Episode 26: 'THE CLOUD' with Dr. Timothy Chou

This week we are delighted to welcome technologist, entrepreneur, author and lecturer, Dr. Timothy Chou to the Podcast.  We are going to discuss the power of the Cloud and what it could mean for children’s healthcare and research. 

In his own words, Timothy has been lucky enough to have a career spanning academia, successful (and not so successful) start-ups and large corporations and he is also an author.

As President of Oracle’s original cloud business, Oracle On Demand, he grew the cloud business from it’s very beginning. Today he serves on the Board of Directors of Blackbaud and Teradata.  

Timothy started his career at one of the original Kleiner Perkins start-ups, Tandem Computers. Now as the Chairman of the Alchemist Accelerator he is focused on next generation enterprise software start-ups. 

Dr. Chou started teaching at Stanford University in 1982 and launched the university’s first class on cloud computing.  For those of you that listened Episode 25 of Podcast, this is where Timothy met his now good friend Dr Anthony Chang and where the shoots of an idea were formed to begin a project to connect all healthcare machines in all the children’s hospitals in the world, which like the consumer Internet, may completely change children’s healthcare on the planet.

Today we discuss this story and understand more about the opportunity that Timothy and his team and trying to uncover.

Visit our shop here to purchase a copy of the Thinking of Oscar Cookbook - Made with Love or Face Coverings. THANK YOU!

Thinking of Oscar website and contact details can be found here.

Follow us on Twitter here or Instagram here.

Theme Music - ‘Mountain’
–
copyright Lisa Fitzgibbon 2000
Written & performed by Lisa Fitzgibbon,
Violin Jane Griffiths

Podcast artwork thanks to The Podcast Design Experts

Transcript

Timothy: 0:00

We like to talk about technology for good. But a lot of what we do is make it easier to buy stuff and sell stuff. And I think this mission really is a mission where we can take our brains, our resources, our connections, and really make a material difference in children's health care.

David: 0:25

Welcome back to The not mini adults podcast pioneers for children's health care and wellbeing. My name is David Cole and together with my wife, Hannah, we are the co founders of UK children's charity Thinking of Oscar. This is Episode Two of the third season and we are delighted to welcome from Stanford University, Dr. Timothy Chu. Dr. Chu, in his own words has been lucky enough to have a career spanning academia, successful and not so successful startups and large corporations and also as an author. As president of Oracle's original cloud business Oracle on demand he grew the business from its very beginning. Today he serves on the board of directors for companies such as Blackboard and Teradata. Timothy started his career as one of the original Kleiner Perkins startups, tandem computers. Now as the chairman of the alchemists accelerator is focused on the next generation enterprise software startups. Finally, he started teaching at Stanford University in 1982, and launched the university's first class on cloud computing. For those of you that listened to our podcast last week, this is where he met his now great friend, Dr. Anthony Chang. And where the shoots have an idea were formed to begin a project to connect all healthcare machines in all children's hospitals in the world, which, like the consumer internet, may completely change children's health care on the planet. Today, we discuss this story and understand more about the opportunity that Timothy and his team are trying to uncover. We really hope you enjoyed this conversation. Timothy, Hi, thank you so much for joining us on the not mini adults podcast.

Timothy: 2:02

Thanks for inviting me, David.

David: 2:04

It's an absolute pleasure. I think the story that we're about to hear and the conversation that we've that we've gotten the topic is pretty different to what we've had previously. So we're pretty excited to share your vision, what you're doing and know the initiative that you're working on. And it's all going to be revolving around clouds, right. But I think to begin with, when Hannah and I were talking about this conversation, the question that came up was, how did you get into paediatrics? So can you talk a little bit about your kind of journey and know how you got into doing what you're doing?

