who
Hanh: 00:02:47
have a wealth of experience, AI offers a new lens to view data, market trends, and customer behaviors. Consider a Baby Boomer running a local store. They know their customers understand their preferences, but might struggle with the sheer volume of data from online sales. Here, AI steps in analyzing data patterns, predicting trends, helping
Hanh: 00:03:11
them make informed decisions. This collaboration faces challenges. Sure, there's a learning curve. Trusting algorithms over years of experience isn't easy, but when embraced, it's transformative. It's about combining wisdom with technology, intuition with data. As baby boomers navigate this landscape, they're not just adapting,
Hanh: 00:03:39
they're innovating, merging their rich experience with the power of AI. This isn't just about keeping up, it's about leading the way in a digital age. So what does this mean for the future of business? It signifies a new era of collaboration where experience meets innovation, where AI complements human insight. That's the power of human AI collaboration
Hanh: 00:03:59
for Baby Boomer entrepreneurs. Continuing from our discussion on AI's role in enhancing decision making, let's explore which types of data analysis are particularly well suited for AI assistance in businesses led by Baby Boomers. In the realm of business, not all data is created equal. For baby boomer entrepreneurs, certain types of data analysis
Hanh: 00:04:29
can benefit immensely from AI. Take, for example, customer behavior analysis. With AI, businesses can sift through vast amounts of customer interaction data to uncover patterns and preferences. This is invaluable for tailoring marketing strategies or enhancing customer service. Another area is financial forecasting. AI algorithms can analyze market
Hanh: 00:04:51
trends and financial histories to predict future financial scenarios. This is a game changer for baby boomers. Who can now blend their financial acumen with predictive insights to make more strategic investment decisions. Supply chain management is yet another field ripe for AI intervention. AI can optimize inventory levels, predict supply chain disruptions, and
Hanh: 00:05:16
even recommend cost saving measures. For baby boomers, running businesses With complex supply chains, this is a crucial advantage. The beauty of AI in these scenarios is its ability to handle large volumes of data with speed and precision. A task that would be overwhelming, if not impossible, for humans alone. This doesn't mean
Hanh: 00:05:38
replacing human oversight. Rather, it's about using AI as a tool to extend the capabilities. and reach of the business owner. A. I. S. Ability to process and analyze large data sets is particularly beneficial in areas like customer behavior analysis,
Hanh: 00:05:53
financial forecasting and supply chain management for baby boomer entrepreneurs. This presents a unique opportunity to combine their experience with A. I. S. Efficiency, leading to smarter, more informed business decisions. Let's go further. Into how AI can compliment the
Hanh: 00:06:16
expertise of baby boomer entrepreneurs. A critical aspect to consider is the types of data analysis that are most effectively augmented by AI. For Baby Boomer business owners, recognizing where AI can make a significant impact is key. A prime area is customer behavior analysis. AI tools excel in parsing
Hanh: 00:06:37
through large datasets to reveal customer trends and preferences. This ability is invaluable for Baby Boomers aiming to understand and adapt to rapidly evolving market demands. Another domain where AI shines is in financial forecasting. By analyzing market trends in historical financial data, AI can provide predictive insights.
Hanh: 00:07:01
aiding baby boomers in making more informed investment and business strategy decisions. Supply chain management also greatly benefits from AI intervention. AI's predictive capabilities can be leveraged to optimize inventory, foresee potential disruptions, and suggest efficiency improvements. For businesses with complex
Hanh: 00:07:20
logistics, this can be transformative. Imagine Sarah, a baby boomer who runs a family owned bakery. For years, she relied on intuition for stock management. However, when she integrated AI into her inventory system, she discovered surprising patterns. Certain pastries were in higher demand on rainy days.
Hanh: 00:07:42
By adjusting her stock based on AI predictions, Sarah was able to reduce waste and increase sales, showing the power of blending AI insights with human experience. In each of these areas, AI's strength lies in handling and analyzing vast quantities of data swiftly and accurately, tasks that are challenging and time consuming for human analysts.
Hanh: 00:08:05
This doesn't imply that AI replaces human judgment. Instead, it serves as a powerful tool, extending the analytical reach of the business owner and complementing the rich experience with cutting edge data processing capabilities. So, for Baby Boomer entrepreneurs, understanding and utilizing AI in specific data analysis areas,
Hanh: 00:08:24
like customer behavior, financial forecasting, and supply chain management, can lead to more strategic, data informed business decisions. Having explored the specific types of data analysis suitable for AI in Baby Boomer businesses, let's shift our focus to an intriguing question. How does AI actually go about identifying patterns and insights in data?
