Yeah, I think it was Patrick Coulson that said that status lags by one generation. So like for people to understand, this is going to be a lag by one generation regarding the media. Let's say, let's actually go to the pre-history and we didn't speak about Nucleus, man. Like say, how did you think about the idea? I heard about the story, but brief us about that. Kyriakos: Wow, look at that. Let's do it. Kian: Yeah. Is this acquisition? Kyriakos: No, we've acquired the old scientist academic product years ago. I'm trying to think. I feel like we acquired one other thing, but this is definitely the most recent. And this is definitely the most kind of public one we've done in that it's very strategic. You know, so you knew about Cambrian. Did you know about Cambrian before the announcement or no? Kian: I know David. Kyriakos: You know David? Well, obviously David's just joined Nucleus. Love David, shout out to David. Founder of Cambrian, absolute beast. You know, he was a professional soccer player. Yeah, smart guy. Athletes are the best because you know they're going to die in the field. Anyways, so yeah, David joined Nucleus. We bought Cambrian. What Cambrian did is they took a bunch of different wearables, right? Eight Sleep or Apple Watch. I mean, you probably know them very well for this reason. And they basically would give you new insight into your wearables, into your biometrics, etc. And when I spoke to David, I said, look, David, you know, there needs to be an integration of all these things. I said, we're stronger together. You got to join Nucleus. And he did. Kian: And so now you can start thinking if you're a Nucleus customer, you can get very excited because yes, we're going in this direction, right? We don't, from a single swab, you don't just get analysis on over a thousand diseases, but before, and you know, into your family planning, etc., but also you have that foundation. Or again, I like to say DNA for us is like books for Amazon: it is the foundation. Just wait till we start integrating in these other data layers. Because now we can start telling much more precise and personalized stories about the customer that gives them far greater insight into what they uniquely should do. Kyriakos: Right, instead of just using your blood, you know, often just your blood, you don't have your DNA. You have no idea what's actually driving a metabolite to be off. It may as well be in your DNA. You have no idea. Similarly with full body MRIs, right? Ideally, you can actually prevent the thing from happening in the first place. You don't want to go and say, hey, you have cancer. Kian: Yeah. Like all of the health information compounds. Kyriakos: Exactly. One, two, three, it's just so much more powerful. So much more powerful. And so that's what we're building toward and that's what we want to do. And that's also why we take a very different approach in a lot of businesses in that we want to be the best in the world in the DNA first, right? Like we really believe in the old startup thing, which is like about focus, right? A lot of companies I think are taking the wrong approach where they're, let's throw as much data as we can at the customer. If you bring someone genetics in their blood and they don't talk to each other, what does it matter? Doesn't matter, right? If you have a bunch of, you know, you want one plus one to equal three, not two, right? It's not enough to bring disparate data sources into a portal. That's not enough. You need to be able to integrate the data together. And so that's our core interest as a company, which is how do we methodically and thoughtfully integrate data together and give people more insight. Kian: And actually we already do this. If someone knows the platform well, they would know that when we calculate your risk for disease, we don't just take your entire genome. This is one of the most underappreciated things about us. We don't just take your entire genome. We actually combine it with your age, your sex, your BMI, your LDL, your A1C levels, etc., into an integrated model that then calculates your overall risk. And the reason why this is so important is because think about if a male had a breast cancer marker and a female had a breast cancer marker. Obviously, the male's risk for breast cancer is dramatically lower than the female, even though it's the same marker. And so in other words, all our genetic results are contextualized with a series of other non-genetic pieces of information, which means we're actually the first and only integrated health platform that takes the entirety of your DNA and different metabolites like your total cholesterol to calculate your overall risk. And then that also means you can see how your LDL changes, changes your unique risk for a disease. Kyriakos: So I can actually see today on Nucleus how if I change my LDL levels, my risk for heart disease comes down, right? Which is really powerful because you can start seeing how you can put that, connect that with a wearable and say, look, Kian, you're a really high risk for heart disease, right? Which fortunately I'm not, but let's say I was. Hey Kian, you're a really high risk for heart disease, you know, you got to keep up the intensity on your whatever, whoop, you need to be on level E5 or something, whatever for this amount of time. That's going to help bring down your cholesterol levels. And if you bring down your cholesterol levels by 20 points, your risk for heart disease will come down by 15%. Notice I just told you a story. I started with your DNA. I started with what you're at risk for. I talked about blood and I talked about how, if you, given your genetic disposition, right? So it's unique to you. If you actually bring down your LDL levels by 15 points, how your unique risk will change for heart disease, right? So all of a sudden I'm bringing together blood, I'm bringing together wearables, I'm bringing together genetics. I'm actually quantifying the change of risk for you, not in general population, for you. And that I think is so powerful because suddenly you start creating the foundation of a true personalized integrated health platform. Kian: And I can't keep asking questions, sorry. I think, let me ask you the last one. Or maybe we