Timothy: 2:36

Yeah. Be glad to. So my background, which is probably unlike a lot of your guest is all coming out of IT and tech. So I actually came to Silicon Valley in the early 80s. To work for one of the first Kleiner Perkins startups, called tandem computers, fundamentally have never left the area, ended up being the president, the first president of Oracle's cloud business. Actually, when I left there, I ended up starting the first class on cloud computing at Stanford. And that is actually the origin of how I came to be involved or to understand paediatric health care. My class and this is a pre COVID conversation. So has about 100 people in it. About 90 of them are local and about 10 are remote. So one of the remote students reaches out and says, I'm a little old school. I like to meet the professor. I went, Okay, cool. So we arranged to have breakfast at Johnny's cafe on California Avenue. And I'm sitting there and this guy walks in, I'm looking at him going, he doesn't look like a regular student, right? sits down, come to learn. He has an MD and MPH, an MBA, and he's chief of paediatric cardiology at Children's Hospital, Orange County. And so I'm looking at him going well, why are you talking to me? like what can I help you with? So he said, Well, actually, I think AI, Big Data, Cloud computing and medicine should meet. And so I've come back to Stanford to earn a master's degree in bioinformatics. I love telling this part of the story it takes Anthony three and a half years to finish a two year programme because number one, he has no idea how to code. Number two, he still has a real job as chief of paediatric cardiology. And number three, he has decided that in his 50's, to adopt an 18 month old and a six month old as a bachelor, I love telling Anthony story because like it's never too late for any of us. Right. So Anthony is really my introduction into the world of paediatric medicine. And the more I got into it, the more I was like, boy, we can help, we meaning us in tech. We like to talk about technology for good, but a lot of what we do is make it easier to buy stuff and sell stuff. And I think this mission really is a mission where we can take our brains, our resources, our connections, and really make a material difference in Children's Healthcare.

David: 5:13

So for those that haven't listened to our previous episode of the podcast, you're talking about Anthony Chang, who, who we had on our previous episode. He's, as you said, everything that you described, but also now a data scientist, as a result of is working with you and taking your course. And, you know, we talked a lot about AI and the opportunities there and, and I really wanted to once we had been introduced, really kind of bring that in and kind of continue the story and continue that. Yeah, or just just the story of what you know, what we began with Anthony, and how you've moved it forward. And I guess there's a bit of kindred spirits here. Because, you know, Hannah and I have been in technology, all of our careers as well. And we strongly see the opportunity for, you know, new technologies and bringing new initiatives and innovation into paediatrics. And that's exactly what we're trying to do from a charity perspective is bringing the future of healthcare to children. So continuing your story you've touched on and we're going to talk about clouds, but you've started an initiative with Antony's support, looking at building a paediatric cloud. But before we go into that, I think just for potentially some of our listeners, maybe you could just give us a quick overview of what cloud computing or what cloud is, you know, in terms of technology, and how that could ever be relevant to healthcare.

Hannah: 6:27

And I'm so sorry, because I am going to chip in and make it a double pronged question, because it was really interesting to have the answer to David's question of cloud, but also, why cloud? Why did you start there, you had the meeting of minds with yourself and Anthony, but then there was many areas that the two of you could have hit on together to address?