Hanh: 00:08:53
This isn't just about the technical capabilities of AI, but also about how these capabilities can be uniquely leveraged by baby boomer entrepreneurs. Imagine AI as a kind of digital alchemist transforming raw data into data. Insightful gold. AI uses sophisticated algorithms to sift through vast datasets, uncovering patterns that might not be
Hanh: 00:09:16
immediately apparent to the human eye. It's like having a super powered assistant who can spot trends and anomalies at an unprecedented scale and speed. But here's an out of the box perspective. AI in the hands of a baby boomer entrepreneur isn't just a tool for analysis. It becomes a bridge between generations of business wisdom.
Hanh: 00:09:40
These entrepreneurs can use AI not only to validate their intuitions and experiences, but also to challenge and refine them. It's a dialogue between the tried and true and the cutting edge. For instance, consider a baby boomer who runs a retail chain. Traditionally, they might rely on sales reports and market research to make stocking decisions.
Hanh: 00:10:02
With AI, they can dive deeper, understanding customer behaviors at a granular level. AI might reveal that certain products previously overlooked have the potential for high demand in specific locations. It's this combination of AI's data driven insights and the entrepreneur's deep market knowledge that can uncover hidden opportunities.
Hanh: 00:10:25
AI's ability to identify patterns and insights in data is like adding a turbocharger to the baby boomer's business acumen. It's not about replacing human intuition, but augmenting it with powerful data driven precision. As we discuss how AI identifies patterns in data, let's consider the emerging field of quantum computing.
Hanh: 00:10:47
This technology promises to exponentially speed up data processing, potentially unlocking new levels of insight for baby boomer entrepreneurs. Imagine analyzing market trends, not in days, but in seconds. Let's go further into the interplay between AI and baby boomer entrepreneurs. A critical aspect emerges. The ethical considerations
Hanh: 00:11:13
in AI data analysis. This isn't just about how AI works, it's about how it should work, particularly in the hands of experienced business leaders. Ethical AI is more than a buzzword, it's a guiding principle. For baby boomers who have seen the evolution of business ethics over decades, integrating AI into their businesses brings unique responsibilities.
Hanh: 00:11:39
It's about ensuring that AI systems are not only efficient, but also fair and transparent. Consider the impact of data bias. AI systems are only as good as the data they're fed. If this data reflects historical biases, AI's decisions and insights could perpetuate these issues. Baby boomer entrepreneurs
Hanh: 00:11:58
with their rich experience. are uniquely positioned to recognize and correct these biases. They can bring a level of oversight and ethical consideration that is crucial in today's data driven age. Another vital aspect is privacy. AI's ability to analyze data in depth raises questions about customer privacy and data security.
Hanh: 00:12:22
Baby boomers, having built businesses on customer trust, must navigate these concerns carefully. Ensuring that their use of AI respects and protects customer privacy. You see, the ethical use of AI in data analysis is not just a technical challenge, but a moral one. It's about blending the efficiency of AI with the wisdom and ethical
Hanh: 00:12:45
standards of seasoned entrepreneurs. This synergy can lead to not only more successful businesses, but also more responsible ones. Let's consider Mike, a baby boomer entrepreneur with a strong ethical stance. When implementing AI in his business, he noticed that the AI's hiring recommendations were skewed towards a certain demographic.
Hanh: 00:13:07
Concerned about unconscious bias, Mike worked with his team to retrain the AI with a more diverse data set. Showcasing the importance of ethical oversight in AI systems. Baby boomer entrepreneurs have the opportunity to set a benchmark in ethical AI usage, proving that technology and morality can coexist harmoniously in the business world.
Hanh: 00:13:34
Moving from the ethical implications, another vital dimension to consider in the realm of human AI collaboration is ensuring the accuracy and reliability of AI driven insights. Transcription Particularly in businesses run by baby boomers in an era where data is king, the accuracy of A. I. S.
Hanh: 00:13:53
Analysis is paramount. But here's a thought. Accuracy isn't just about the data itself. It's also about how it's interpreted baby boomer entrepreneurs with their years of industry experience play a crucial role in this. They're not just passive recipients of A. I. S.
Hanh: 00:14:12
Insights. They're active interpreters. Applying their context and understanding to validate these insights. Imagine a scenario where AI provides a forecast based on current market trends. A baby boomer business owner could cross reference this with their first hand knowledge of past market shifts, adding a layer of depth to the AI's predictions.
Hanh: 00:14:34
This collaboration can lead to more grounded and robust business strategies. However, ensuring reliability in AI also means being aware of its limitations. Thanks. AI is an incredibly powerful tool, but it's not infallible. It requires continual monitoring and updating, especially as market conditions and business environments evolve.
Hanh: 00:14:57
For baby boomers, this might mean a shift in mindset, from seeing AI as a one time solution to viewing it as an ongoing partner in their business journey. In a real world application, consider a baby boomer run logistics company using AI for route optimization. Initially, the AI suggested faster routes, but they weren't always reliable during peak hours.
