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
From Cloud Pioneer to Pediatric Innovator: Timothy Chou Explores AI in Health
Transforming Pediatric Healthcare with AI: An Interview with Dr. Timothy Chou
In this episode of The Human Code podcast, host Don Finley interviews Dr. Timothy Chou, a pioneer in cloud computing and AI-driven healthcare. They discuss Dr. Chou's journey from his work at Oracle and Stanford to leading the Pediatric Moonshot initiative, which aims to revolutionize pediatric care globally through AI and real-time data. Dr. Chou shares his insights on the progression of AI from automation to real-time decision-making and the impact of moving applications to the data rather than vice versa. They explore the challenges and opportunities in addressing pediatric healthcare shortages, the potential of federated and distributed AI, and the vision of creating real-time, privacy-preserving AI applications for healthcare. The conversation delves into the practical applications and future potential of AI in detecting, diagnosing, and treating rare diseases, emphasizing the importance of early intervention and prevention in healthcare.
00:00 Introduction to The Human Code Podcast
00:49 Meet Dr. Timothy Chou: Pioneer in AI and Healthcare
01:18 The Pediatric Moonshot: Revolutionizing Pediatric Care
02:14 Timothy's Journey: From Stanford to Global Healthcare
03:33 Challenges and Innovations in AI-Driven Healthcare
06:46 The Vision for AI in Medicine
07:53 Addressing Pediatric Healthcare Shortages
13:07 The Future of Healthcare: Early Detection and Investment
16:44 The Role of AI in Mental Health and Drug Trials
32:01 Building a Distributed AI Laboratory
38:37 Final Thoughts and Wisdom from Dr. Timothy Chou
39:44 Closing Remarks and Sponsor Message
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.
Today we welcome Dr. Timothy Chou. A pioneer in cloud computing, AI driven healthcare, and business transformation. As the former president of Oracle's cloud computing business and a Stanford lecturer, Timothy has shaped the evolution of enterprise technology. Now he's leading the Pediatric Moonshot, a bold initiative to revolutionize global pediatric care by using AI and real time data to improve outcomes, lower costs, and reduce healthcare inequalities. In this episode, we dive into the progression of AI and organizations from automation to real time decision making. must move to the data, not the other way around, and how this shift is transforming healthcare. How AI can address pediatric healthcare shortages and improve global access to care. Timothy's vision is both daunting and doable. And today we're exploring how AI is shaping the future of medicine and decision making. Let's get started on the human code.
Don Finley:I am here with my new favorite friend, Timothy Chou. I got to say, we've had such a fun time on the pre show talk that I'm excited to hear what you have to say. You've got a lot of inspiration in you. and there's a lot of beautiful things that you've got going on in this world. So really appreciate having you here. And then again, I just got to ask you, what got you interested in the intersection of humanity and technology?
Timothy Chou:I think it happened. I started a class at Stanford, on cloud computing many years ago. And, I always do in my class, I do the first and last lecture and in between, I have guest lecturers who are all CEOs of public companies. in my last lecture, I end with one phrase and I say, to those who much is given, much is expected, not that I quote the Bible that often, but I wanted to get across to them. I mean, I'm sitting in front of 150 Stanford kids who, yes, much has been given. I mean, the fact that they're even there is much has been given and that they have a responsibility to do something with that is what I wanted to leave them with. And, so that's how I ended a lecture, like, I don't know, for 10, 15 years. One day I'm sitting there going, okay, what about you? and as you heard in our pre meeting, I had a very interesting student show up in class one year who had an MD, an MPH, an MBA. He's chief of pediatric cardiology at the Children's Hospital of Orange County. And Dr. Chang, Anthony, he kind of adopted me. And I learned things like, Oh, wow, they're still using CD ROMs. Are you kidding me? And then, and I know you've spent time in the world of AI. If we're going to build, you know, trustworthy AI applications and healthcare with particular focus in imaging, the only way we can do this is we have to be able to take large amounts of training data. So that's why right around the pandemic occurring, I'm sitting around thinking, Oh, watch Netflix all day or do something useful, maybe, remembering what I say to the students.
Don Finley:Yep.