Timothy: 6:46

Yeah, so maybe I'll kind of go down how we ended up thinking about cloud being an answer to the question. And let's start with the question. And then obviously, per David's comment, I'll try to give a brief tutorial on what cloud computing is. So what I started to learn by virtue of being involved with the community, was just how I'll call it primitive things are, so today, in fact, this happened just last year, a kid went undiagnosed with brain cancer for over a month in Southern California, because it was too difficult to move an MRI image through two hospitals and one clinic. And I think a lot of people in the world in the paediatric world know this. They're still using CD ROMs, which like, when's the last time you saw one of those. And of course, the CD ROM has a little sticky note on it with the password. So guess how much security that is? So we learned that I learned that story. There's a story that Anthony tells, a little kid in Myanmar, who he's providing consulting for, and she's on the operating room table, they want to share the echo with him in real time. They can't do it. The kid dies on the operating room table. Later on, he gets to see the echo says, Oh, I could have told him exactly what was going on. And then you start looking at this globally, one of my old friends is actually the CEO or the former CEO of Save the Children. And I was describing what we were looking at, she says, Well, you know, pneumonia is the number one killer of kids in Africa. And it's not because there's not low cost scanner technology. There's nobody to read the scan. And in fact, about a month ago, I'm spending time with leading paediatrician in Rwanda. And I come to discover there is a single one paediatric cardiologist in the entire country, which then leads obviously in the overlap with Anthony and AI, like, well shoot, what if we could take the best brains from Stanford, children's Texas children, whatever, and put it in a computer, so that you could actually be able to diagnose pneumonia or COVID, or whatever number of circumstances, when you look at all of that, and say, Well, what is the root cause of everything from you're still using MRI scan, you know, CD ROMs, etc. And oh, AI is still difficult, because and everybody that's in the world of AI knows this already to be true, and particularly AI in medicine is there's not enough data to drive these deep learning networks. And if you don't have enough data, you're never going to get very accurate algorithms at all. So you look across this. You go well, what's the big issue? The big issue is that there's not data. I mean, there's 1000s of CT scanners out there, right. Hundreds of ultrasounds, Gene sequencers but nothing is connected, fundamentally. And so, I like to say in our world, we cracked through the connection problem back in 1994. We connected a million computing machines, and that was the beginning of the consumer internet. And that's the beginning of eBay and Netscape. And, and we all know now at this stage, how much that's completely transformed our consumer lives. And also, by this point in time, I had started to understand, there are about 2000 healthcare machines in every Children's Hospital in the world. And there are about 500 children's hospitals, which turns out, that's about a million healthcare machines. So a year ago, we launched this project to connect all million healthcare machines and all the children's hospitals in the world, and create a digital infrastructure that could transform children's health care. That's the problem, the challenge we saw, kind of our our thinking about it obviously, is on a planet wide basis, which leads to Okay, sounds like a great vision, how the hell are you going to do this? So if you look at it go, Well, if I'm a gene sequencer, a blood analyzer, whatever, and I want to get to that data, I need a computer, we're going to call it an edge server to talk to that machine. I'm also going to need a computer to talk out, for instance, real time stream and echo as an example. So that computer we call an edge server. And so what we are building or what we have built is an edge cloud. Okay, why do I call it an edge cloud? So I'll get to David's question. So if you took my class, the very first day, I tried to explain cloud computing, particularly what I call compute and storage, cloud computing. And if you speak, Amazon speak, I'm talking about what they call a EC2 and S3. So what does Amazon do? Right? Well, Amazon says, I'm going to go buy a million servers, a million computers, I'm going to manage the performance, availability and security of those computers, I'm going to deliver him in an op x model, you don't have to purchase up front, you can pay me every month. And I'm going to put those computers in 10 data centres in the world. And what I've just also explained to you as well, that's Microsoft Azure, or whether that's Google Cloud, etc, that abstraction applies across the board. Okay, so that is cloud computing, I am delivering compute and storage as a service by managing those servers, and changing the business model to saying yes, you can buy it, frankly, by the hour by the day by the month, what are we doing? So our edge cloud is in many ways the same thing. So we're going well, we're going to buy a million computers, we're going to manage the performance, availability and security of those computers, we're going to deliver them an op x model, the only thing different is we're going to put them in a million data centres, meaning right next to connected to the ultrasound, the gene sequencer, the blood analyzer, etc. And the second thing we're going to do differently is we're going to fill them with data. So we're going to fill them both with what we call machine data. So that could be things like, what's the serial number of the machine? Where's it located? What's the laser power level on the gene sequencer, and the other kind of data as we call it, gnomic data, so that's the data the machine would generate. So a blood analysis a genome sequence, an echocardiogram. And based on that allow applications, what we call edge applications, to be able to do any number of different things with that data, with permissions, obviously. So it could be things which are, I'm going to take that data, and I'm going to stream it to a secure cell service that looks like an Instagram, we're actually working with a company called Figure One is that to aggregate it in a centre cloud to do centre cloud, what we're gonna call centre cloud learning, or is that and we're just in the middle of this is it to use it to develop federated learning applications, all of these become possible as to what edge applications do. And therefore we're only limited by people's imagination of what becomes possible in all this.

David: 14:32

So I'm going to try and slightly simplify what I think you've just said just for probably from my own benefit, but certainly for maybe some of our listeners, but essentially your aim is to take paediatric data which if you took it from one source or one hospital wouldn't really be enough to actually do anything useful with potentially. Amalgamate that together so that anyone anywhere can take advantage of that data. In order to try and solve some of the, you know, the world's biggest, biggest problems in child health by putting it up onto a central system, which which people can gain access to.

