The Human Code
The Human Code" podcast unravels the intricate blend of technology, leadership, and personal growth, featuring insights from visionary leaders and innovators shaping the future. Host Don Finley dives deep into the human stories behind technological advancements, inspiring listeners at the crossroads of humanity and tech.
The Human Code
Exploring AI's Potential with Suresh Madhuvarsu
The Intersection of AI and Humanity: A Conversation with Suresh Madhuvarsu
In this episode of 'The Human Code,' host Don Finley sits down with Suresh Madhuvarsu, a seasoned tech entrepreneur and AI visionary. With over two decades of experience and insights drawn from his upbringing in India, Suresh discusses leveraging AI to address human-centered challenges, particularly in healthcare and education. Emphasizing the role of empathy in technology adoption, Suresh elaborates on how AI can augment human capabilities and drive transformative change. The conversation also touches on the evolution of AI, the importance of aligning technology with real-world problems, and the future of tech-driven innovation.
00:00 Introduction to The Human Code
00:49 Meet Suresh Madhuvarsu: A Tech Visionary
02:23 Suresh's Early Life and Inspirations
06:26 The Symbiotic Relationship Between Humanity and Technology
09:26 AI's Evolution and Impact
13:56 Future of AI and Its Challenges
21:03 AI in Healthcare and Education
26:04 Preparing for an AI-Driven Future
28:54 Conclusion and Final Thoughts
Sponsored by FINdustries
Hosted by Don Finley
Welcome to The Human Code, the podcast where technology meets humanity, and the future is shaped by the leaders and innovators of today. I'm your host, Don Finley, inviting you on a journey through the fascinating world of tech, leadership, and personal growth. Here, we delve into the stories of visionary minds, Who are not only driving technological advancement, but also embodying the personal journeys and insights that inspire us all. Each episode, we explore the intersections where human ingenuity meets the cutting edge of technology, unpacking the experiences, challenges, and triumphs that define our era. So, whether you are a tech enthusiast, an inspiring entrepreneur, or simply curious about the human narratives behind the digital revolution, you're in the right place. Welcome to The Human Code. On today's episode, we're diving into the incredible journey of Suresh Madhuvarsu. four time founder and product visionary with over two decades of experience in the tech and AI industries, Suresh shares his unique perspective on leveraging AI to solve human centered problems, drawing from his background, growing up in India, where innovation thrive, despite limited resources. We'll explore his insights on the evolution of AI from its early roots to today's generative models and how it's poised to revolutionize industries like healthcare and education. Suresh also highlights the critical role of empathy in technology adoption, ensuring innovation truly serves the people they're designed for stay tuned. As we unpack the balance between humanity and technology and discover how Suresh envisions a future where AI not only augments our capabilities, but drives meaningful impacts across the globe. I'm here with Suresh Madhuvarsu and we are excited to talk today about the intersection of humanity and technology. Suresh and I have had a few minutes to get to know each other better before the show. and I'm really excited to have you on today, man. And first question, what got you interested in that intersection of humanity and technology?
Suresh Madhuvarsu:first of all, Don, thanks a lot for the opportunity and, I've seen the previous episodes that we've had and I always enjoy, I think, really talking through everyone's experience and, we all contribute to the humanity and the technology in one way or the other. And, thanks a lot for bringing both together. Really appreciate that. From my point of view. I grew up in Southern India, and as you can imagine, at that time it was a 1.2 billion, population. And, we used to compete, I used to compete as a kid with, millions of, kids. I'm talking about millions of kids, Every year, to get to the top of whatever you want to do. Whether it is about the undergrad, whether it is about the masters, and, whatever. and then, the kind of solutions that you would see in India, for example, all the way from cities, and then, we also have the tier one, tier two, towns, or the cities, what we call as, and then the villages. But as you can imagine, whether it is with respect to the healthcare, education, or even the agriculture, there are so many local innovations that people do and that I see growing up and then I will be like, Oh my goodness, this is such a local innovation that somebody did, but you would never see that in a different place. Why? because one, it's very subjective to the people, what the experiences that they're going through, what challenges that they're going through. They feel, Oh, you know what? I don't have the resources. But lack of resources shouldn't stop you from innovating. That's the mindset that people have, And, during the same time is when, especially for me, I got into the whole aspect of, The western influence of the science and the technology that is coming in. And what I mean by that is, we used to have these, televisions that came initially. Those are all black and white, televisions. And then we moved on to the color television. And then, we used to call the radios as the transistors. Because transistor is the Electric element that is there in the radio, it's funny when I really think about, probably 25, 30 years ago, but then that's what is really what we mean by the technology coming in, And then for the entire city, especially I'm talking about, this is my childhood, by the way, when I was in the middle school sort of age, 11, 12 years old, there used to be. Two computers for my entire neighborhood of thousands of families. That's it. Again, the reason why I'm giving you that perspective is when I looked into that kind of innovation that is coming up when there are no resources. And then on the other hand, there is so much of technology that exists, but cannot be commercialized because of whether we lack the Empathy to really look into the problems or the lack of resources to commercialize it, That's really what really brought me interested in. Hey, you know what? We have this set of challenges. They are not unique to us, but they are unique to the people, who are there living for decades and decades. And then we have these new technologies that are coming in. And the whole idea is, How can I better manage, better help all these innovations using tech, Because, end of the day, I feel really terrible if there is a technology and then people can't use or there is a technology and that is trying to look for a solution. But I always feel the other way around, which is we need to really empathize, look into the problems. the challenges that people are going through and then look for the right technology that can solve this problem. So that's really where, Don, to your, initial starting, question, I always feel let's not really think about Humans are different and the technology is different. but it has to be a combination of both. And that's the only way that I feel, especially in this generation and in the last probably even thousand years, I would say how we progressed all along.