Hanh: 00:15:20
By incorporating real time traffic data and the driver's experiential feedback into the AI system, the company significantly improved route accuracy, exemplifying the importance of blending AI insights with human input. Remember, the reliability and accuracy of AI driven insights in baby boomer businesses hinge on a balance between advanced technology
Hanh: 00:15:45
and seasoned human judgment. It's about creating a synergy where AI's data capabilities are enhanced by the entrepreneur's contextual knowledge and experience. In ensuring the reliability of AI insights, the key is AI explainability. Understanding why AI makes certain decisions. This transparency is vital for baby boomer
Hanh: 00:16:05
entrepreneurs, ensuring they can trust and effectively utilize AI recommendations. Let's pivot now to a crucial aspect of this discussion. The skills necessary for baby boomer entrepreneurs when working with AI in data analysis. This is about bridging the gap between seasoned business wisdom and the new world of artificial intelligence.
Hanh: 00:16:33
First off, a fundamental understanding of AI is key. I'm not talking about becoming tech experts, but having enough knowledge to ask the right questions and make informed decisions. It's like learning a new language. enough to navigate a foreign country successfully. Critical thinking is
Hanh: 00:16:51
another essential skill. With AI providing insights, baby boomers need to critically assess this information, understanding its relevance to their specific business context. It's about merging AI's technical insights with human intuition and experience. Adaptability is also vital. The tech world evolves rapidly. Baby boomers need to stay
Hanh: 00:17:14
agile, willing to learn and adapt to new tools and methods. This doesn't mean abandoning tried and tested practices, but augmenting them with new technologies. Lastly, collaboration skills. Working with AI is a team effort. It involves interacting with data scientists, engineers, and other stakeholders.
Hanh: 00:17:35
Effective communication and collaboration can enhance the AI integration process, leading to better outcomes. So, for Baby Boomers, it's not just about having business savvy. It's about complementing that savvy with a foundational understanding of AI, critical thinking, adaptability, and collaboration skills. This combination is what will set them
Hanh: 00:17:55
apart in a data driven business landscape. Now let's dive into how AI handles different types of data in baby boomer businesses, particularly unstructured versus structured data. Understanding this distinction is key in leveraging AI effectively. Structured data is organized, often in databases or spreadsheets. Think sales figures or
Hanh: 00:18:23
customer demographics. AI excels in analyzing this type of data, identifying trends and making predictions. It's like fitting puzzle pieces together in a well defined space. Unstructured data, however, is more complex. This includes text, images, or social media posts. Here, AI has to interpret data
Hanh: 00:18:44
that's not neatly categorized. It's a bit like reading a novel and trying to grasp the underlying themes and motifs. For Baby Boomers, the challenge is in harnessing AI to handle both types of data. Structured data might be more familiar territory, but unstructured data offers a wealth of insights into customer preferences and market trends.
Hanh: 00:19:08
It's about striking a balance, using AI to analyze sales figures. While also understanding customer sentiments expressed through reviews or social media. The key here is versatility. AI's ability to process both structured and unstructured data opens up new avenues for business intelligence. For baby boomers, adapting their
Hanh: 00:19:29
strategies to include both can lead to more comprehensive, nuanced business insights. Moving forward. Let's consider the latest advances in AI for business data analysis and their implications for baby boomer entrepreneurs. Staying abreast of these developments is crucial in maintaining a competitive edge.