Timothy: 15:11

we will enable just to be clear, we will enable that what you just said, which is aggregation in a centre cloud, we will also enable that it never has to be aggregated. This is an interesting thing. So I said the number 2000. So, if you look, and we just ran an experiment at Lucile Packard, so if you imagine Lucile Packard a building, which now has 2000 servers in it, right, that all have an interesting amount of resource memory, GPU, CPU, all that good stuff. And now connected with a high performance private 5g network, you could imagine that what I just said as I just move the cloud down into Lucile Packard's building, and now all the computing that you want to do, from even from a learning perspective, could actually all occur locally. I mean, this really stretches I think, where we are in technology. But that is entirely possible, just to make a point of it. It doesn't have to be just about learning. This could be as simple as the example I gave you, which is, there's a kid in Myanmar, I want to share the echo image with Anthony in Orange County, that's all I want to do. This infrastructure makes that easy to do. So it can be from the very, let's call it far reaching almost science fiction, down to something very simple. I just want to share a movie, like I share with my friends on Instagram. Does that makes sense?

David: 16:43

Yeah, absolutely. I think the vision is incredible. I guess the next question is, you know, people that know this kind of computing, will some of the questions will be security, that's a fundamental thing that people will be asking about. So let's maybe go there first. So de identified data security or this element? How are you going to kind of provide that and how you're going to manage that?

Timothy: 17:06

Yeah. So maybe, obviously, when we launched this, we knew security and privacy was had to be designed in from the beginning, we weren't going to kind of try to add it at the end. So from an engineering perspective, we started there, we've actually engineered 28 different security features, and compare them to what is being done at AWS, and actually, we're doing more. Part of that has to do with the fact that we've got problems that are more difficult to solve. So in their world, it's kind of difficult to walk in the computer room and walk away with a server in our world, you could actually walk away with a server. So we have to engineer a bunch more protection mechanisms. The other part is privacy. Kind of fortunate. One of my former students is a privacy lawyer with 12 years of experience in privacy law, particularly the GDPR. So everything we've done from a privacy point of view has been architected from day one to be around GDPR, because we knew we wanted to go global. And we see it as a superset of what HIPA compliance is in the US. So security and privacy have been a day one objective. We think we built a world class system here. And as we've been going out and talking to the various hospitals as we deploy, we're inviting them to go, Hey, if we missed something, we want to know about it. Because this is not something we're trying to shy away from. We think it's an important bedrock issue. And we want to bring the best of technology to it.

Hannah: 18:39

While I'm having that side of the capability nailed then gives you the opportunity to go global, as you just referred to, as you were talking in the conversation so far, there's a topic that's come up time and time again, in conversations we've had on the not mini adults podcast, and that's been one of equality. So you talked about, first of all you talked about, in my words, it would be accelerating, or reducing the time it takes to diagnose an unwell child. And that's been at the core of our ambition for our small charity. That was one of our first stepping stones that we were interested in, because we could see the promise that technology had. But then what I've learned subsequently has been more around what big problem would you love to resolve in healthcare time and time again, we've heard just that there are many complex, interrelated factors that lead to a very unequal provision of health. And so an example of a first world country versus a third world country is and is an obvious one. But to what extent were you driven by this sort of global agenda of getting a higher level of health care to children, regardless of where they were living? Was it more about speed or diagnosis? Do you care more about the global agenda? What how did those factors interrelate? And what's your thoughts on that? equality or more quickly inequality?

Timothy: 20:03

Yeah, and you know, we're all are seeing inequality in spades right with COVID. So, no, I, I think it's because back to what can we as technologists do, that can materially impact the world has been the agenda? And I told you when am I, one of my old friends is CEO of save the children talked about pneumonia? You don't really have to. I mean, by the way, in my opinion, you don't have to go as far away as Africa to see inequality. I mean, rural California versus Metro California level of health care is not the same. And why is it not the same? Well, it's because it's a manual system, based on silos of humans and data. So if I've got the best and brightest in Palo Alto, well, I'm lucky, right? I live here. You know, you live in you know, in Northern California, the in Ukiah, whatever, you're not going to see that you don't have access to that. And I think we know that technology can even access to information, we see it all the time. That is the consumer internet. I mean, that's the other thing that I think a lot of times, because of where healthcare has come from, people have thought about medical devices, and pharma and drugs and all that sort of stuff, which all have enormous manufacturing costs and cost to deliver. Because we all live in the world of software, I'm going software, the cost of manufacture is zero, it's your brain power, cost to distribute is zero. So if we can enable a platform and infrastructure, which allows the best and brightest to use their brains to create diagnostics, recommendation, any number of different things, we know the cost to build is zero, we need to know the cost to deliver is zero, we could now change children's health care. I don't care whether you want to talk about rural California, rural England, or Africa, we have the capability. It's all sitting here in front of us. So why don't we do it?