Timothy Chou:so I grabbed a group of, we were talking about friends who are multi talented in engineering, marketing, et cetera. And we set ourselves a mission. And our mission is to reduce health care inequity. Lower cost, improve outcomes for children locally, rurally, and globally. How are we going to do that by creating real time privacy, preserving AI applications? Based on access to data in all 1 million healthcare machines in all 500 children's hospitals in the world. And I say to people, I call it my last great project. it's really a combination of people I know, technology I understand, and a mission which I think is not one you would take on if you wanted to be an entrepreneur that makes a lot of money in five years. But it's one that gives the answer to the question I ask the students too much. I have been given a lot. This is my answer to the question.
Don Finley:and I'm calculating the number of miracles that have to happen in order for your moonshot to go. And it's kind of high, Like,
Timothy Chou:Amen.
Don Finley:and like typical startup investing, you, you look for a startup that has maybe one miracle that needs to occur, Like if you have too many, you know, how difficult of a challenge is, but the vision that you offer is So endearing and everybody can see how tangibly the world would be better if that was the case that I imagine that you're attracting some very, significant minds to be a part of this mission as well. And so like, how has that journey been for you as far as, you know, sharing this with the world and you and Dr. Chang, building this pediatric moonshot?
Timothy Chou:Yeah, it is. I mean, you said it's daunting, but I also felt like it was doable. I mean, it's daunting, but it's doable.
Don Finley:Well, yeah,
Timothy Chou:Yeah. Mm hmm.
Don Finley:you have training and then you have inference. And so federated training was something that like TensorFlow has had in it for years. So like there is research that goes on on how to do this. technologically, like that is achievable. And then inference, you know, you can distribute that as well. but then there's the, the legal framework of, getting new technology into organizations that are still using CD ROMs.
Timothy Chou:Tell me about it.
Don Finley:Yeah. That's scary.
Timothy Chou:Well, you know, as you already alluded to, we took a step back and went, well, in order to accomplish the mission, Do we need to build a new rocket, which happened in the original moonshot? And as many of your listeners know, the current approach to building AI applications is really to centralize all the data, Suck it all into one giant, computing system, learn on it. Right. In the cloud, and we said that can't work in healthcare and life sciences. The data size are much larger. Ultrasounds are a terabyte. the security requirements, much stricter privacy law, much tougher Norwegian Norway saying we don't want Norwegian data leaving Norway. So we kind of came to the conclusion that in essence, rather than move the data to the application, why don't we move the application to the data? And so we have built a distributed AI cloud infrastructure for healthcare and life sciences, which literally puts the cloud server inside the building at Children's Hospital of Orange County, or inside the building of a clinic or inside the ambulance, because remember I said we wanted to build real time systems.
Don Finley:Yeah. Yeah.
Timothy Chou:I mean, I know there's a lot of reasons to do, you know, after the fact analytics, but that's kind of like why, I mean, just to give you a little statistic in the United States today, 60 percent of the rural counties have zero pediatric expertise, zero. There are only 3000 pediatric cardiologists in the United States. By the way, they live in Philadelphia. They live in Chicago. They live in San Francisco. You go to Salinas in California up to Willits in Northern California. There's nobody there. that's America. You go to India, there's 300 pediatric cardiologists. You go to Africa in Rwanda, there's one guy. So if you take a step back and you go, well, oh, okay, we're going to go build tons of medical schools everywhere and train everybody. I mean, the quote, American system. of medicine. How can this scale? There's no way it can scale. You can't in, you know, if I'm a fresh graduate from Stanford Medicine and Pediatric Cardiology. You want me to move to the middle of Montana? And earn 1. 98. I mean, why would I do that? And you just see that We could build I think some people because AI we try to put it in competition with are smartest people. We, we, that's how we want to think about it. It's going to be better than the world's best cardiologist or oncologist or whatever. And I'm kind of going, I don't think that's the point of the whole thing, What if we could build, I call them, red, green, yellow applications.
Don Finley:Okay.
Timothy Chou:Red. This kid needs to be medevaced out of here. Or this accident victim, right, has a traumatic brain injury, needs to go to the ER. Red. Green. Hey, everything's cool. Yellow. We need somebody else to take a look at this. If we could do that, we could put the brains, in essence, of the world's best oncologist, orthopedic surgeon, etc. Right into the rural community, into India, into Africa. Right. And so it's not, I always say to people, if your mom works for Google and you live in Palo Alto, yeah, what we're working on is kind of cool and interesting. But that's not the point of the whole thing. I really think that's why, AI in healthcare, both is necessary, but also is. We're capable of doing that.
