00:35:33 · Josh Meier
[00:35:33] S0: Yeah, it's, I'm very excited to see how it lands. If we look at our last release with Chai two, people almost didn't believe it. They were like, how is this possible? And there was like even skepticism and then yeah, people started to, it started to soak in, people realized, okay, yeah, this is, I guess this is physically possible and now someone has achieved it. And then, you know, companies started using it, right? You have the Lilly announcement, for example, and people are like, okay, I guess, I guess this is the new way, that, that molecules might be made. With three, I think we're at this point now where people think of, AI and drug discovery as as sometimes being a point solution. Like, I'm able to get that starting point, but I still need to do bunch of work to make the molecules better. And with Chai three, we've taken a a massive leap forward, not just in the success rates, but in quality of the molecules that are coming out, and I think it's going to be another one of these like, oh wow moments of like, oh wow, I guess like it doesn't just stop at what we saw before, these molecules can keep getting better, and I think we might even get to a place where people almost like, they're just like suspend disbelief, right, where it's like things are moving so quickly in this space. It feels like any time people have like a critique or a question about the models in this space, it just gets solved a couple months later with the next model release. So at some point, I think people, I hope it doesn't get too far where people's expectations just get too high because of the progress is being made so far, but actually that might be a good thing because it means people are starting to think about what problems... Okay, we want people to think about what problems they can solve with Chai three. But it's actually pretty valuable if pharma starts thinking about what are they going to solve with Chai four and Chai five, because the ideas can start percolating, and then once the models are here, then we can get really fast adoption with those technologies. So I think it's almost great for people to be following that curve and to start to even now start extrapolate where things might go from here.
00:37:11 · Sachin, Josh Meier, Adam Miller
[00:37:11] S1: I think what's so exciting about this is our whole mission of this channel is based around tech optimism. And I think when we think about what's happening in LLM land, there is real layoffs happening now and there's real kind of a turning point in society whether or not we want to keep continuing this progress, right? Like there's no matter what side of that equation you sit on, there is like a real conversation going on. But with what you guys are doing, it's so objectively good for the world that it's like, let's throw as much compute at this as possible because the world could look profoundly different. Maybe there's a world in which anyone with any disease can design the perfect drug specifically for them and have it in their hands really, really quickly. Like that's just such a objectively amazing world. [00:37:51] S0: This is what I tell our cloud providers whenever we can't get compute. You should move this off of some entertainment app and move it over to actually making medicines that can help cure and treat diseases. [00:38:02] S2: Do you think there will still be skeptics into the future? Like, is there going to be an element of storytelling here where you need to speak to regulators, consumers, different sort of health providers, and really, like, sort of guide them along the journey of how this all works, or do you think the results are simply just gonna speak to themself? Because if all of this is successful, it is a complete shift change for humanity.
00:38:02 · Adam Miller, Josh Meier
[00:38:02] S2: Do you think there will still be skeptics into the future? Like, is there going to be an element of storytelling here where you need to speak to regulators, consumers, different sort of health providers, and really, like, sort of guide them along the journey of how this all works, or do you think the results are simply just gonna speak to themself? Because if all of this is successful, it is a complete shift change for humanity. [00:38:23] S0: I think it will be the latter. I think people will see the results, and then they'll be convinced. The same thing happened in the rest of AI. You don't really have skeptics of chat GPT. It's like the thing works. Try it out for yourself. And the thing with drug discovery is it is, you know, it's not as simple as a chat GPT and looking at the answer that comes out. You really need to do some lab testing to understand whether these molecules work, but those experiments are being done, and, and turns out it doesn't take that long, right, maybe two weeks to see if the thing is working. So I I think we're gonna move away from this world of skepticism towards one of more, okay, how can I use this to solve my problem? And that's that's a really exciting place to be.
00:38:23 · Josh Meier, Adam Miller
[00:38:23] S0: I think it will be the latter. I think people will see the results, and then they'll be convinced. The same thing happened in the rest of AI. You don't really have skeptics of chat GPT. It's like the thing works. Try it out for yourself. And the thing with drug discovery is it is, you know, it's not as simple as a chat GPT and looking at the answer that comes out. You really need to do some lab testing to understand whether these molecules work, but those experiments are being done, and, and turns out it doesn't take that long, right, maybe two weeks to see if the thing is working. So I I think we're gonna move away from this world of skepticism towards one of more, okay, how can I use this to solve my problem? And that's that's a really exciting place to be. [00:38:58] S2: Do you think philosophically there might be skeptics about curing everything almost on demand? Like, for example, with ChatGPT, you've still got a large percentage of the population that are just plainly anti AI. They think it might erode our cognitive abilities. They think it's going to hurt labor markets, etc. Do you think there'll be these anti health skeptics eventually in the future?
00:38:58 · Adam Miller, Josh Meier, Sachin
[00:38:58] S2: Do you think philosophically there might be skeptics about curing everything almost on demand? Like, for example, with ChatGPT, you've still got a large percentage of the population that are just plainly anti AI. They think it might erode our cognitive abilities. They think it's going to hurt labor markets, etc. Do you think there'll be these anti health skeptics eventually in the future? [00:39:21] S0: I think it's a bit different in our space as well. We're working on generating a molecule. There's a very clear objective function of what you want. I want a molecule that does X, Y, Z. We can measure that in the lab, and it's all about finding a molecule that does that. So if we can do it with AI, or we can do it with yeast, or, you know, it almost doesn't really matter to the end user. People often ask us, like, who our competitors are and actually tell them yeast, right? Like that is what we're going up against. People have been doing something in this field for a long time. It actually works like, you know, it's been tuned, to work somewhat well, and that's the bar that we need to overcome. And now we're past that, so it's all about like, now the competitor is Chai two, or we're making Chai three, right? And with Chai four, it'll be Chai three, but it's a very unique space to work in where the progress that we can create here can translate into value so rapidly. [00:40:08] S1: I'm really curious on how you spend your day to day now. Like, are you actually in the weeds training the models or are you doing more on the business side?
00:40:08 · Sachin, Josh Meier, Adam Miller
[00:40:08] S1: I'm really curious on how you spend your day to day now. Like, are you actually in the weeds training the models or are you doing more on the business side? [00:40:16] S0: I mean, it changes every day, right? It could be that we need to go in, get the next foundation model going, and there's some blocker around that. It could be pouring over lab data, figuring out like, what does this mean about the models? How do we make them better? It could be getting a deployment up and running with a customer. Those are always some of my favorite moments as well, and actually seeing this translate into real medicines. I've been working on this research for most of my career, and to finally be at a point where it's not just, you know, core results on benchmarks, but actually we're making molecules that are being pushed forward in real pipelines and real drug companies, is pretty incredible. [00:40:52] S2: Awesome. Well, I mean, this whole mission is, incredibly exciting and I think like, you know, we very rarely get to meet companies, that we think that could actually change the world, and maybe this is changing the world in terms of the biggest problem that we have, in terms of sickness and illness. So it's been a really exciting day. [00:41:09] S1: Yeah, extremely inspired and everyone we've met here has also been so genuine and thoughtful. It's a very different energy than some of the other more application layer companies we go into or some of the other ones we explore. So, yeah, it feels special and thanks for having us here.