Hannah: 22:06

Given that the usual and oftentimes an obstacle might be cost? And that's not the issue here. What obstacles do you see in front of you? And what other help might you need?

Timothy: 22:17

Well, you know, I think the obstacles are not technological. The obstacles are both the obstacles of change of anything, right. And as all of us who worked in, in IT know, right, transformation, digital transformation is not a trivial thing. I don't care what industry you're in healthcare doesn't make it any easier. Let's say it that way. Right. So the obstacles of change, which have social things in it, you know, organisational, etc, are all you know, and obviously, there are challenges around security and privacy. But I have to tell you, I feel like all of that we have the technology to address, I think what we need is what we all need. When you do digital transformation, you need the champions, right. You need those early adopters to go"Yeah, I see your vision. And I'm gonna rally my troops over to here". Anthony is the Pied Piper have this, by the way, just to say it. I mean, he's out there way in front of most of them, talking about artificial intelligence and what it could do in medicine. But he's an outlier. I mean he's a real outlier. And I think that is really our biggest obstacle. And just to be nice to the medical clinical community, I tell my world, you know, our world, I go, you know, if I'm a clinician, I live in the here and now I have to live in the here and now. And now this is all I have, I can't live a year from now or five years from now, it makes no sense. And yet, what we all live in and what we're used to, and what we talk about, is we talk about where things could be. And I think that disconnect between how people think, right is is there now we're not you know, we are finding and, you know, between Anthony and many other people at a lot of these children's hospitals, there are the early adopters, the Vanguard's the people who are going, Yeah, we really need to start doing this differently. And I think our challenge is how do we rally those troops, bring them together? galvanise this mission? Whenever we meet with people, I always invite them to be part of our mission. I don't see it as an us them question. Yes, we're developing technology, etc. But it's an all of us thing. And I think that if we get the right people, galvanise them, right, motivate, help them right, we'll get here, the technology part, I'll just keep repeating. This is not gonna be that hard. It's the next step which will be hard.

Hannah: 25:00

Well, and the disconnect piece is interesting. Because I imagine you're thinking about your how you make it easier to get from where we are today to the future. So you're showing people the way perhaps.

Timothy: 25:14

Both showing and helping, I think the beauty of the software business is we don't go back to it doesn't cost anything. So every step of the way, if we can build it, I was just talking to a system integrator yesterday, who wants to be a part of this. And I said, I have to tell, you know, when I go talk to people in financial services, I can kind of say, Well, let me you want to imagine the future, this is what it could look like, I guess they usually can do that, because they've been living in the world of software for a long time now, because there is no physical meaning to the world they live in. But in medicine, that's totally not the case. And I said, I think it's impinnchent to begin to show them this, so that they can begin to grasp what it is, and not leave it on a PowerPoint slide or, a speech or whatever. And I think by doing that, and you know, again, the world of software, we can iterate at the speed of thought, I mean, you want to build it new again, tomorrow, no problem, we can do that, right? And get that and bring people along and show them the power of doing this. I do believe they all realise that things got to change. It's just how does that change happen? Where does it happen? who leads that change? I think those are going to be the central questions. And I think that's the work, you guys are doing great. I mean, we need more people to want to change this thing. And then to see how change can happen. And I think in that I've already seen this, I do have the privilege of teaching at Stanford. So I'm on all the faculty distribution lists. So this, this quarter, there are three AI classes being taught. And so I thought, just for the fun of it, I'm just going to post into one of them. Because they were all going well, we need projects we need projects to work on. So I just posted in one of them, basically not much information. I just said, How about a project to do AI in paediatric medicine? You know, within 36 hours, I had three teams of three people reach out, what can we do? What problems should we work on? How can we help? You know, I think the will is there in the community in the larger community. And I think by building a platform, a way to begin to do something about this, then we can actualize that we can take, you know, smart kids who want to work on ,who are maybe brilliant in federated learning, and marrying them up with clinicians who have the vision to say, this is what we could do with it. And they I mean, I'll just give her real credit that we've been working with a doctor at Children's of Atlanta, Rito , I talked to her and I said, Well, hey Rito what would if we had all the data in the world? And she said, paediatric cardiology paediatric echo expert and I said if we had all the data in the world what would you solve? So she goes 1,2,3,4,5 .Okay, so. So now I'm looking at 1,2,3,4,5 going, you know, some of these words like a and and the ,I understand. But most of these words like, what does this mean? So I invited her we have a team meeting every Monday and Thursday at two o'clock. So I said, Hey, Rito will you come and do a, I called it a micro MD degree? I said, you know, words, like, what is cardiomyopathy mean? And she came, I was so impressed, she built a presentation, just for us, it was like, let me explain this to you. Let me explain why you could understand it, what the challenges are, and tons of videos so that we could go Oh, I see what she means by that. And so I think that's the other half of this problem, which is, you know, we need to bring the, you know, ML federated learning, you know, AI people, and we all know how to talk tech head, but we also need to find a way to learn to talk to them. And some of that, I think, is they need to educate us a little bit on what's the vocabulary that we can start to use. And I think in that merger of talent of the domain, expertise of a Rito and they, you know, federated learning expertise is coming out of Stanford or, I mean, a lot of this work actually is occurring at Oxford, by the way, right. And we bring these communities together on top of a platform that lets them build it, you know, we're not that far away.