Hanh: 00:19:54
One exciting advancement is in Natural Language Processing, or NLP. This allows AI to interpret and respond to human language in a way that's more intuitive and meaningful. For baby boomers, this means AI tools can now analyze customer feedback, social media conversations, or even emails more effectively, providing richer insights. Another breakthrough is
Hanh: 00:20:16
in Predictive Analytics. AI can now forecast market trends, customer behavior, and even potential business risk with greater accuracy. This is a game changer for baby boomers, enabling them to plan more strategically based on AI's foresight. AI is also becoming more accessible and user friendly. This means baby boomer entrepreneurs
Hanh: 00:20:38
don't need to be tech experts to leverage AI tools with more intuitive interfaces. In clear outputs, AI is becoming a more integral part of the business toolkit. Lastly, the integration of AI with other emerging technologies, like the Internet of Things, is opening new horizons. Imagine AI not just analyzing data from traditional sources, but also from connected devices, providing a
Hanh: 00:21:06
360 degree view of business operations. A breakthrough in AI's predictive analytics was utilized by a small, baby boomer owned retail chain. By leveraging AI to analyze local buying patterns and social media trends, the business was able to anticipate a rising demand for eco friendly products. This foresight allowed them to adjust their inventory early, leading
Hanh: 00:21:32
to a 30 percent increase in sales in that category, demonstrating the tangible benefits of staying abreast with AI advancements. Looking at the latest AI advancements, let's not overlook the fusion of AI with augmented reality. Imagine baby boomer entrepreneurs exploring their business data through interactive 3D
Hanh: 00:21:50
visualizations, making complex data more intuitive and actionable. These advancements show that AI is not just a static tool, but an evolving partner in business. For Baby Boomers, staying informed and open to these developments can lead to more innovative, data driven business strategies. As we wrap up our exploration of human
Hanh: 00:22:15
AI collaboration in business, let's focus on how small and medium sized enterprises led by Baby Boomer entrepreneurs can leverage AI for data analysis. This is about making AI accessible and beneficial, even for smaller businesses. Firstly, it's important to recognize that AI is not just for the big players. Advances in technology have made AI tools more affordable and
Hanh: 00:22:42
accessible for smaller businesses. It's about finding the right tools that fit the specific needs and scale of a business. For small and medium sized baby boomer enterprises, A. I. Can be a game changer in understanding customer behaviors, optimizing operational efficiencies and
Hanh: 00:22:57
identifying new market opportunities. It's about using AI to do more with less, analyzing customer data to personalize marketing efforts or optimizing supply chains to reduce costs. However, the key is not just in adapting AI, but in integrating it with existing business practices. It's about enhancing the wisdom and experience of baby boomers
Hanh: 00:23:23
with data driven insights. This integration requires a strategic approach. Identifying areas where AI can have the most impact and starting small with gradual implementation. Also, it's crucial for these enterprises to invest in upskilling their teams, ensuring that employees are equipped to work alongside AI tools.
Hanh: 00:23:44
This investment in human capital complements the technological investment, creating a symbiotic relationship between AI and the workforce. For smaller enterprises, an exciting application of AI is the concept of digital twins. These are virtual replicas of businesses, where baby boomers can simulate changes, like market shifts
Hanh: 00:24:03
or new product launches, before applying them in the real world. In conclusion, for small and medium sized baby boomer businesses, AI is not a distant, futuristic concept. It's a present day tool that, when used strategically, can lead to significant business growth and innovation. It's about embracing the power of AI to complement and enhance
Hanh: 00:24:28
their rich business experience. As we wrap up, let's look back at what we've covered. We started with how baby boomer entrepreneurs work with AI. It's like mixing their experience with new tech for better business decisions. We talked about where AI helps the most, like understanding customers or planning finances.
Hanh: 00:24:49
We saw how AI can spot trends in all kinds of data, helping business owners make smarter choices. We also touched on being careful with AI. It's powerful, but needs to be used right, respecting people's privacy, and avoiding biases. Then we looked at the latest AI tools. These are getting easier to use, helping even small businesses.
Hanh: 00:25:10
It's about picking the right tool and learning a bit about how it works. In all this, the key is balancing old school business smarts with new tech. It's not just about having the latest gadget. It's about using it in a way that makes sense for your business. As we say goodbye, remember, AI is a tool. It's there to help, but it
Hanh: 00:25:29
doesn't replace the human touch. For baby boomer entrepreneurs, blending their experience with AI could be the next big step. Thanks for joining me on this journey. Keep exploring and finding new ways to grow your business. Until next time.
Narrator: 00:25:48
And that wraps up another enlightening episode of AI50 Connect. Your go to podcast for all things AI and data. We hope today's discussion has provided you with valuable insights and sparked your curiosity about the endless possibilities of AI in the world of business and beyond. It's a revolutionary approach
Narrator: 00:26:04
that's reshaping how we interact with information. It's about making data driven decisions, gaining real time insights, and enhancing efficiency in data analysis. This method opens up a world of accessibility to information, even for those without a technical background, encouraging interactive exploration and personalized insights.
Narrator: 00:26:28
And if you're wondering how to leverage these advantages in your own business, think about the potential for error reduction, trend identification, cost effectiveness, and improved collaboration. These are not just buzzwords, they're tangible benefits that can transform the way you operate and compete in today's fast paced, data driven environment. Now let's take a moment to spotlight
Narrator: 00:26:49
AI50, the force behind this podcast. At AI50, we're dedicated to helping businesses like yours harness the power of AI and data. Our expertise lies in crafting tailored AI solutions that drive efficiency, innovation, and growth. Whether you're looking to enhance decision making processes, gain actionable insights from your data, or revolutionize your
Narrator: 00:27:12
business operations, AI50 is here to guide you on this transformative journey. Interested in learning more about how AI50 can empower your business with cutting edge AI solutions? Reach out to us. We're excited to explore how we can collaborate to turn your data into your most valuable asset. Now, don't forget to
Narrator: 00:27:32
stay connected with us. Follow AI50 on LinkedIn to get the latest updates, insights, and behind the scenes looks at our podcasts. Join our growing community where we share cutting edge ideas, discuss emerging trends, and network with industry experts and enthusiasts alike. Also, make sure to follow our esteemed host, Hanh Brown, on LinkedIn.