Don Finley:I love the point that you're coming to because it is a symbiotic relationship that we have with technology. And I even go further back to say, the second that we lit our first fire, we were forever embedded with that kind of thought that hey, this is technology, this moves forward. You can't go back to that space. and so it's an exercise of raising consciousness. In this reality, this realm, but also the other point that I'd love to hit on is you talk about technology for the sake of technology really doesn't help. the technology needs to be helpful in solving a problem that a human has. And starting from that point, I think it's probably also, led to some of your success. as well, because that having that attitude of the application of technology in the right space for the right purpose can really help to drive better results for people.
Suresh Madhuvarsu:Absolutely. it's funny you touched upon, lighting the fire. And then, for me, one of the greatest example that I always, very humble upon is the invention of the wheel.
Don Finley:Yeah.
Suresh Madhuvarsu:again, of course, in 2024, we may not really feel a grade of accomplishment that somebody invented real, some time back, but I'm sure at that point of time for them, it's really Hey, you know what? I have this bunch of things every day I need to carry from place A to place B. And, my, people are dying because of the carry of this weight that I have to do every single day. I don't know. we don't know for sure, is it 10 hours, 15 hours a day that they were carrying this load? And now we need to find a better way to carry things. You and I probably cannot appreciate that enough because that's not a problem anymore, or that has become a fundamental, thing in our lives, but that's a problem for somebody out there, The reason why I bring up that topic is, There are so many challenges, Don, that we see in everyday life. That is a big challenge for the people who are going through that pain. But if you don't have the same pain, you're like, Hey, why do I care? And that's exactly the piece where I feel whether it is about, honestly, at a global level, whether it is about the education, health, or whatever technology that we bring, it has to be a, in the context of a particular problem that we are seeing. the only way I feel we bring in the technology, increase that option and really see how things work out that way. not the other way around. In a way, whereas, I just bring in something and then people are saying, Hey, you know what? Can you use this one? probably that doesn't really work out that way.
Don Finley:we've seen that, we've seen that in the technology space, I'm going to shoot myself in the foot with this example, but at the same time, like crypto and blockchain, there is value created, but I think the potential of that technology, the problems that it can solve is a lot greater than the use cases that we see today. And yet additionally, the hype that we saw during some of the cycles. was a bit overblown for the actual problems that it could be solving. And on that note though, knowing that you're also an expert in AI, what I'd love to ask you is, do you see AI as living up to the hype that it is? Or are we in one of those situations where like the excitement has overgrown the capability?
Suresh Madhuvarsu:The way I want to think about the AI now is, again, we go back to 30, 40 years of the Turing machines and, all that good stuff, Turing machines and later on, I'm sure, probably people who would have taken computer science would have gone through the Lisp programming and, the decision systems and, all that good stuff. I know, Don, you were chuckling and, That's one of those things where at that time we were like, Oh, you know what? yeah, I'm learning, the whole of the decision making process and whatnot. And then you come to the commercial applications. Is nothing,
Don Finley:Yeah.
Suresh Madhuvarsu:right? even in, for example, I don't want to be shamed after that, I did a bit of COBOL programming.
Don Finley:Oh, okay.