David: 29:56

We're doing a lot of you know, given that we're hopefully people are listening Listen to this, but we're doing a lot of nodding along with everything that you're saying. And I think, you know, that's that's probably not evident if you're listening. So in total agreement, but one of the things that really stood out for me, what you just said is, if you actually raise the problem, and you start to, you know, just put it out there, what can you do to help us in paediatrics, people want to do things they want to help? You know, it's a it's an evocative subject. But I think then, as with anything you've got, you know, as soon as it kind of goes out of the mind's eye, then you get back to normal and people just kind of carry on. So it's a case of continuing to have it in in the mind's eye. I guess the next question is, is the how, how are you going to, you know, what do you need to do in order to move this forward? And you've already touched on a little bit, but you've, you've got your first implementation you're working at, funnily enough, Stanford children's, but can you just talk us to a little bit about what you've done already? And then you know, what you're hoping to do in the future? And, and you've got a, you've got a kind of vision of a domino effect, I guess,

Timothy: 31:00

you know, our team is all people that come out of enterprise software. So we kind of think in terms of well, how do you get to the customer? And how do you grow the business, so we're not academics. So we, we established a beachhead, fairly, obviously, at Stanford, which, by the way, it wasn't even with all the connection networks, and everything, still was not the simplest thing in the world. So we understand the challenges of their organisational structures, and kind of the established ways of thinking about things, even at a leading institution like Stanford, right, so. So that's great, we learned a lot, we went in, just to tell the story, we went and installed the edge server, it took two and a half hours to do the installation, which acts on the one hand, and it's not so bad, because we actually have never seen an ultrasound, we had no way to test until we showed up in the in the building. But the flip side is two and a half hours, you're going to deploy a million of these that we just can't do that. So we've already done an iteration of the software and actually rereleased it onto the edge server at Stanford, which we believe could take this provisioning time down to like 20 minutes. So we're improving all along the way.

David: 32:16

So just quickly, what's an edge server for those that might not know what is it you know?

