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Speaker B: How does a model determine what health is? |
Speaker D: So. And then I can go back and give you kind of a. Hopefully it'll be interesting, kind of the inside story of kind of the daily struggle of running a company like humanity. So the base truth. And a lot of people are starting to base models on this and for different things like drug discovery and things like... |
Speaker B: Right? |
Speaker D: I think we're all fed that, that meme so many times. We don't, we don't know the difference. Correlation is not causation, but correlation isn't good enough to predict the future, right? |
Speaker B: Correlation is correlation, yeah. |
Speaker D: And, and if. If the same things happen at the same time, repeatedly, that's good enough to predict the future. That's what all these models are built on. To maybe emphasize it a bit more, to really put it in people's heads, is anything you measure on the system, in this case, the human body, years ago, becom... |
Speaker B: So one thing that I'm kind of just excited to watch is that we are, I assume, the amount of data that we are collecting from our wearables, and also the strength and precision of our algorithms, both are up only and probably in an accelerating fashion. And also, when there's two things that are accelerating ... |
Speaker D: Out of that, the competence oriole, it's. |
Speaker B: Like, it's to the power of two, right, is the output of this. And so, like, one thing I'm excited about is to watch this humanity app develop in strength and power and significance over time. And so, like, can you just paint a picture of what you want humanity and what you want this part of the health indust... |
Speaker D: Yep. I think what we want to be is, and relate this to a theory. We want to be a beacon to actually show at scale that you can basically take this data and then figure out exactly how to guide the person with it. And so we want to show that both it is worthwhile for us to do the little bit of work it takes t... |
Speaker B: Humanities told me that I started the app at 30.3, and I'm now at 29.7. |
Speaker D: Cold plunge. |
Speaker B: Cold plunge. |
Speaker D: Shout out. Cold plunge. Yeah. So I think that's one thing. And then on the side, and especially now that I've been in, you know, at Zuzalu, it's been quite a. It's motivated me even more to push because I think, like I said, blood's in the water with the AI. Like, people now know, they feel it, they taste th... |
Speaker B: Right. |
Speaker D: And so what we want to do is be basically a beacon to show, hey, you want to start training models? First of all, you have a bunch of data. So I think sometimes the conversation starts with, how do we motivate people to start collecting data is already there. The health systems have a ton of data. Every sing... |
Speaker B: Google Maps for health is great. Is a great model. |
Speaker D: Exactly. Yeah. And we are very good at why we got into this is we're very good at people using an app and changing their behavior because of the app, all the things that we might not like about some of the other social media apps, that stuff works to change behavior, and we're using that to change health beh... |
Speaker B: Certainly, yeah. And so I'm gonna hit record on my phone here, and we're gonna pull up the humanity app. And so congrats on actually introducing a new app into my life. That's not an easy thing to do. I haven't gotten a new app in years now, but, like, I've been using humanity for ever since coming into Zuza... |
Speaker D: Yep. |
Speaker B: And so you want to score as high as possible. I've got 80 points so far, so I got, like, 20 to go. |
Speaker D: Well done. |
Speaker B: I've never gone higher than, like, 92 or 93, but I still. It's showing me a blue color, and I like blue. It starts off redhead, but blue feels. Makes me feel good. |
Speaker D: Got to get the blue. |
Speaker B: And so, like, talk, can you walk us through movement, nutrition, mind and recovery? How, like, how do you know how many points to allocate to each one? And how does that. How does that math get determined? |
Speaker D: Yep. So, yeah, like you said really well, earlier, we wanted to boil it down to things that are quite easy for the user to follow. And getting more points in a day, you know, is an easy thing to follow. What we do is we translate, so we figure out how impactful each of these actions will be for your type of ... |
Speaker B: So my points are my point, but if I get two points for doing this one activity, that's because that app weighted me to have those two points. Somebody else could be given a different weighting because of just the data that they have. |
Speaker D: Exactly. And so when you're going through your guidance, all very simple stuff. Once you have that semi complicated kind of back end system, very easy to then say, hey, we're just going to raise the guidance to you in order of the most points, and you can scroll through, you can decide, hey, I'm not going to... |
Speaker B: I skip my meditations. I'm naughty on my meditations. |
Speaker D: Sorry to call you up. |
Speaker B: Which is why my mind is. My mind part is at the lowest, which makes sense because I'm a chronic user of Twitter and other things like this. |