Don Finley:Absolutely. And so basically, I think your first kind of iteration of this, or like what you're talking is like in the simplest level of the triage of basically saying like, Hey, what is going on here? What do we need to do? And how do we pair the AI with the team on site to basically know, Hey, here's the situation and here's how quickly we need to act.
Timothy Chou:Well, also, you know, if you look at it, I think ultimately all diseases are going to be classified as rare diseases. It's just, we don't know enough
Don Finley:That's it. Yeah.
Timothy Chou:do that yet. Right. Let me just give you a, an example. There's a condition called focal cortical dysplasia. which is actually a brain lesion. If this lesion is left untreated, a kid has epileptic seizures. So there's a kid in Florida who's had epileptic seizures two to three times a day. At night, he wakes up screaming for 12 years. I mean, think about that.
Don Finley:Ooh. Okay.
Timothy Chou:MRI imaged him early on, didn't see anything, started taking him down a treatment of drugs, some they could afford, some they couldn't afford. Ultimately, they were starting to talk about, let's go put in electrodes into his brain, They finally re MRI imaged him. They now believe that he has this condition and he's I actually have photos or images, MRI images that I could show you. I mean, you and I would look at it and go, What's the difference between A and B? No, I can't see it.
Don Finley:Yeah.
Timothy Chou:But, you know, if you can find it, you can actually surgically remove it. And if you surgically remove it, the kid's cured for life. Amazing, right? Okay, there's a good news and bad news story here, The good news is there's only 25, 000 cases of this a year in the U. S. Good news, right?
Don Finley:Okay.
Timothy Chou:Bad news, no one pediatric neuro oncologist ever sees enough of this to be able to recognize it.
Don Finley:Exactly. Yeah.
Timothy Chou:now, on the other hand, we all know over in the world of AI that, damn, if I could get all the MRI images of all the kids in the world, I could build a focal cortical dysplasia diagnostic all day and all night. and you can repeat, I think you could repeat thinking about the world this way. Over and over and over again. It's not, we will end up, like I said, I think all diseases will end up being rare diseases. It's just we don't know enough yet.
Don Finley:That is probably like, it's a very profound statement to say that like all diseases are rare diseases. And I think that is the path that we're going down. which gets me thinking about like, what does that world look like after that fact, how do you see your work impacting the healthcare space? what is the future state that you want to have, as far as the experience of people going through this?
Timothy Chou:Well I think, you know, there's better people to comment on the healthcare system, which I'll comment is totally broken. but I think We all have to get to, and this technology is part of it, is how do we invest earlier? Earlier meaning, you know, we all invest in the last 10 years of your life, we invest infinite amounts of money, which are in essence the end of productivity for that individual. We do not invest early, We're making a difference in a 10 year old kid's life. He has 80 years, 90 years of productivity in front of him. We say kids are our future. We don't spend that way at all, You want to go do a startup in pediatric health care? Are you crazy? Why would you ever do that? There's not enough market. I mean, we say kids are our future.
Don Finley:Yes.
Timothy Chou:So, we need to invest earlier from the standpoint of, we'll call it the population. But also, why are we not investing? Why do we wait until just using this kid? We're waiting for 12 years to figure out what's really going on here. That's how the whole system is built. We're built for the acute issue that happens, which either you're going to go take a drug for it, or get surgery for it, That's how the whole thing is built. Why are we not detecting issues way earlier in the cycle? The technology is capable of doing that and beginning to alter what is the other half of this, which is lifestyle there. There's a condition in kids. This is a kind of a, other type of story. kids that have cancer, good news. They are given, you know, chemotherapy, et cetera. Their cancer is cured
Don Finley:Okay.