Narrator: 00:27:56
Hanh's insights and experience in the AI field are invaluable, and following him means you're always in the loop with the latest developments and thoughtful perspectives in the world of artificial intelligence. And if you haven't already, subscribe to AI50 Connect on your favorite podcast platform. By subscribing, you'll never miss
Narrator: 00:28:12
an episode, and you'll be part of our journey as we explore the fascinating world of AI together. Each episode promises to delve into new topics, featuring expert guests and providing you with actionable insights. Don't forget to also follow us on YouTube. We've got some exciting content lined up, including video versions of our podcasts, exclusive interviews, and much more.
Narrator: 00:28:38
It's a great way to visually engage with our content and join our expanding online community. Lastly, if you're considering integrating AI into your business to gain the numerous benefits we discussed today, We'll Reach out to us, whether it's about data driven decision making, obtaining real time insights, or enhancing your business efficiency through AI.
Narrator: 00:28:58
We're here to help guide you on this transformative journey. Thank you for tuning in to AI50 Connect. We're excited to continue this journey with you, exploring the ever evolving landscape of artificial intelligence. Remember, the future is data driven, and with AI, you're not just keeping up, you're leading the way. Until next time, keep innovating,
Narrator: 00:29:18
keep connecting, and stay ahead with AI50Connect. Goodbye for now.
Hanh: 00:00:03
Imagine AI as a super smart assistant that can quickly sort through mountains of data and find the gold nuggets of insight we need. This is about turning complexity into clarity. Once we've gathered this rich chat data, the next step is deciphering it. And that's where artificial intelligence comes in.
Hanh: 00:00:21
AI transforms this daunting task into an achievable one by swiftly analyzing vast amounts of data A feat that would be impossible for humans alone.
Narrator: 00:00:35
Hello, and a warm welcome to AI50, where we delve into the fascinating realm of artificial intelligence, or AI, and its profound impact on society, especially for our older generations. In each episode, our host, Hanh Brown, unravels the complexities of AI, making them accessible and relatable. Hanh's expertise lies in simplifying intricate AI concepts, shedding light on
Narrator: 00:01:01
how this technology is revolutionizing aspects of our daily lives, healthcare, and business industries. AI50 is more than a discussion on technology. It's a journey through the heart of AI innovation. We bring you in depth stories, uncover the latest advancements, and engage in rich dialogues with specialists.
Narrator: 00:01:22
Our conversations span the spectrum of AI, from its role in driving healthcare advancements, to its influence in reshaping business strategies, and its integration into everyday routines. Each episode offers a wealth of knowledge about AI. We go beyond the surface, exploring the ethical dimensions, the challenges, and the transformative potential of AI.
Narrator: 00:01:44
Our focus is on providing insights that show how AI can be a positive catalyst for change, particularly in enhancing the lives of older adults. Join us as we embark on this insightful expedition. We promise a mix of compelling narratives, expert perspectives, and real world applications. This approach is designed to deepen
Narrator: 00:02:03
your understanding of the dynamic and ever evolving world of AI. Hanh, let's dive into today's enriching conversation on AI.
Hanh: 00:02:15
Welcome to AI's transformative role in business insights in the baby boomer revolution, where we delve into the cutting edge impact of technology on business strategy, with a special focus on its significance for the baby boomer generation. I'm your host, Hanh Brown. In today's episode, we're embarking on a deep dive into how AI and chat data are
Hanh: 00:02:37
revolutionizing the business landscape. We'll explore how these innovative technologies are not just mere tools for innovation, but are indeed catalysts sparking a new era of entrepreneurial insight and opportunity, particularly resonant for experienced and savvy baby boomer entrepreneurs. Join me as we navigate the complexities of chat data in the transformative
Hanh: 00:03:04
power of AI driven analysis. Together, we'll uncover how these pivotal elements are revolutionizing customer behavior insights, personalization, and much more. Let's embark on this enlightening journey into the future of business insights. Imagine you're running a business, and each day, hundreds of conversations flow through your chat channels.
Hanh: 00:03:27
Each of these chats is a puzzle piece holding valuable clues about your customers needs, preferences, and experiences. As a baby boomer entrepreneur, understanding this data is like having a direct line into the minds of your customers. It's not just about what they are saying. but how they are saying it, the
Hanh: 00:03:44
words they use, the questions they ask, and the feedback they provide. However, the sheer volume of this data can be overwhelming. This is where AI steps in, which we will discuss in the next segment. But before we go there, let's appreciate the potential of chat data. It's a digital footprint of your customer's journey with your business.