Speaker D: But you're expanding your mind here at Zuzalu. So, yeah, so then that's how we apply all the science and all the tracking in the back end then just gets applied to. You're getting, you know, as you go, you know, maybe we need to give you four points for meditation, and then we'll. Then we'll get you over the... |
Speaker B: The longer that I go without meditating, the app starts to wait. |
Speaker D: Okay. |
Speaker B: You need to meditate a little bit more, bro. So, okay. Nutrition, movement, mind recovery. I would assume, like, as more data is available, more pillars could come online based off of what the models and the data suggest. |
Speaker D: Yeah, yeah. It's quite simple right now. The cool thing is you also get a bit of a kind of a crowd, a crowdsourcing thing that will be going on will more and more allow people to actually enter in things that they're trying or doing. And so our thing is, like, take everything at face value. If someone thinks... |
Speaker B: Right. |
Speaker D: So it sounds like a complicated matrix, but that's the great thing that, you know, computers and AI are very good at keeping these things straight. |
Speaker B: So, speaking of complicated matrix, I think one other we were talking about, okay, more users are wearing more wearables, so there's more data out there. The missing part of that that I forgot to bring up is wearables are actually getting better. |
Speaker D: Yep. |
Speaker B: And so we're not only are we getting more data, but our wearables are actually getting more precise about things. |
Speaker D: Yeah. |
Speaker B: So, like, is the bull case for this is, like, almost any variable about the human body, like our. Our glucose in our blood, our insulin levels, like, etc. Etc, is actually going to become more and more measurable. And that's what all gets fed into this, at this app that you're building. |
Speaker D: Yeah, yeah. And it's happening very quickly. And, like, you're saying that then you get an exponential effect of, like, the thing that we're missing right now, other than humanity doing it, is we're just not using the data. But, yeah, once more people are using that data, like we are, I think. Yeah. Then the... |
Speaker B: Yeah. Maybe we can take this back to the beginning, which is this is a perspective at a vantage point that the traditional healthcare system has not been able to have or be able to operate with. And so with all of this data and with this data being made available to everyone, what is your hopeful case for th... |
Speaker D: Yeah, that's a great question. Well, one hope is, I hope they see us much later in life. Sorry, guys, you're not going to see me for a few decades. That's one hope. I think the other thing is, I mean, we started to see this a bit in Covid, and honestly, it took us about six months into Covid to start even, o... |
Speaker B: Right. |
Speaker D: And so, again, you're less trying to categorize things. You're just letting the AI say, we have seen this before, and we know how to get this person back to that. We know the path. |
Speaker B: Right. Right. Where the current practice of medicine is probably just so blunt, as in, just like it produces best practices for standard. |
Speaker D: Of care comes from a very sometimes not varied enough population of patients, and sometimes too varied in the sense that the standard of care is like, the least harm that we can do to the general population. Unfortunately, you're not the general population. |
Speaker B: Right? Yeah. When you walk into a hospital, you are treated as if you are general population, which you both are, and you are nothing. And with this new world with, you can come in, maybe they scan your wearable, download all of your data and be like, here's what this person is. Here's how they're different ... |
Speaker D: Yep. Yeah. And I will say this. I think we're seeing kind of an analogy with, like, large language models. Just a shout out to the AI watchers. I think there's been a lot of talk like, well, we need to compute the world's data and spend $100 million to create a good LLM. But even just months later, we're see... |
Speaker B: Right. |
Speaker D: That standard of care just like, statically lives. Right? And the biggest thing is we need to keep feeding the results in and be like, hey, actually seems you can both personalize it more because you do that. Because why did it work for that person? It didn't work for that person. You get so many of those ca... |
Speaker B: So, Michael, thank you so much for guiding us down this conversation. |
Speaker D: Thank you, David. |
Speaker B: If people are interested in trying out the humanity app, where can they go? |
Speaker D: Yeah. So if you have an iPhone, you can use it right now. So just go to the app store, put in like, humanity, humanity health, and, yeah, check it out. And we love feedback. We're constantly learning and growing. And the more data we have, the better it is for every single user. And then Android is coming so... |
Speaker B: Awesome. Michael, thank you so much. |
Speaker D: Thank you, David. Cheers. |
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