Timothy Chou:news. There is a tendency that what ends up happening is it affects their heart. And so while they survive the cancer, they die of heart disease. Now, if you can detect this earlier, the beginning of this, there's all sorts of, I mean, back to diet, exercise, all these sorts of things that will prevent this from happening if you knew earlier in the cycle until, right? So, I'm just saying, I think the earlier we can know, the earlier we work on these problems, the lower the, fundamentally, the lower the cost of the system. Fundamentally, the better the outcomes in the system. And if we can use technology to do this, where, you know, I was at JPM yesterday. I was like, you know, the beauty, a lot of people work on medical devices and pharma, I said, the beauty of software is in essence, the cost to build it is zero and the cost to deliver it is zero. I said, the impact the software can have is huge. Because I don't have the cost of distribution. I mean, or my cost of distribution is very low. Right. And I think that's where hopefully, you know, maybe not in my lifetime, but hopefully we all get here where we can do that sort of thing. Focus earlier in the cycle.
Don Finley:There's so many things you touched on. I know we didn't touch on this earlier, but like, I'm a big mental health advocate. And so one of the things that I'm supporting is like the MAPS institution, who is like, They're running the trials for MDMA to treat PTSD and severe depression.
Timothy Chou:huh.
Don Finley:And so one of the challenges that they've come to in their phase three trials, which they just in the last few months got rejected by the FDA, two problems with MDMA. One is you can definitely tell when you've had it. So it's really hard to do a double blind, study with the patient. The second thing is that treatment is necessary to go along with the substance. And so, the FDA doesn't approve treatments, they approve drugs. And they can't approve a drug that requires a treatment that goes along with it. The efficacy of it has to stand alone. And so our entire system is, MAPS is showing basically, after I think like five years, they're showing an 85 percent effectiveness of the treatments of like a six month treatment protocol. And so like they're showing Less than 20 percent are going back to depression or like having signs of PTSD. And yet at the same time, our system that is in place is really supportive of, is it a drug or is it a medical device? And if it's a medical device, is it similar to something that is, you know, You know, old or if it's completely new, that's an entirely different process. But like we, we have patterns and systems that are set to basically treat symptoms instead of getting to that early upfront kind of approach. And I know that we talked about like triage of somebody who is, you know, has a trauma head wound, you know, they need to be medevacked out. How do you see the pediatric moonshot playing in that space of prevention or early kind of like lifestyle diagnostics?
Timothy Chou:if people are interested, we're actually tracking 140 different, deep learning imaging applications in adult and pediatric medicine. You will not be surprised, this is at appcommons. bevelcloud. io and I know you can edit into show notes.
Don Finley:Yeah.
Timothy Chou:You will not be surprised. They're just a handful. of work in pediatrics, And, let me just, you know, if the listener doesn't really realize this, pediatric cardiology and adult cardiology basically don't have much similarity. the phrase that's used in, in the world of pediatrics is, children are not little adults. an And this is the rationale is that the things that cause mortality and cause issues in kids, which are unresolved, they die. So the population of us old people who are smoking and drinking too much or whatever, the pathologies that we create are very different than what happens in children.
Don Finley:Ah, true, true.
Timothy Chou:Right. So number one, I think it's just let's go pay. In fact, I just spent time with the head of neonatology at Stanford. There's a condition in a premature baby where this is interesting. A chemical gets activated in a baby, normal babies gets activated, which in essence causes the lung to inflate and he used a great example. He says, when you blow up a balloon, The very first puff, you really have to force it to open up. That's exact because the baby's been right underwater. That exact mechanism has to happen when a baby's born. a premature baby, it doesn't happen in a lot of cases. But at this point, they actually know this and they have an artificial synthetic whatever drug that causes this to happen,
Don Finley:Ah, okay.
Timothy Chou:So, I mean, just, that's just another example of that never happens in adults.
Don Finley:I don't know, Timmy. You've never woken up and been like, oh, I gotta breathe
Timothy Chou:yeah, I gotta breathe now.
Don Finley:Gotta breathe now.
Timothy Chou:Yeah,
Don Finley:Gotta start my day breathing.
Timothy Chou:yeah. And I think the challenge in pediatrics is, I mean, good news. Most kids are healthy. I mean, that's the good news. So all of us, our perception is, Kids are healthy because, But the reality is there's a lot of, I'll touch on another one. I've spent time with the head of rare diseases at, UPMC. and in that usage of the word, rare disease is super rare. And so he's been doing a lot of work in genetics. And so he told me, he said, you know, a couple of years ago, he gets called into the adult department. There are three patients who are in intensive care. They cannot figure out what's going on. He goes in and genetic tests them and comes back with actually four diagnostics, which were pediatric rare diseases. Which had been undiscovered in the adult world.