Suresh Madhuvarsu:yeah. and then the whole thing with the COBOL, for example, is really like a How you speak, it's really a very well written English language, I would say, but in the business sense, the reason why I'm bringing up the COBOL example is when you think about the COBOL or, or even in the latest of the years, the whole of the Java that we have seen and now the Python and, all the other language that we see, It's a lot to do with the conditional rule based systems that we still build to this day. All the commercial applications that we have are completely rule based systems. With the exception of course, some of the EI that we are seeing, again, I'm not really bringing the EI into the commercial system that we have now, but the place where I'm going with that is we have seen all that era where, yes, there are these vision systems. And then after that, for example, one of the beautifully done company I always think of is the Intuit. the QuickBooks and TurboTax kind of folks where they have taken a manual workflow and then they included very nice UI on the top of what a CPA would do and now I'm sure probably we all use it with less pain. it's less painful to file taxes. The reason why I'm bringing all this is yes. TurboTax is great. that kind of, progress is great, but we are still limited by. the computational capacity. We were still limited by how much of data that you can process in the memory for the instantaneous results. We were still, restricted by the amount of learning some systems can do at that point of time. And now the fast forward We have the cloud computing, which is great. we have the AI and ML systems, that is great. And now recently the whole of the Gen AI capacity that we have is really great. And I feel Gen AI is capable only because of the GPUs that we are seeing today. So it's a multi dimensional improvements that we've actually brought in at this point of time compared to 10 years, 20 years ago. For example, and that's really where I strongly feel this is not a hype cycle, but this is really the whole advancement the AI that we want to see. and I'm sure every single day, every single week, there are so many net new advancements that are coming, either with the foundational models or the LLMs and now the RANs. that we are seeing, and that's what really excites me more because now it's not really about one system is capable of, doing more things, but one system is intelligent, to do things that are combined of multi million number of people that we have in the entire US, for example. and then even the ability for some of the systems to go to the super intelligence, kind of more, yes, at some point of time, it feels super scary, but I feel super excited about how, some of these can really advance our own health systems, education, and in general, the entire infrastructure in general.
Don Finley:So given that our AI capability today is constrained by both the data that we're able to consume, And then also the compute. That we have available, And we're talking about gigawatt, data centers that are coming online to be able to handle this capability. OpenAI also released a paper that showed the compute scaling cost. And that with current transformers, in order for us to get like another 10x advancement, we need 100x cost that goes against that as well. And so the capabilities are exponential The cost is also exponential to where we're going with this. Do you see any constraints on what we could actually apply based on the actual cost of utilizing this technology?
Suresh Madhuvarsu:way I think about this is any tech in general, when I say any tech in general, even when initially we went from the whole of The on premise tech to cloud to mobile computing, If you remember initially when you think about the cloud software There will be naysayers. There'll be oh, you know what, it costs too much and then clearly, you know Sometimes it was really as simple as all these dell machines. They just kept it in one big server room and then that's the cloud but Where I'm going with that is, with the demand that we are seeing, I am very positive that the supply will also increase. That has to a natural function of whether it is about the Nvidia chips or Qualcomm or AD or T the tsmc, that we are seeing. The whole ecosystem now is actually gear up for the improved demand, and I feel with the supply increasing the processing capability will also increase, which means. to your earlier point on 100x increase in the cost, for example. Again, I'm not probably trying to say that they will come down to, let's say, 2x or 10x, but I feel they will drastically decrease over the next five years, just from the point of view that the supply will also increase proportionately,
Don Finley:Yeah,
Suresh Madhuvarsu:That's really my point of view. That's one. The second I feel is, especially from the Corporations, the local businesses, and the government's point of view. We still have to really understand what this AI can do for us, honestly. Because that's the only way we can price the AI properly. And that's the only way that we can see the economic outcome for using the AI. Because one of the biggest challenge, for example, again, Salesforce is actually a great example. they released the Einstein, Einstein didn't really do well. And then, this particular Dreamforce, they're all on agent tech, AI, for example, Again, that's a great thing, but the customers also have to decide, okay, I'm getting this AI. Is it giving me 10x productivity? Is it 4x productivity? And based on that, can I pay more or should I pay more? So I think it's a complete ecosystem, I feel where it is really about the compute infrastructure is at one level. And the second level is really about how much of productivity gains can somebody have using AI, are going to really determine the next five years of. The pricing adjustments that we see, and then the infrastructure, and then most importantly, the apps and the interfaces that we see today. I feel will not be the same in the next five years. what I mean by that is today, it's pretty much like a screen based. you go, you enter the data, from field one to field 10 or 100, based on whatever application that you are using. and. Unfortunately, that just messes up the entire situation, Let me give you an example. I have a family member who actually works with one of the state government agencies and she tells me it took two months of training for them to learn a system where they would do the DMV registrations. Two months. And in spite of that, they actually regularly go through on a quarterly basis, the user training, because there are some changes in the system. And again, the point for me is, yes, that's the state of the governments and the systems that we have today. now I can imagine with the AI, you don't have to do that anymore. It has to be a, Normal human interaction, it could be just a there is no screen, nothing. you are just talking to it.