Timothy: 32:22

So the the edge server, the edge server is a computer about the size of your hand, we're actually looking at some that are two inches by two inches, but the ones we're working with right now, by the size, your hand, which connect to in the case of Stanford connect to the Philips epic seven ultrasound, so that every ultrasound that is done that is shipped to the PAC System is shipped to the edge server. And then the edge server has two applications running on it. One which looks at the gnomic data, the question you asked earlier David, identifies that at the edge, and then actually, for demonstration purposes, puts it into a box account, because there's a nice daikon viewer sitting there. The other application is with a third party ISV named Unitsa, which has been managing smart devices and for people like apple and carvanha, and whatnot. So I've known the founders for a long time, we said, well, we could bring all that technology to managing healthcare machines, the maintenance of health care machines, utilisation of health care machines, etc. So that's the second application runs on it, which communicates with them that's the which actually is an application that runs at AWS. So that edge server is that device, which those applications run on, which communicates with the external world. And with the Philips, in this case, the Philips ultrasound. So we completed that it passed all the tests. Actually, right now, specifically, we're still working. There's an integration, which we built to get the syslog data off the Philips machine, which is all about machine data, and that we're going through testing right now. So the next big step is we said, You know, I think we know how to scale inside the building. How do we scale across institutions. And so the next big thing as we've called this, the vanguard project, this is eight hospitals, seven more. One of them is obviously Stanford, seven hospitals, where we in essence, want to replicate what happened at Stanford, to ensure that we have built a scalable, secure environment. So we are in conversations with about 15 different hospitals out there. A lot of names that you would know, just to say it just yesterday, but being gay Sue, which is one of the largest children's hospitals in Europe, has agreed to be one of the vanguard hospitals. So our plan is to identify the eight we're covering. One of the reasons its eight is we're covering all the costs of doing this. So we plan to identify the eight by the end of May, and start installations in June. So that's our next big step is moving out to eight different sites. Once we've done that, I'm pretty sure not that we know everything. But we know a lot about what things we need to work on for scalability, security and performance. And we'll do another iteration test that but I think, you know, in this year, we will know what it takes to deploy a million servers.

David: 35:32

I mean, as we've kind of already said, the vision is incredible. What you kind of need to do to realise that vision, given that it's a million servers in every continent on earth, and the rest of it seems, seems to be, you know, quite quite a challenge and what have you. So what, what do you envisage the future looking like? And when?

Timothy: 35:51

So, you know, some people ask me a question, why children's medicine, right? I mean, doesn't adult medicine have the same problem? Like, Oh, well, yeah, adult medicine does have the same problem. But the idea that we would have any prayer of doing it in every adult hospital, I have no idea how you'd pull that off. Now, the nice side about children's medicine, I made the point earlier, there are about 500 children's hospitals in the world. Well, you can guess what that means is that about 25 of them, that are the leaders and you guys have been in this space, I think we all could write them down. We know who they are. So basically, the first objective is, let's get the 25, of which, by the way, eight, are going to be in this category already. Because if I get the 25, the other 475, well, will fall in that's not going to be that difficult. And I that's why this market is somewhat unique, I think and the prayer that we could pull this off, because it's this type of market, I think is very high. So the step after the eight, I think will really involve we're already having a ton of conversations about this. There are two angles to the next step one is research. So what research projects, which you could have never done before, are now possible, given this infrastructure. And so we're having conversation. In fact, I just had one this morning, a children's national who's been doing a lot of work in federated learning, is it going to be federated learning around CT scan data for COVID prediction? Is that what the thing is right, or what is it going to be? And this obviously lines up with the question of what becomes fundable? The one thing I say to people is, I'm not sure how AI and adult medicine gets funded. But I'm pretty sure there's no easy answer to AI and paediatric medicine. No venture capitalist is going to invest in that market. It's just not big enough. So it's gonna have to be a combination of, you know, foundations, government etc money that's going to have to come in just to pick on him for a second, we did an analysis of NIH funding. So NIH spends about$1.8 billion a year in paediatric medicine $1.8 billion. We tried to identify like, how much of that is spent on AI? 15 million, maybe? And we're stretching, right? So there's an education cycle. There's a lot to bring the research community together. And they have responsibility in this as well as like, well, what are the big clinical issues? What's the proposal, we're working with a team at Stanford, you could guess in a project called chamber to do aggregated paediatric echo data, and looking at the potential of that being funded by a number of different sources. So I think there's one whole angle, which is research, predominantly around AI, which by the way, and I tell their community this. You know, we have the chance in paediatric medicine to leapfrog adult medicine, because they have all the same issues. But you know, how are they going to get aggregate data? How are they going to do federated learning? I mean, you know, if this community gets together, we have the potential to leapfrog what they're doing. So I think that's one whole angle that we are going to press forward with the other whole angle is production applications. So you guys come out of my world. So we're just talking about ISVs independent software vendors, who because of the technology we have built, will enable them to do things they have never done before. So just a simple example, there's a company out there called Nautilus amusingly a company built by the guys who built the CD ROM exchange software. And they've now moved their application into the cloud. And so we're saying hey, let's build a Nautilus edge application, which if childrens of Atlanta decides to give it permission to access the echo or the CT scan, you can now do image exchange and annotation using the centre cloud application at Nautilus. And then I mentioned as clinical application to help the clinical engineer who today is managing. I mean, at Stanford, there's 20,000 assets in the building. And they're managing in the disconnected state, they don't know where the machine is, or whether it's being used. So you know, if you have too many machines, do you have too few machines, no one knows. So they're going to be more, these are just early kind of people that we've been working with ISVs, that we want them to use the infrastructure to develop new applications or extend their current application. So those are the two big directions.