Don Finley:Oh.
Timothy Chou:So the, you know, we, the greater we, right. We say, you know, children are our future. I mean, in a hundred ways, that's true. And so, I always say to people, if you're interested in what we're working on, we have tons of ways to get you involved. But the more important thing is let's put some attention on this. as a society. And by the way, not only healthcare, but education would fit into this category as well. You know, that's the seed corn. You know, one of the reasons I like teaching is you know, you if you can, I like to say I have the opportunity to shape young minds. it's a responsibility and a blessing at the same time, right?
Don Finley:I, look at it as kind of like, you know, you're, you're tending a garden, right? Like you want the flower to bloom in its own way, but at the same time, you're there to support that growth.
Timothy Chou:Yeah. And we're starting to work in over in oncology and adult oncology. What we're talking about transcends, I mean, all the work we're doing. I always say to people, our computers actually have no idea if they're in a children's hospital or a clinic or an adult, they don't know really. Um,
Don Finley:yeah. No!
Timothy Chou:cancer, one of the things that happens in, in more complex cancer cases is that they convene what is called a tumor board. So because cancer has this multifaceted side to it, like, well, I need a pathologist that looks at the slides. I need a radiologist that looks at, you know, the, the lung images. I need a radiation oncologist who knows how to irradiate that. I need a medical oncologist who knows all the, And the incredible number of drugs that are now being developed, which are, basically call it gene specific. Okay. At the big fancy institutions like Stanford over here, or you go to Dana Farber, they have all these experts and they literally, I mean, this is kind of fascinating. They literally glow into a room. It's like a meeting room with PowerPoint. And in a one hour period, or one or two hour period, they will give every patient five minutes, these complex patients.
Don Finley:Okay.
Timothy Chou:Prevent the case, et cetera, et cetera. And then have this conversation. You look at that. First of all, that only happens at the fancy places. You go get cancer in, you know, Western Montana or whatever. What, what tumor board,
Don Finley:Yeah.
Timothy Chou:But yeah, and I know you guys have been working in multi agent, the multi agent world, if you sit down and think about it, couldn't you build a multi agent tumor board Right? You have an expert in the image. You have an expert in the pathology. You have an expert in, and at this stage, we're also spending time over in the drug trial world. You look at it. I mean, there's so many different drugs coming out. How does a oncologist, even a general oncologist, in the middle of the country know, it's not their full time job, the whole range of what's available right now? You
Don Finley:And, that's, the thing. The amount of research that's getting released on a daily basis is more than you can read in a month. And so, and then to do the job that you're doing, there's no way for anybody in that profession to keep up with where they're at. Plus, if you have a tumor board, Any collection of humans kind of has like the dynamics of a human relationship. And so, you've seen the study or you've heard this, I think it was a study, about judges as far as if you get, if you have your sentencing, before lunch, you're, you're done. Right. But if you get it, if you're there after they eat, you're going to get a lighter sentence. Right. And I think that we'd, we'd see the same sort of results in any sort of dynamic when it comes to like an oncology or a tumor board. I love that name, by the way. So,
Timothy Chou:By the way, just to make a comment, tour boards are volunteer efforts. The docs do not get compensated for this. I mean, it's back to this fundamental, we have a broken system. I mean, just
Don Finley:I mean, that's, I mean, another example of, like, how broken the system is. Now, are there other countries that you see doing this, like, better? That we could, we could gain inspiration from?
