A nonprofit can put biological tools in more hands

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 17:04

   venture-backed companies as a way to have impact on the world. What was it like collecting data on Zebrafish or the span of the data or the wet lab work or just the scale? Like what makes this a better fit for this big nonprofit, you know, ecosystem effort versus a venture-backed company? Well, I think we just want to give tools to the whole scientific community. And I mean, like, so I think... order to have the biggest impact, I mean, part of it is just we're, I mean, it's not actually clear that we couldn't run it as a business if we wanted to. I just think that we'll have a bigger impact by getting this in more scientists' hands quicker by doing it as open source projects instead. So yeah, I mean, I think that that's kind of the approach, but I don't know. It's an interesting question. I'm not sure that, I mean, obviously you were doing it as a for-profit company

2. 18:00

   a bunch of the modeling before, then you run into certain issues. I mean, you have to raise a large amount of money in order to build the compute clusters. You know, I mean, it's, I think in a lot of ways, the data is actually even more of a constraint. And because if you look at like the scale of these models compared to language models, they're smaller, but they're smaller because the amount of data is less. In order to get the data, it's not just like there's some factory somewhere that you can pay to produce the data.

3. 18:28

   Like you actually need to invent new novel scientific approaches to be able to do the, you know, for example, the type of cellular engineering we're doing in New York or the types of devices in Chicago, which is why, you know, when we're talking about this concept of frontier biology and frontier AI, the frontier biology is you need to do real science to advance different biological methods in order to be able to observe the things that create the data that go into the model.

4. 18:53

   So it's not just like an off-the-shelf thing that you can create. Now, that's a pretty big effort. I don't know that there are like that many things like that that are done as as biotechs. I think it's just the scale of the ambition of what we're doing, the horizon over which we're committed to doing it. I think part of the theory is like if you're building tools that are this complicated, you kind of want to have a 10 to 15 year time horizon on building out these efforts.

5. 19:19

   And then the scale of capital required. I mean, I guess there's no rule that said that you couldn't do it as like an incredibly well-funded startup, but I think that this just made more sense. And then it also is simplifying strategically to not have to think about how you're going to make money with the different things. I mean, we just, we want to get the models in people's hands. We release them as open source. I think that that's like a very valuable thing to do.

6. 19:42

   And again, I mean, the theory isn't that we're going to cure the diseases. We're not. It's that we want to help accelerate the pace of progress for the whole scientific field. As the person least experienced with making money here, I would say that the sort of neutral nonprofit nature of our work. actually helps harness more people to enter this effort and to actually achieve the mission of understanding the totality of human biology and to cure, prevent, manage all diseases. You actually do need the entire academic biotech industry to come together and to work on this in a sort of unified way, in part because there's a lot of talent out there and it's not helpful to leave any talent, exclude any talent from the effort. And there's a super long tail of diseases.

7. 20:34

   There are the common ones, and even the common ones, I think if you unbundle heart disease, cancer, neurodegenerative diseases, even if you unbundle like dementia or depression, there are many, many, many subcategories that become more and more niche. And that's not even looking at the long, long tail of rare diseases. Those often get orphaned and don't get brought along when we're sort of looking at the most efficient way to impact the lives of many.

8. 21:04

   But if you sort of decentralize the effort and put the tools in many people's hands, you start getting people who are like, you know what? I am super interested in spinal mass muscular atrophy. And that's something I care deeply about. And if you put the tools in that person's hands, they're going to be able to make progress in a way if you had to focus your efforts and make big bets, you probably wouldn't because it's just a niche, individual, small group disease that actually will in turn, if we can understand that disease process, helps us unlock knowledge about a lot more about how the human body works.

9. 21:41

   Do you have any thoughts or predictions in terms of what disease areas this work will