Don Finley:you an example of this as well. We, one of the businesses that I'm involved with has an application process that goes along with it, So it is six pages that you go through and it's for, lending money, So you basically have borrower information, asset information, loan information across a number of things. Most of the information on the application can be gathered from other sources. And so the next iteration of the platform is an AI that actually knows the application and then can interact with the person to say, Hey, can you just give us the articles of incorporation? If you hand those to us or your last taxes, we'll be able to fill out 90 percent of this and then the AI can figure out what is the gap and then say, okay, I know that I can get this information from other documents or I can get it from other sources or I'll just ask and you can have that dialogue, but instead of a process that would take about, let's say 30 minutes. you can probably do this in less than five without even looking at a screen until the final presentation of what loans are available for you is presented.
Suresh Madhuvarsu:Absolutely. Again, Don, That's a great example where you already have the information somewhere. All that you have to do is extract that and then put in the right places. And for the additional information that you don't have, you just have to go to the public places, get the data and put it in, Again, it's not that hard. But then in the context of whatever we are doing, I think, that's really where I'm so opportunistic in the future on why people don't have to, for example, train on systems for months and months, or they don't have to struggle with, oh, you know what, this user interface, this design, philosophy, I don't like. No, you're just talking to a system And it just knows, interprets what you are saying, and then that's it.
Don Finley:Yeah.
Suresh Madhuvarsu:Probably there is not even a UI as top of that.
Don Finley:where do you see this impacting like the future of startups and entrepreneurism?
Suresh Madhuvarsu:for me there are two specific, industries that I'm really passionate about. Don, one of the things, again, my philosophy is super simple. We all, as humans, we need to have good healthcare. That's my philosophy. Really the basics of what we all go through and our ability to live impact each other in our whole family, in our community, in our country, whatever that is, is directly to how healthy somebody is. That's number one. two, once somebody is really healthy, they are good to do what they need to do. I always feel we all should have the basic good education. And that's really how, I really think about my mental model, how I need to impact and how I need to think about my life, really on what I do. So the reason why I'm saying that is, Those are the two places where I constantly think about how AI is impacting on multiple levels. For example, number one, when you think about the healthcare angle, number one, in the U. S. and elsewhere, there is a constraint on the number of physicians that we need to have and should have. I'm just using the physicians as a general sense, but think of, the surgeons and then the neuro and all the specializations and everything. That's number one, Number two, even if you have the good, professionals out there, the cost of innovating drugs, the pharma industry that they are spending, is just skyrocketing. And I feel EIE has an absolute chance to make 10x lesser costs in both the industries as we speak, here is how, I really think about, most of the times when you think about the radiology, radiologies are six figures. And there is a lot of, unfortunately, about 20 to 30 percent mistakes actually happen in radiology readings.
Don Finley:Wow.
Suresh Madhuvarsu:Yeah, on a yearly basis. And sometimes they actually also go on to more of suing the hospital systems, the individual practices and whatnot. And nobody likes that whole angle of
Don Finley:So are you saying
Suresh Madhuvarsu:But then when you
Don Finley:30 percent of readings from radiology are wrong?
Suresh Madhuvarsu:erroneous.
Don Finley:Wow.
Suresh Madhuvarsu:yeah. again, it's hard to believe. It's hard for us to comprehend that. But then, again, there are multiple things that happen over there, one part is to say, Hey, you know what? there is too much load on the radiologists is one part of it. They are burned out is the second part of it. and then sometimes people just don't either see the patterns. You have your x ray, you have your sonogram, you have your ECG, whatever that is at the end of the day, but you need to be able to read it in the right way. And then, think about even the specialization part of it. Somebody just coming out of, coming into the radiology and the reading has a very different pattern matching compared to a senior. who is out there, who has seen it all, for the last couple of decades, So now, when I think about, we talked about the intelligent systems, the AI capabilities that we see now. if you put in a 200 million records of the, X rays, sonograms, or whatever that is, and then we train the system, right now, actually, we're actually seeing in the last three years, by the way, Don, the number of FDA approved models have drastically improved.
