15 korrents from this recording
Every claim below is a statement made in this recording, quoted word for word and linked to the second it was said, so you can hear it rather than take our word for it. The wording comes from the transcript published alongside the recording; the sentence above each quote is our reading of the claim, not their wording.
Our reading
Curing, preventing or managing all disease by the end of the century is now too conservative a goal.
Their wordsBut still, I thought that by the end of the century was a stretch. Now, I think it's like uh too conservative.
Their wordsI 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 scientist hands quicker
Their wordsI think in a lot of ways the data is actually even more of a constraint and um 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
Their wordsit's not just like there's some factory somewhere that you can pay to produce the the data like you actually need to invent new novel scientific approaches
Their wordsI 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 on building out these efforts.
Their wordsAnd again, I mean, the the theory isn't that we're going to cure the diseases. We're not. um it's that we want to help accelerate the pace of progress for the whole scientific field.
Their wordsI mean, I'm optimistic it'll be sooner. I mean, I think that the thing that's complicated is that it's a dynamic system, right? So, if you fix something, there will obviously be future things that you need to work on.
Their wordsrather than studying the specific diseases we think that by trying to understand inflammation more broadly that will make it so that other companies that can then use these tools can work on specific therapies.
Their wordsWe don't believe in this like very centralized future where there should be a small number of institutions that um that basically are are advancing all this stuff. Our vision is not that there's going to be like some central super intelligence that solves all of science.
Their wordsI think like people are really important and I think we'll be more important in the future and giving people more tools to be more productive is going to be like a critical part of any kind of positive future
Their wordsthat's how progress has always been made historically, right? It's not um through centralization. It's through empowering individuals to try things that are somewhat out of the mainstream that other people didn't think were good ideas
Our reading
Social media and open-source AI come from the same conviction: hand the technology to individuals.
Their wordsI mean to some degree it's like why you create something like social media, right? To give people a voice.
Our reading
Open-sourcing biology models is right in principle but has to be balanced against biosafety.
Their wordsIn terms of science, I think it really makes sense and we're deeply committed to open source. Um, there are obviously interesting considerations on this that are important too because there's a lot of considerations around biosafety and things like that that we're going to need to balance and think through how to how to handle.
Our reading
Progress in AI takes a very strong dozen or two researchers, not hundreds or thousands of them.
Their wordsin order to make progress in AI you don't need like many many hundreds of AI researchers um or thousands or anything like that I think you can really make progress with um you know a very strong group of a dozen or a couple dozen people.
Their wordswhen you have an exponentially growing curve, I think the way that an exponential curve feels is it's growing so quickly that the the kind of emotional feeling is it can't possibly keep going, right?