All-In with Chamath, Jason, Sacks & Friedberg
00:14:24 · Will Ahmed
[00:14:24] S0: So HRV stands for heart rate variability. It's the amount of time between successive beats of the heart. And and it's a little counterintuitive, but the more variability in time between successive beats of the heart, the healthier your overall system is operating. And it's this lens into your autonomic nervous system, which consists of sympathetic and parasympathetic activity. So sympathetics activation, heart rate up, blood pressure up, respiration up. It's what happens, you know, when you have a thought like the... There's a lion in the room or, you know, when you start to exercise or you're thinking about something stressful. Conversely, parasympathetic is all the opposite. Heart rate down, blood pressure down, respiration down. It's what helps you fall asleep. If you exhale for a long period of time, that's parasympathetic. And what you want is for for sympathetic activity and parasympathetic activity to be coupled, and so your body's kind of constantly regulating its environment. And when that's the case, it it means you have a higher heart rate variability, that the measurement will be higher. And we're measuring heart rate variability twenty four seven. It was really one of the the key innovations in founding the company. I did all this medical research when I was a student at Harvard and heart rate variability was a thing that jumped off the page to me because there was really interesting research on it but it couldn't be measured twenty four seven. And and so that's where, you know, part of where Whoop was born out of. Anyway, heart rate variability is something that we use for stress monitoring. It's something we use for our recovery score. And and we baseline everyone on Whoop, then we're able to show you every day, are you within your baseline? Are you a little higher? Are you a little lower? When you look at trends of this over years, you start to get a sense for is someone getting healthier over time or or less healthy? It's a really important longevity indicator. Typically speaking, as you get older, your heart rate variability will drop. So, you know, people who are in their twenties, their heart rate variability will be anywhere between, like, 80 and a 100 on average. Thirties, you start to drop to 70. Forties, you start dropping to 50. You know? Fifties, sixties, all of a sudden, you're in, you know, thirties and below.
00:16:37 · Will Ahmed, Jason Calacanis
And so if you can fight that trend, that... Those averages and keep your heart rate variability even just flat over years, that's actually a sign of good fitness, good longevity. And, anyway, back to the story I was telling you, the... This individual, they had a very steady heart rate variability that was within a specific range and all of a sudden it plummeted. So it was a healthy person. They had a heart rate variability of about a 100 and and then it was 50 all of a sudden for for a period of time. Again, goes in, gets all these tests. He turned out to have testicular cancer. Oh, wow. And so [00:17:11] S1: Now was that known previously that HRV would in some way be a a lead indicator for testicular cancer? [00:17:19] S0: I mean, I don't think so. You know? That's what's so fascinating about this moment in time is we've never had this much data on the human body continuously. One of the principles to founding Whoop was twenty four seven data. And it's it's why we have a fourteen day battery life now. It's why we we invented a charger that you slide on to your Whoop. [00:17:39] S1: I was about to say these are super important. And when you first told me about this on on this week in startups, I was like, wow. I need a... I wanna see how many steps I've done and the time. It makes no sense. And you were like, trust me, Jake. I'll... [00:17:51] S0: You know,
00:17:51 · Will Ahmed, Jason Calacanis
[00:17:51] S0: You know, [00:17:51] S1: there's a reason for this. Yeah. And now that I've used it, it turns out you're absolutely right. The reason I have had so many long streaks... The only time I really stopped using this for the past couple years is when I lost it and I had to order a new one. So it broke my streak, which was a bummer, but it is what it is. It's just a number. Because you can wear it in the shower, you can wear it in the bath, and you should. It turns out a warm bath is... When we get to journals in a minute, super, great for my recovery for whatever reason and my sleep. You never have to take it off. And you can slide on the battery charger. So you can have essentially the opposite experience that I had with my Apple Watch. The Apple Watch was annoying because it's... I'm getting alerts, and I'm getting alerts for things that I... App I installed two years ago, and it's just constantly bothering you. People think you're rude when you look at the watch, and then the battery dies every, you know, whatever. For the Apple Watch, I think I might have gotten to twenty four hours or thirty six hours, forty eight hours a couple times, but it's a terrible experience. With this, I I mean, I I've made it ten days, you know, fourteen days. No problem. And I carry... I bought three battery chargers. I just keep I keep one in my desk. I keep one on the bedside, one in my bed... My travel bag. It's like these things aren't expensive. And and that's a key to it, think, as well. Yeah? Is the the amount people wear these.