Timothy Chou:well, just to make a point of it, I think we're all on the bleeding edge of what AI and healthcare, and when I use the term, I think a lot of people, the word software and the world AI are interchangeable. Software could do a lot of cool stuff. You know, I've been in the business for a lot of years. but if we're talking about deep learning, neural networks, et cetera, we're really still at day one, day two of this whole thing, right? Of which ChatGPT exposed us all to the potential of it. and that's, Really text data, imaging data where, you know, I don't know we're first minute or something. So I think to tell you there is work. we're tracking work and spending time with folks in the UK that are working in this area, folks in Germany that are working in this area. So there are other places, particularly when you talk about distributed learning. And, swarm learning, federated learning. There are other places and particularly, you know, Europe because of their, I'll call it more strict way of viewing data, They're much more aggressive about working on how do you build out distributed capabilities rather than centralizing it, at mother Google or whatever. So yeah, there are, I mean, but we're all early, very early. I mean, there's this unique combination of domain expertise in cardiology, orthopedics, or whatever, and. An understanding of being able to build a team. Like I said, we're tracking 140 of these where I've got some guy who knows what a convolutional neural network is. Right. and putting those two pieces together is non trivial. and, but I think, we're in the early days. I always tell people, I was kind of there at the, we'll call it the birth of cloud computing. really, I mean, even AWS is, what, 15 years old? Salesforce is 20 years old, rough 20 25 years old, but even with cloud computing, whether application or infrastructure, we're still nowhere. I mean, plenty of people are running on prem, traditional software models, plenty. I mean, you know, plenty of computers are being sold that are put in data centers. I mean, it's not like it's all quote game set match done. So when you look at where we are with AI, I'm kind of like. we're year one of a 15 year cycle. I mean, super early.
Don Finley:Oh, I absolutely agree with you. And I think we end up in situations where we go from distributed computing to centralized computing. And like we find like we go back and forth. and it's kind of like, even in the software world, we go waterfall to agile back and forth as well. The pendulum swings. We create new things and it's cool. And I think we're in that, their phase of artificial intelligence being centralized. But like people like you and, the work you're doing to decentralize this and showcase that it is possible to build private systems that can actually help you and support you. And I think that that's a really Awesome push for what you're doing. And like, we look at even on the social media side, right? Like centralized AI and social media has meant that we are now the product in which our emotional engagement is what the AI is gaining or trying to gain from us. But what I like to see is now let's have AI that is looking at like, what is your purpose? What is your goals? and then helping you to achieve those. And I think that, you know, what you're working on as well fits into that paradigm of giving more control and access to the people where they need it. if, you know, myself and the audience included had a magic wand to help you get the, to the next evolution of your pediatric moonshot, what could we provide to you?
Timothy Chou:I think there's multiple levels. at one level, it's really, and you're helping do this, is let's keep telling the story. I tell people it took 40, 000 people to get to the moon. We're a few shy of that. So, spreading the word, number one. number two, I think for those people who can engage, do engage. Meaning, you know, what does it mean to build a congenital heart disease? AI algorithm. I mean, if you're in the space of either the world of cardiology or the world of AI, go start looking at these problems. There's tons of, I said, we already have examples. I mean, let me say how specific this can get. There is a team at Duke working on AI analysis of weight bearing, low power CT imaging. of the ankle and foot. So normally, right, when you think about it, you go take an x ray of your foot, there's no load on it,
Don Finley:Okay. Okay.
Timothy Chou:it's, obviously, there's information when you can get, weight bearing. But obviously, if you go do that, you can't be subjecting it to a ton of Right, radiation. Hence, low power CT. So I'm just using that as an example of how specialized this can get. Low power CT, weight bearing ankle and foot,
Don Finley:Yeah.
Timothy Chou:That. I think, we're in the middle of building a Distributed AI laboratory for healthcare and life sciences. What do I mean by that? We are going to have 32 sites where all the imaging data is available in real time, CT, low power, CT, ultrasound, x ray. MRI, et cetera, all offline data available from the Paxes, which for the listener doesn't know is in essence, the repository that the radiologist uses to look at, the images and then all the EMR data available to authorized applications. And we are want to perfect the art and science. of taking research work, whether that's at University of London or in Germany or in Philadelphia, this small research team, and move it from, we like to say, from the research bench to the bedside by implementing it in a laboratory that sees 2, 000 terabytes of data a year. We'll have 3, 000 servers in it. Right. If we can figure this out, we now have a path to take brilliance in low power CT for ankle and foot, and now deploy it across all low power CT systems in the world, So we're in the middle of that. I've been funding all of our efforts to date. This next step is not going to be able to be done that way. So we are actively in conversations with a lot of people who, you know, I will say are interested in how distributed AI will work. And I'll just make a comment. If everything moves to, well, I just pick on mother Google. If everything moves to mother Google, well, they build their own chips. They don't buy servers from anybody. So there are a large constituency that is interested in how does a distributed world work and we're very eager to have conversations with anybody in that space whether that's from the tech front or the other major area we're spending time in is our new friends in biopharma. Where,
Don Finley:Bye bye.