Don Finley:Nice.
Suresh Madhuvarsu:from the efficiency point of view and the usage point of view, GE Medical, of course, is one of the top contenders who is really doing a great job in that. but my point really is when you really think about that efficiency, Think about the efficiency where, for a radiologist, the whole point is you upload the data. it goes into the, is reading it. Within five minutes, it comes back to you as a radiologist set of recommendations to say, Hey, you know what, this is what I see. And now as a radiologist, your job really is to say, do I agree with the UI recommendation? of the study or do have more and then you really use AI as your augmentation
Don Finley:Yes.
Suresh Madhuvarsu:at the point of time and then really provide better health care and faster health care to the patients that we have. Again, this is just one example that I'm talking about but there are by the
Don Finley:example of basically how AI both today and also in the future will be more of an augmentation of our experience. There will be some jobs that end up getting replaced, but at the same time, the jobs that we create and the jobs that we end up having are going to have some bit of interaction with an AI. so what I would love to wrap up the conversation on is, as people are looking at both their careers, their investments, their life in the state of now having intelligent solutions to be aiding us, what are the skill sets that they can be looking at to give themselves a better chance at succeeding in the world to come?
Suresh Madhuvarsu:that's a great one, by the way, there is something that I keep thinking about it. And, for most part, it is very controversial. That's for sure. I don't want to say it in any other way. the way I think about it is almost 20 years ago. When we think about most successful, whether it is about doctors, attorneys, and then the public servants that we see out here, and then the police department colleagues that we see, they all understood the power of computer programming. What I mean by that is they don't necessarily need to code. But they have a basic understanding of what a computer program can do their own proficiency, And I feel with the AI, it is very much similar, which is to say, You may not be an expert in creating a LLM or small language model or RAG or whatever, but you must the impact of AI in your own industry, number one, as it is today. And also be abridged with what it can do in the future to the job that you are doing today. I'll give you a simple example, by the way. Don, some of the podcasts that we are doing now, previously, it used to take about a human being for somebody, to really go through the entire podcast of one hour of discussion, almost about five, six hours. To actually get to the context and then have the right clips and then remove these kind of and all that stuff, and then bring out a 30 minute clip.
Don Finley:Yep.
Suresh Madhuvarsu:But now, fast forward, when we think about the ai, now you can, use whatever favorite, yay app that you have within five minutes. They're giving you 15, 20 clips that are 10 seconds to one minute, whatever that frequency is. And now you are like. Oh my goodness. Now you think about, a person who is doing that job of doing that social media, video editing and all that. Now, my point really is this, you don't need to really think about, oh my goodness, no, will I be replaced? But instead, you should be thinking about what tools can I use to make my life better? And that's going to be the common theme across any industry, any job that we take with the AI.
Don Finley:One, I got to say, I really appreciate you taking the time to talk to us today. But also continuing on this idea as far as the podcast goes, this is a podcast that we record roughly 30 to 40 minutes. In total, from the time that it takes us to get you booked on the show to publishing and promoting is five hours of effort because of all the AI tooling that we use in the process. And so I love that example. It hits home. We originally weren't going to be doing the podcast because I had an impression that it was just going to take too much effort for us. And When the team members sat down and showed, no, this is actually how it goes. you're absolutely right. the AI is saving us so much time. we edit by transcript now, Like we're not looking for where to make the cuts in anything. And if you really wanted like a bare bones pass, you can edit, you can do a first pass edit of a show in five minutes. And that used to take, I was talking to my friend does video production. She's like that used to take for every hour. It was two to three hours for that first pass. So absolutely insane. Suresh once again, it has been an absolute blast having you. I really appreciate you taking the time out of your day to talk to us in the audience and, looking forward to talking to you again.
Suresh Madhuvarsu:It's a pleasure, talking about my journey and then the whole of the impact of AI in the future. But that's something, I'm sure, what you do as well, we keep thinking about every single day that's going to impact our lives. And, I'm really excited about the possibilities and the positive impact that we all can make to this humanity using AI.
Don Finley:Absolutely. Thank you for tuning into The Human Code, sponsored by FINdustries, where we harness AI to elevate your business. By improving operational efficiency and accelerating growth, we turn opportunities into reality. Let FINdustries be your guide to AI mastery, making success inevitable. Explore how at FINdustries. co.
