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Speaker E: It's quite the list. |
Speaker F: Yeah, you've got your hands everywhere a little bit. And then also wins on tour, which regrow your nerve endings, which is really cool for neuropathy and pain. And a couple other companies that are in stealth mode. One of the fun ones is actually through the Methuselah Foundation. Vitalik donated 43% of the ... |
Speaker E: Dogelon Mars. Yeah. That's on the long tail of dog tokens for sure. |
Speaker F: Yeah, it's actually, I don't know if it still is, but I think it was dogecoin, Shiba and Dojilan Mars, which is number three in the world. It's incredible fun community and yeah, it's a really interesting story for sure. |
Speaker E: Yeah. Well, thank you for guiding us through all of this crazy, crazy topics. This is only like one of many, many longevity topics. So thank you for walking us through the top of the rabbit hole and I hope to continue going down it throughout this week. |
Speaker F: Thank you. Thank you so much for having me. |
Speaker A: Thankless nation. |
Speaker B: We are here at Zuzalo and I'm talking to Michael Greer of humanity. Michael, what's up? |
Speaker D: Not much. Great to be here. |
Speaker B: Michael, I first met you at the 08:00 a.m. cold plunge and you have been there every single day. |
Speaker D: Been best friends ever since. |
Speaker B: Best friends ever since. So you're at an interesting intersection between all of the various topics that are being talked about at Zuzalu. The intersection of longevity, which we had a longevity week. I think we're going to have another one and also AI. So that's a fun little place to operate in. Tell us a l... |
Speaker D: Yeah. And honestly, I think you can throw the public goods and the crypto into the mix there as well. Yeah, I mean, I started with, I think a lot of people in health tech start is they have someone close to them or themselves have kind of a really tragic health event. That kind of, you learn the cliche that ... |
Speaker B: Right. |
Speaker D: More susceptible. |
Speaker B: One step in front of that. Yeah, yeah. |
Speaker D: Because what, what the whole. I mean, we don't need to go into the whole healthcare system, but I think most people that spend a lot of time in the healthcare system call it sick care now because we focus at that end stage where it's not too late, but it's like the person's already pretty diseased and you're... |
Speaker B: And you're saving them in the most expensive part of that trajectory and also the part of the trajectory where they are suffering the most. |
Speaker D: Yeah. |
Speaker B: And so that is the part that the current institution of medicine is prolonging the most. |
Speaker D: Yeah. And. And it's good that they're there. The problem is not that they're doing. They're giving sick care. That's great. And they do amazing job in hospitals doing that. The problem is that we don't have a lot of emphasis on much earlier. |
Speaker B: Right. |
Speaker D: In that. In that process. And so a lot of people have. Well, almost everybody has the intent to stay healthy or to be healthier, but there's just very few tools out there that can actually lead them in the right direction. And so, eventually, once I had that idea in my head, I don't get excited about stuff u... |
Speaker B: Sure. |
Speaker D: So across our user base, we're looking at all the users, what they're doing. Then we're finding users like you. So, you know, your kind of biological sex, your age, you know, different attributes of you, and seeing what seems, what group of actions is seeming to positively affect this endpoint. And that endp... |
Speaker E: Right? |
Speaker B: Yeah. There's a lot of magic behind the. |
Speaker E: Scenes at the app that I definitely want to dive into, and we'll see. |
Speaker B: If we can get some visuals up on the screen as well. But first, I still want to zoom out and just, like, can you give us, like, a high level, just mission statement for you and humanity? And also tell us just a little bit more about the is ought gap between the current institution of health and where you thi... |
Speaker D: Yep, I'm gonna. Sometimes I'm gonna stop you and ask for definitions of some of these things. Sure. Is ought is a. |
Speaker B: Is odd gap. Yeah. So there is the is odd gap. |
Speaker D: Is, like, currently have and have nots or the. |
Speaker B: Currently. The world of medicine is one way. |
Speaker D: Okay. |
Speaker B: And I think you, as a result, ought to be some other way. |
Speaker D: Cool. |
Speaker B: So where is it and what it be? And then, like, your own personal mission statement with what you're building here at humanity. |
Speaker D: Cool. Yeah. So we try to boil down our mission to real simplicity. We want to give a billion years of health back to humans by 2030. |
Speaker B: That's funny. So at bankless. Sorry, just a slide. Cuts. We talk about we want to help a billion people go bankless. That's been our line. |
Speaker D: A billion. It's a nice, round number. |
Speaker B: Yeah, it's the largest number that humans can still reason about. |
Speaker D: Exactly. But, I mean, so the consumer VPN that I was running, we got to 900 million users. So, like, the beauty of the Internet is that you can. You can actually affect that many people. Right. So that's the mission. We want to get back those billion years and very specifically healthy years. |