Hanh: 00:04:09
For Baby Boomers, this is a shift from traditional customer understanding methods. It's about adapting to a new digital language, one where every emoji, every phrase, and every query can unlock new business opportunities and insights. You see, understanding chat with data is the first step in a moving towards a deeper, data driven
Hanh: 00:04:27
understanding of your customer base. It's about bridging the gap between traditional business wisdom and the digital dialogue of today. Now, let's take a fascinating turn into the world of AI driven data analysis. Imagine AI as a super smart assistant that can quickly sort through mountains of data and find the gold nuggets of insight we need.
Hanh: 00:04:54
This is about turning complexity into clarity. Once we've gathered this rich chat data, the next step is deciphering it, and that's where artificial intelligence comes in. AI transforms this daunting task into an achievable one by swiftly analyzing vast amounts of data. A feat that would be
Hanh: 00:05:11
impossible for humans alone. For baby boomer entrepreneurs, embracing AI in data analysis can be a game changer. It's like having a superpowered assistant that not only reads through every line of chat but understands patterns, nuances, and customer sentiments. AI algorithms are adept at identifying trends, flagging issues, and even predicting customer needs
Hanh: 00:05:35
before they're explicitly stated. But why is this important for our seasoned entrepreneurs? Imagine being able to predict a surge in demand for a product or identifying a common customer complaint before it turns into a major issue. AI driven analysis of chat data can provide these insights in near real time, allowing businesses to
Hanh: 00:05:56
be proactive rather than reactive. This approach democratizes data analysis. It's no longer just the domain of large corporations with extensive resources. AI tools are becoming increasingly accessible, enabling small and medium sized businesses often run by baby boomers to compete on a level playing field. AI driven data analysis is not just about processing information.
Hanh: 00:06:25
It's about extracting wisdom from words. It's a bridge connecting the invaluable experience of baby boomer entrepreneurs with the cutting edge technologies of today, empowering them to make informed data driven decisions in their business endeavors. Building on AI's power, we're now stepping into the intriguing territory of customer behavior insights.
Hanh: 00:06:47
Here it's like having a microscope that lets us zoom in on the real reasons behind what our customers do and want. It's about getting to the heart of customer needs. Through AI's lens, chat data becomes a map revealing the path of customer behavior. It's about understanding not just what your customers want, but why they want it. For baby boomer entrepreneurs, this
Hanh: 00:07:09
is akin to evolving their business intuition into a data driven science. AI does more than just read text. It interprets them. It picks up on subtleties in language that indicate a customer's preferences, hesitations, and even their level of satisfaction. This is invaluable for businesses seeking to deeply understand their clientele.
Hanh: 00:07:33
Imagine tailoring your services or products to address unspoken customer needs or resolving issues before they escalate into problems. This level of insight is transformative. Particularly for baby boomer entrepreneurs accustomed to more traditional forms of customer interaction. It's about enhancing that gut feeling with concrete data.
Hanh: 00:07:56
AI provides a window into the nuances of modern consumer behavior, allowing these entrepreneurs to stay ahead of the curve in a rapidly changing market. For instance, AI can analyze chat data to reveal that customers often inquire about a specific feature, guiding product development and marketing strategies. This is not just about responding to the market, it's about anticipating
Hanh: 00:08:19
its shift, a crucial advantage in today's competitive business landscape. Next, let's explore personalization of customer experience. In today's market, personalization is the key to customer loyalty and satisfaction. AI leverages chat data to create a customer experience that feels tailor made. For Baby Boomer entrepreneurs, this
Hanh: 00:08:45
means an opportunity to blend their rich experience with cutting edge technology to offer unparalleled customer service. AI can analyze individual customer interactions and preferences, enabling businesses to customize their approach. This could mean offering personalized product recommendations, custom tailored services, or even individualized communication styles.
Hanh: 00:09:11
For baby boomers, this is a powerful way to connect with customers on a deeper level, something they value highly, but it goes beyond just making sales. Personalization builds relationships. When customers feel understood and valued, they're more likely to return and become brand advocates. For baby boomer entrepreneurs, this is about adapting their traditional,
Hanh: 00:09:33
customer centric approach to the digital age, ensuring that each customer feels uniquely appreciated. Imagine a scenario where a customer mentions a specific need during a chat. AI can pick up on this and inform the business. Which can then reach out with a personalized solution. This level of attentiveness can transform
Hanh: 00:09:52
a one time buyer into a lifelong customer. It's a blend of the old and new, the timeless value of personal connection, powered by modern AI technology. Next, we dive into the dynamic world of real time response and engagement. In today's instant response culture, this is about being as quick and attentive as possible, ensuring every customer interaction is timely and meaningful.