Timothy Chou:yeah, this is why I said we're spending a lot of time in, you know, clinical trial work where today the ability to do very precise connection of the patients to the trial is done today. I'll call it haphazard manual. Do you know the right people is the general mechanism. So what we're right in the middle of building is a application. We call it total recall, which is connected. Remember, we have a distributed computer sitting inside the firewall so it can talk to the EMR. So now I can take it on. I'll pick on oncology. I can take an oncology patient who has a 3, 500 page PDF document as Her electronic medical record. I can rag train a local LLM and now I can ask questions like, well, you know, what's the difference between the last two CT scans or how many courses of cisplatin has the patient been given? What was the reaction? What we learned, we shared this with 12 oncology nurses around the country. I told the team, I said, if we had a buy now button, I'm pretty sure they would have hit it because we didn't realize how much manual labor they go through in essence with a little search bar, looking at a giant PDF document and it's like crazy, right? so we, we actually, the reason we called it total recall is. We demoed it to these oncology nurses, then we turned over the, the controls to them to let them ask whatever the hell they wanted to ask. So, at some point in time, one of them said, well, what is the prognosis for this patient? And you're going, this is where AI appears like magic, right? So it does all the other stuff, so it must be able to answer that. You're like, no, You humans can't even answer that question. Why are we asking the computer? So that's why we said, no, it's called total recall. It has perfect recall. of what has happened with the patient in the past, right? That's what it does. Perfect recall, right?
Don Finley:recall. That's it.
Timothy Chou:that's, what it does. Don't
Don Finley:it's
Timothy Chou:do
Don Finley:in the name. It doesn't, it's not pontificating on what is actually like going on. It's not connecting the dots, but it's just total recall. I love that.
Timothy Chou:Now remember, we now, the application now has complete profile information of the patient, Cause it, looking at the MR record. So what we have come to learn is that in phase 2, phase 3 drug trials, the real data about what those protocols are, are sitting inside protocol documents that can be 300 pages of PDF and they are sitting behind the firewall because the pharma company doesn't want to let everybody know what they're working on. Okay, if you have a distributed infrastructure, I park a server inside Roche, Bristol Myers, Squibb, whatever, LLM, RAG, the protocol document, and now multi agent, I can have the total recall agent talk to the protocol agent, and now the hit rate has got to skyrocket because you have now complete knowledge of the patient and complete knowledge of the protocol. And just to say it, This. is not that hard to do.
Don Finley:No, that's entirely you're, you're talking about things that we do in other areas, right? Like there are
Timothy Chou:bad.
Don Finley:of this. And in fact, we have rag solutions running in our own systems. We distributed for our clients, right? Like all that question and answer stuff is. is relatively, I mean, it's not a, a solve solve problem, but they are solvable. They require a little, it's like the early days of Oracle, right? Like, you know, it was a database company, but they were still like building and like rag solutions are context based. For the most part, you got to figure out how to get the information in, in a way that the machine can process it. But at the same time, like you're talking about stuff that is, you know, day one implementable, not. Two years, five years down the line. I love it. So Timothy, I gotta wrap this up. Is there any other like last bits of wisdom that you would like to share with the audience of like any life lessons as far as how to, how to live in this, you know, future AI world that we're talking about?
Timothy Chou:Well, it's something I, I said to you during the pre meeting. When I start out my Stanford class, I always say to the students, I go, you know, the quality of a student is not measured by what you know, but by the quality of the questions you ask. And maybe in a world of LLMs, it is even more true.
Don Finley:Yes.
Timothy Chou:It's the quality of the questions you ask. And I think the, the more we're able to be curious, the more we're able to ask the right questions, the faster this is all going to happen, right? And
Don Finley:I absolutely love it. Curiosity is one of the things that drives this world and Timothy, thank you so much for being on the show today. Like I really appreciate the time we've had together.
Timothy Chou:I have as well, Don, it's been a lot of fun.
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.