didn't, I'll ask you two more. We didn't speak about the race, the last race that you've done now. How much did it change from your first one? And why are you doing the race? Kyriakos: Well, these rounds now come together, you know. We talked about this earlier where, you know, the first round is the hardest, but then after that, you know, once you start getting momentum and you hit some sort of closer and closer to some sort of escape velocity, the investors come. And we had support from our current investors, Founders Fund and 776, NIO came in, you know. Ali and Suzanne are amazing. Kian: Is NIO? I thought it was an accelerator. Kyriakos: NIO actually has a later stage fund and they're actually, you know, finding the best, you know, kind of series A companies and putting money into it. Ali is doing an extraordinary job there. He's really good with AI. I usually see him wherever he shouts in all the, have you seen what he's doing? Kian: Wait, like with the videos, like on LinkedIn? Kyriakos: In all the hackathons, basically, he goes and runs on stage and shouts. Like shouts, like, have you seen Steve Palmer? Kian: Yeah, yeah, yeah. Kyriakos: He's doing the same. Just kidding. I caught it. That's iconic. And yeah, we had a bunch of different, you know, angels to come in as well. We had like Amanda Bradford, for example, who was doing a really good job there. So, you know, we had a lot of fun, a lot of strategics in this round as well. And so this capital principally, I mean, we're just gonna accelerate growth. I was gonna keep going. I mean, you know, the largest whole genome database in the world today is on half a million people. The largest in the world, half a million. That's nothing. And there's what, some billion people in this world. There's 300 million Americans alone. I mean, I think in the next, in the next five to 10 years, we're gonna have a lot of people that are gonna be in the world. We're gonna have a lot of people that are gonna be in the world. We're gonna have a lot of people that are gonna be in the world. I mean, I think in the next, you know, you know, I think in the next two, three years, you can easily beat that, you know. And in doing that, you're not just building a genome database, you also integrate with non-genetic pieces of information, which then you can use to better serve customers, which is really important. Because then once you have a database that you can take all these variables together, you can actually start seeing, you know, wait a second, you know, wow, like, you know, the power of a true kind of real-time, you know, medical platform. Because what do you really need to do to build the true precision medicine kind of frontier is you need very large biobanks. What I mean by this is you need, let's say, you know, a hundred million people where all the hundred million people have their genome sequenced and they have their blood, they have their full body MRIs done, they have all their wearables, right? And there's this massive database and these people are longitudinally tracked, okay? And then you can start building models to see. Kian: Basically flagging molecular abnormalities for the individual prior to any obvious phenotypic signal. In other words, instead of coughing and say, oh, you're sick, or instead of seeing a tumor, I can actually start molecularly flagging it far before someone could take some sort of qualitative metric from the customer. That is true precision medicine. And you already see this today, actually, with something like coming out of Eight Sleep, for example. Mateo is an investor, actually, in Nucleus. And Eight Sleep is interesting because sometimes your heart rate shoots up. You say, I feel fine, it's a little weird. Then you're sick two days later. So already you can start seeing the beginning of these models that are basically predicting far before it ever happened, different diseases. And then that is truly a more of a preventative-based model. Then once you know, obviously, what is either oncoming, you can then basically take the steps to prevent it, circumvent it, get rid of the tumor, whatever it is. And so I like to think of the future as medicine. I steal this from Dr. Leroy Hood. He's the founder of the Systems Institute of Biology. He's brilliant. And he described a medical system that's something called P4 medicine. He says the future of medicine is predictive. So we can actually predict disease risk from birth, which is really through your whole genome. It's preventative. So it's all about delaying the onset of or progression of disease. It's something called participatory. In other words, basically, the consumer is in charge of their health, not the medical establishment. The consumer is in charge of their health. And lastly, it's personalized. And when he says personalized, he means it has the entirety of your health data. So participatory, predictive. Now I'm getting lost in the P's. Predictive, personalized. I lost the P's. People remember already. People remember. I said four of them, whatever. OK, so you take these four P's. That's the kind of medical system that you want to build. And so that is always my model, which is like, how do we build toward this P4 medical system? And I think then again, if you think about what is actually those four P's, whole genome sits at the foundation. So that's why we start there. Kyriakos: I haven't asked you the most important question. Kian: Ask it. Kyriakos: What's your deadlift? Kian: What's my what? Kyriakos: What's your deadlift? Kian: 225. I weigh 130. Kyriakos: Kgs or? Kian: No, no, pounds. 225 pounds. I weigh 130. Kyriakos: We need to work out together, man. OK, how much do you have? How much do you have left? Kian: My record is 220 kgs, but now I'm more of a 180, 190 kgs. So how much do you have left? My gym is outside here, so we should. Kyriakos: OK, so maybe after this podcast, we start deadlifting? What do you say? Kian: Yeah, sure. You know, you're all about activity. You're all about activity. Terra's all about activity. Kyriakos: Of course. So we've got to basically, we've been chatting. Now it's time to work. Kian: Well, that's been fun. Awesome conversation. Kyriakos: Awesome. And thanks so much for being here. Kian: Thank you.