Hanh: 00:10:26
In a digital era where every second counts, AI empowers businesses, including those led by baby boomer entrepreneurs to respond to customer inquiries and interactions instantaneously. This isn't just about speed, it's about fostering a connection. At the moment, it matters most. AI's ability to analyze chat data in real time means that businesses can engage
Hanh: 00:10:50
with customers right when their interest is peaked or their need is greatest. For a baby boomer entrepreneur, this represents a significant shift from traditional response methods. It's about being present in the digital conversation as it happens. Ensuring that no customer query goes unanswered or unacknowledged. Imagine a customer expressing confusion
Hanh: 00:11:10
over a product feature in a chat. AI can immediately flag this enabling a prompt response that guides and reassures the customer. This level of engagement can significantly enhance customer satisfaction and loyalty. It's about combining the wisdom and customer service ethos of baby boomer entrepreneurs with the efficiency and immediacy of AI technology.
Hanh: 00:11:38
This real time engagement also opens up opportunities for immediate feedback and adaptation. Businesses can quickly tweak their approach based on customer reactions, making their services more dynamic and responsive. For our seasoned entrepreneurs, this is a powerful tool in staying relevant and competitive in a fast paced market.
Hanh: 00:12:00
Shifting gears, we enter the nuanced landscape of sentiment analysis. Here AI becomes our emotional interpreter, decoding not just words, but the feelings behind them. It's about understanding the emotional pulse. of our customer interactions. This is where AI really showcases its prowess, turning chat data
Hanh: 00:12:26
into a barometer of customer emotions and satisfaction. For baby boomer entrepreneurs, this is a leap into understanding the emotional undercurrents of customer interactions. AI's sentiment analysis goes beyond the literal meaning of words. It interprets tone, detects nuances, engages the emotional context of customer chats.
Hanh: 00:12:47
This insight is invaluable for businesses aiming to understand and improve the customer experience. It's not just about what customers are saying, but how they feel about your brand and services. For example, if AI detects a trend of negative sentiment in customer feedback about a specific product, the business can quickly investigate
Hanh: 00:13:08
and address any underlying issues. This proactive approach to managing customer relations can be a game changer, especially for baby boomers who may be adapting to the nuances of online customer engagement. Sentiment analysis also helps in personalizing marketing and customer service strategies. By understanding the general mood
Hanh: 00:13:26
and preferences of your customer base, You can tailor your approach to resonate more effectively with them. It's about aligning your business strategy with the emotional pulse of your customers. A strategy that blends the intuition and experience of baby boomer entrepreneurs with the analytical power of AI. Now, let's go into the
Hanh: 00:13:48
visionary realm of predictive analytics for business strategy. This is where foresight meets data. We're not just reacting to today, but anticipating tomorrow. It's like having a crystal ball powered by AI, guiding us towards future opportunities. In the realm of AI and chat data, predictive analytics is like a
Hanh: 00:14:14
compass pointing towards future business opportunities and challenges. For baby boomer entrepreneurs, this is about taking their years of experience and augmenting it with insights drawn from AI's analysis of chat interactions. Predictive analytics uses AI to interpret patterns and trends from past customer conversations, projecting these into actionable future strategies.
Hanh: 00:14:37
Imagine being able to anticipate a market need or customer preference before it becomes mainstream. This foresight is invaluable for staying ahead in today's competitive business environment. For instance, AI might identify an emerging trend in customer questions or concerns, signaling an opportunity for product development
Hanh: 00:14:58
or a shift in service offerings. This can be particularly empowering for baby boomer entrepreneurs, bridging their deep industry knowledge with cutting edge AI capabilities, enabling them to make strategic decisions with confidence. Predictive analytics can identify potential risks or customer dissatisfaction early, allowing businesses to address these proactively.
Hanh: 00:15:20
It's not just about reacting to the market. It's about shaping it, a concept that resonates with the forward thinking mindset of our experienced entrepreneurs. As we embrace these advanced AI tools, it's crucial we also navigate the challenges and ethical considerations they bring. This is about balancing
Hanh: 00:15:42
cutting edge innovation with responsibility and integrity. We're treading new ground here. Setting standards for how AI should be used ethically in business. This is especially pertinent for baby boomer entrepreneurs who are adapting to a digital business environment where these concerns are at the forefront. The challenge lies in balancing
Hanh: 00:16:03
the immense benefits of AI driven chat data analysis with the responsibility of protecting customer privacy and maintaining trust. It involves adhering to data protection regulations. ensuring transparency in A. I. Operations and being vigilant against biases in A.
Hanh: 00:16:24
I. Algorithms for baby boomer entrepreneurs. This requires a commitment to ethical business practices, staying informed about evolving data privacy laws and fostering a culture of responsibility and integrity in the use of A. I. It's about ensuring that their business not only benefits from A.