00:19:14 · Will Ahmed, Jason Calacanis
[00:19:14] S0: On average, a Whoop member wears Whoop 23.6 a day. And as a consequence, we have just over fifty billion hours of continuous physiological data. So it's one of the largest health data sets in the world. And now with the, you know, the advent of AI and what you can do with large data sets, it's just like a really exciting time to be working in this space. [00:19:40] S1: Do all the AI companies, like the frontier models, wanna buy this data from you in aggregate? Is that like a huge business for you guys eventually? How do you think about that or building your own models? [00:19:51] S0: Yeah. Today, we're building our own models, you know, foundational models within the company that are essentially training on top of this data. So one So [00:19:59] S1: you're using open source models or you're you're you're [00:20:02] S0: We're developing our own models. We've got open source models. And and what's amazing is you've got this huge physiological dataset, but then you also now have other datasets. Right? So people are uploading their blood tests or they're doing advanced labs through Whoop. They're uploading medical records. And and so as an example, we're we're now starting to see indications that through physiological signals, we might be able to predict that a biomarker is out of range without actually measuring the biomarker itself. [00:20:33] S1: Wow.
00:20:33 · Jason Calacanis, Will Ahmed
[00:20:33] S1: Wow. [00:20:33] S0: And so then, you know, you could give someone a very targeted, hey. We think you're... You know, we think you have high cortisol. You should get this one test. And and it gets... And, you know, and it gets super it gets super targeted, which is exciting. [00:20:46] S1: Which the AI would be able to figure out. The AI is gonna look at all this data and say, hey. Maybe there's a cortisol this year or here's the possibilities, which is super fascinating. So not... You you see your business in the future as this AI assistant, and you added an AI assistant, I think, to the product less than six months ago. I'm addicted to it now. Yeah. And you have these ongoing conversations. It logs the conversations. And so now it was, I'll be candid, pretty dumb at the start. It would be like, you know, you could talk to it and you'd be like, yes. You had this rate. Okay. Thanks for that rate. But now it's gotten a bit more sophisticated because now when I tell it, I'm in Japan. You didn't record my sleep. It's like, oh, okay. Here's what's happening. And it actually is understanding the product, and I I I guess you're doing some reinforcement learning. [00:21:35] S0: Yeah.
00:21:35 · Will Ahmed, Jason Calacanis
[00:21:35] S0: Yeah. [00:21:36] S1: And it's gotta be that these 4,000,000 members, including myself, are now telling it where the product breaks down. Because when you... Or or where the opportunities are to add more features, however you wanna look at it. But there's this constant struggle I was having with changing time zones. And was my, was my sleep getting recorded properly so then I can get my recovery? And then I started asking, and then it prompted me and said, hey. By the way, when are you leaving for Japan or whatever? And I was like, here's my flight. This is when I land. And it was like, you should sleep at the first half and then not go to bed when you get to Japan. Don't have caffeine at this time. So somebody in the company, I think, explicitly started doing a time zone change, or did it just learn that and infer it? What... Did you did you get specific about that, and how are you using the AI coach? [00:22:28] S0: We spun up a team on travel specifically because it's such a popular use case for a lot of our members and, you know, our origins were with athletes, but now we've got this wide audience of aspiring people. You know, I'd say that's really the... If you think about who is Whoop targeting, it's the aspiring. And that could be a great athlete, that could be someone who's fit, but it could also just be someone who wants to have more energy for their family and their job and their life Yes. Hobbies. That's right. And wants to live longer. Right? [00:22:54] S1: Yeah. Live longer.