Speaker B: Right. |
Speaker D: So those fully functional, or, you know, mostly fully functional, healthy years that we, almost all of us enjoy living. And so that's. That's the mission and kind of what we have right now. I would say the biggest thing, if I was to cut straight to the chase, we don't measure our health. So those that are re... |
Speaker B: Right. There's so many out there, and you're saying that even the very blunt tool of your phone in your pocket still can provide sufficient data. But then we're many years into the Fitbit revolution. Now we've got the apple watches, there's the whoop band, there's the oura ring, there's the sleep eight mattr... |
Speaker D: Exactly. And apply it in, almost leave the kind of clinical trial system and these kind of, like, small research study things behind in a way, because the secondary problem. So that was the big is odd. I. The secondary problem is that we. Because I think in the past, it was easier to have one common marketin... |
Speaker B: Right. |
Speaker D: And that thing can give you very personalized stuff. And we. And we actually are unhappy when it, you know, we talk about how personalized it is. These. These ads know too much about me. |
Speaker B: Right. |
Speaker D: That same thing. Knowing everything about you can give you specific health knowledge. Right. So. |
Speaker B: Right. We can start to turn it around and start to use it for our benefit. And I think this is where just perhaps the AI conversation starts. Because the idea is when so many people have their phones, everyone has their phones. And even not as many people have phones as has wearables, but a large number of p... |
Speaker D: And in their closet, too. And now they're taking them out to use with the app. |
Speaker B: Right, right. Yeah. So, like, I've had an Apple Watch and I've loosely worn it here and there, but since coming here to Zoozalu, doing the morning cold plunges, going on the runs, having this app to actually tell me what's going on with that data, all of a sudden, my rigorousness about how frequently I'm wea... |
Speaker D: I'm going to cut this part of it. I'm just going to send that to Apple. Feature us more, please. |
Speaker B: Yeah. Official iOS partnership app. |
Speaker D: Right? We're selling watches. |
Speaker B: Okay. So we have all this data. We have way more data than I think we know what to do with. And maybe that's even, like, one of the big problem statements. We have more data than we actually can apply to actually know what to do with it when it comes to our health behavior. But I think this is where perhaps ... |
Speaker D: Yeah. And I think what you're touching on is also, I think we've had a few years. I think all this stuff just puts it in the mainstream. So I don't think any of this was, like, a wrong direction, but we had a few years of like, hey, we have a bunch of data on you. And here's some cool graphs, right? And, and... |
Speaker B: That's your heart rate variability, by the way. |
Speaker D: And so I think, sorry, what was the question? |
Speaker B: So now that we have other tools, not just wearables, not just data, but we have AI and lots of data, what can we do with this? |
Speaker D: Yeah, so I think that's where the cool, the cool thing that happens is when you have enough of this data, no matter if data is noisy, no matter if data is interspersed, and you're not getting it every day. The great thing about AI is it actually can just still, it looks at all that data and it can find all t... |
Speaker B: Right. And I really want to drill down on kind of the problem of all this data that we have for anyone with a wearable or an apple will. I'm sure Android has this, too. But if you open up your health app, you can just scroll and scroll and scroll through all the things that it's measuring. |
Speaker D: Right, sorry, Apple Health app. |
Speaker B: Yeah, they're taking some credit back. So, like, it measures things like your gait imbalance, right? Which leg that you put more weight on while you walk. It measures heart rate variability, which is very useful. It measures how many steps you take. Like, it measures everything that it can get its hands on. ... |
Speaker D: Yeah, and I don't want to be overly positive, but there is the other side of the coin, which is basically these platforms, these hardware companies, or if they consider themselves hardware companies, their sensors are getting more and more prevalent. More and more people have them and they're getting better ... |
Speaker B: Right. |
Speaker D: But they create this process, this feature that they take out of that data that then we could use. Like, I mean, if you're a sports app, you get gait instability. You're like, okay, you're injured. Here's go out on this route. Right? And I think that's so there's an ecosystem where there's easier and easier ... |
Speaker B: Okay, so when you apply AI to all of this data, can we just unpack a little bit more, like, what that means? Because in this day and age, we just say, and then we do AI. |
Speaker D: That's where the variable reward is. You press the button and magic happens. What magic am I going to see next? |
Speaker B: So how does humanity actually apply AI to produce meaningful results for its users? |