Hanh: 00:16:43
I. Technology, But also champions responsible and ethical AI usage. Remember, navigating these challenges successfully can enhance a business's reputation, building trust and loyalty among customers. who are increasingly aware and concerned about their data privacy. It's an opportunity for baby boomer
Hanh: 00:17:00
entrepreneurs to lead by example, showing that technological advancement and ethical business practices can go hand in hand. As we look ahead, it's clear that the role of AI in extracting business insights from chat data is only going to grow more sophisticated and integral. This journey is just beginning. And the possibilities are expansive. Emerging trends suggest further
Hanh: 00:17:28
advancements in natural language processing and machine learning, enabling AI to understand and interpret human language with even greater nuance and accuracy. We're moving towards a future where AI can not only analyze text, but also understand context, emotion, and even cultural nuances. For businesses, including those led
Hanh: 00:17:50
by baby boomer entrepreneurs, this means increasingly personalized and predictive customer interactions. We're looking at a future where AI can anticipate customer needs and offer solutions before the customer even articulates them. The integration of AI with other emerging technologies, like augmented reality, blockchain, and the Internet of Things,
Hanh: 00:18:13
will open new avenues for customer engagement and business insights. This convergent technological landscape presents an exciting frontier for all entrepreneurs, especially baby boomers, to explore and innovate. As we stand at this juncture, the future of business insights with AI and chat data seems poised to redefine how we understand and interact with our customers.
Hanh: 00:18:39
It's a future that holds immense potential for businesses ready to embrace and adapt to these evolving technologies. As we wrap up today's episode, we've discussed the multifaceted world of AI and its profound impact on business insights, with a special focus on the baby boomer generation. We started by understanding the vast landscape of chat data, then to the
Hanh: 00:19:05
wonders of AI driven data analysis. And explore the depths of customer behavior insights and personalization. We also tackled the crucial aspects of real time response, sentiment analysis, and the predictive power of AI in shaping business strategies. We also discussed the challenges and ethical considerations that come with these advancements.
Hanh: 00:19:28
And finally, we glance into the future, anticipating the exciting trends on the horizon. For our Baby Boomer entrepreneurs, this episode has been a journey of discovery, showing how the wisdom of experience can meet the innovation of AI to create a dynamic, responsive, and ethical business environment. Thank you for joining me on AI's
Hanh: 00:19:49
transformative role in business insights and the baby boomer revolution. Until next time, keep embracing the changes and let's continue to innovate and inspire. This is Hanh Brown signing off.
Narrator: 00:20:07
And so we conclude another insightful episode of AI50 Connect. Your trusted source for insights into AI and data. Today's episode has hopefully expanded your understanding and piqued your interest in the transformative world of artificial intelligence, especially in its application to business and beyond. In the realm of AI,
Narrator: 00:20:28
we're not just observers. We're active participants. This technology is revolutionizing our approach to data, making it more intuitive, insightful, and impactful. Whether you're a tech enthusiast or a business leader, AI's ability to enhance data driven decision making, provide instant insights, and boost analytical efficiency is something
Narrator: 00:20:50
that can truly change the game. For those envisioning the integration of AI in your business strategy, Think about its potential to streamline operations, identify emerging trends, reduce errors, and foster a collaborative work environment. These benefits go beyond just improving your bottom line. They're about transforming
Narrator: 00:21:12
your business's core dynamics. At the heart of this podcast is AI50, your ally in navigating the AI landscape. Our passion lies in empowering businesses with AI and data driven strategies. We're committed to developing solutions that not only drive innovation and efficiency, but also align with your unique business goals. Curious about how AI50 can
Narrator: 00:21:34
revolutionize your business? We're just a conversation away. Reach out and let's explore how AI can turn your data into a strategic asset. Keep in touch with AI50 on LinkedIn for the latest news, insights, and a behind the scenes look at our podcast. Join a community that's leading the conversation on AI advancements and applications.
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Remember to follow Hanh Brown on LinkedIn. Stay connected with Hanh's valuable insights and stay at the forefront of AI developments and discussions. And don't forget to subscribe to AI50Connect on your favorite podcast platform. Stay tuned for more episodes where we dive into exciting AI topics, bringing expert voices and
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actionable insights to your ears. For more visual content, follow us on YouTube. We have an array of engaging content waiting for you from podcast episodes to exclusive interviews and much more. It's a fantastic way to engage with our content visually. Lastly, if you're considering leveraging AI in your business operations,
Narrator: 00:22:39
don't hesitate to contact us. We're here to assist you in harnessing AI for data driven decision making, gaining real time insights and enhancing your business efficiency. Thank you for listening to AI50 Connect. It's been a pleasure having you with us on this journey through the evolving world of artificial intelligence. Remember, in this data driven age,
Narrator: 00:22:58
with AI, you're not just following trends, you're setting them. Until our next episode, keep exploring, stay connected, and lead the way with AI50 Connect. See you next time.