David: 40:57

Typically, we could literally talk about this, given that this is kind of our area of interest. Very conscious, you know, of your time. I'm very grateful for the time that you've given us. One of the things that stand out is, and it's great that you know, this kind of thing is happening in pedes. First, and I think we can all agree that if it if it works, which we all have full faith, it will, then the opportunity to scale up to adults is there and hopefully it has been, it makes it a lot easier from that point of view. And that's kind of exactly the essence of what we're trying to convey for, from not mini adults podcast perspective, I've got a couple of kind of closing questions for you. One is in one sentence, you've talked about it a lot, but I'm just conscious that some people won't understand necessarily tell us what federated learning is in kind of one sentence or, or maybe two.

Timothy: 41:52

I don't know that I'm good enough to do it in one sentence, but I'll explain it this way. In contrast to federated learning, classic learning is, I take data from many different sources. And I bring it into a central location. And I try to train my algorithm using all the data in a central place. What federated learning says is you don't need to do that you can leave it in place, and only transmit model parameters. So it's all been architected. In fact, if there's a great video that Andy Trask does, you watch this thing, it's all been done for healthcare, because of privacy concerns. So rather than transmit the data anywhere, just transmit model parameters, so do the learning at the edge is how we would say it right. So that you never have to let the data leave the third floor of alder Hey, just to pick on him. Right?

David: 42:52

Yeah, no, perfect. Thank you. And if anyone so if there is someone from a hospital that may not be in that eight that is listening and is interested, what do they need to do?

Timothy: 43:02

Oh, reach out. We'd love to talk. Do you guys, you put a email address down. Just share the details. I just as a comment, I'm on LinkedIn to reach out. And LinkedIn is another easy answer to this. We are a consortium of the willing. So anybody willing, come on down?

David: 43:23

Well, so we will certainly share all your details on that on the notes, so everyone can can hopefully get in contact. Final question that we ask everybody that comes on to the podcast, Timothy, which is if you could solve one problem within paediatrics, what would it be?

Timothy: 43:39

Well, it sounds self serving. But I think we are solving the one problem, paediatrics. You know if we could pull this off, I don't actually think it's a if it's when we pull this off. It will change everything. I mean, the evidence I have of this is just imagine our world before 1994. And imagine the world today, it's so completely different, because we live in the connected state. And they live today in that fractured siloed world that we all used to live in back in the 80s. And that level of change is possible with technology. And the willing and I you know, like I said, probably self serving, but I think this is the one thing.

David: 44:23

Thank you. I had to ask the question. I've failed to ask it previously, or at least try to guess what the answer is and got it entirely wrong but I thought you'd say that. I'm glad you said that. Thank you so much for joining us. Thank you for your time, I think, you know, it's been a unique and fascinating conversation, and I hope everyone will agree with that. So really appreciate it.

Timothy: 44:44

I appreciate you guys taking the effort to do something like this, you know, without getting communicating without sharing ideas is we're not going to make it very far. So I'll equally say thank you guys for doing these podcasts. And I love the name Not mini adult. It's great.

David: 45:06

Thank you so much to Timothy for joining us on the podcast and we wish him every success in his endeavour, we can really see how connecting the world's paediatric data can have such a huge impact on the health of our children and children for generations to come. Next week, we're bringing the conversation back to the UK, and we're joined by Dr. Don Sharkey to discuss innovations and technologies within neonatal care. We really hope that you can join us then please do subscribe to the podcast. And if you're enjoying it, please do leave us a review as well. We hope you'll join us again next week.