Speaker D: Yep. And so we're doing something, I wouldn't say simple, but it's, you know, it's kind of like really good machine learning on it, which is basically saying, what? So we see all these actions that people are taking, and so we take all these values from your. From your wearables, from your. From your phone. ... |
Speaker B: Right? |
Speaker D: So that's where the stratification is the most important. And so you just do that repetitively every single day, and you can take time periods, you can start to understand if there's a lag between an intervention. So maybe if you do a cold plunge, we'll see your prediction of health better in three days and ... |
Speaker B: Right. |
Speaker D: So you start to learn all this from the data, but in the end, it's, it really is exactly like traffic navigation. You're not trying to do a study on side streets versus highways. You're basically like, hey, these cars were heading on all these different paths and all these edges put together made a better en... |
Speaker B: So, okay, so let's talk about some of the healthy behaviors that do actually move the needle. So we have all of this data, but most of the data is probably trash. And some of the data is probably really, really good. |
Speaker D: You always got to be careful with that because I think the genetic space played this out very well. They're like, these, these are gene encoding areas, and then there's a bunch of randomness that, you know, throw that stuff out and they're like, oh, shit. That actually. |
Speaker B: Well, no, no, some data is going to be more valuable than other data. |
Speaker D: Correct? |
Speaker B: In the moment, yes, in the moment. Right. And so, like, maybe we could actually just, like, zoom out and put humanity aside. We'll, we'll open up the app in a second. But just like, talk about what are the big behaviors that do move the needle for people that can actually be measured by things like our fitne... |
Speaker D: Yep. So I think there's a bunch and you need to be monitoring yourself and the combination is important, so I'll keep repeating that throughout. But the combination and the one that probably people, people could understand that they're different, and so they pick up on that quicker. Like, okay, it works for ... |
Speaker B: And probably also the order of those two things also matters, right? |
Speaker D: Yep. Yeah, exactly. Timing. Yeah, yeah. So order, you can see so well with nutrition, right? So if you talk about, like, blood glucose and it's spiking, and that. That being generally bad, at least, you know, according to what we know so far, is, you know, if you go for a walk, this is why some of these comm... |
Speaker B: What are the behaviors that really move the needle? |
Speaker D: Yeah, people always want to know. So I'll list a few, I think, from our data. I'll give it straight from our data we're actually seeing for some cohorts, and you may or may not be in that cohort, so please don't take this as a prescriptive thing. In some cohorts, moderate intensity activity seems very. Has v... |
Speaker B: So. And you said moderate activity doesn't move the needle. Can you define what that means to move the needle? Like, what does that mean? |
Speaker D: Is it impactful, in this multivariate analysis, this group of actions that people are taking in a day, does it seem to be impactful on reducing their probability of future disease to that endpoint that we're trying to affect? |
Speaker B: And that's just based on scientific study that we are looking at from indicators of health? |
Speaker D: No, that's directly from the data, is saying, yeah, our prediction that we're getting from your movement pattern and your heart rate pattern on a daily basis, that prediction doesn't seem to be moved, impacted by, in a couple of the strata, by the moderate. And so that means. And you don't want to then immed... |
Speaker B: Right. |
Speaker D: But it is exciting now, I'll admit it. It's quite exciting to, like, see the real data now, because I think in the longevity space, it makes a lot of sense. But again, this is my own personal Michael Gere kind of conjecture is there are certain things that you trigger in the body when you do high intensity e... |
Speaker B: Right. And we would only really be able to know this if we have a lot of data and the models to be able to create these relationships, assuming. Right? |
Speaker C: Yep. |
Speaker B: And so, like, one question I have is, like, going back to, like, what does it mean to move the needle? There's one. There's one perhaps way of making a health app, which is going through all of the literature and all of the studies and all the doctors that say, hey, this is good. |
Speaker D: It's kind of the way that most health apps are made, actually. |
Speaker B: Right. And then there's another way of doing this, which is just giving models, AI models, a bunch of data, and then also cross referencing that with how healthy these people are, how long they live, and actually have the AI models determine what is good. |
Speaker D: Exactly. |
Speaker B: And then that sounds like kind of more of the approach of the humanity app, where you don't want to actually have, like, inputs as to what is good or what is bad. You just want to input a bunch of data and have all of that data create relationships with itself, and then have the AI model say, like, oh, well,... |
Speaker D: Yeah. |
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