“How far they are from AI or AGI, I think that's almost beside the point. I think the really, really interesting point is where we can characterize these systems as reliable enough, do we find useful things for them to do? I think we need to be much more utilitarian about it. We can just build useful systems. In fact, I think the whole industry is thinking a lot about how do we build useful systems that matter for people doing software development, that matter for people doing writing, that expand the nature of the problems we solve, and then we'll see if we end up with AGI, but we will certainly end up with useful systems.”
AlphaFold's software became science's surprising backbone
“The real shock to me is those weights that we train, that system, that piece of computer software has been so incredibly practically important to scientists working in this field to this day that the actual bit of software is used that makes this difference in all these different application areas, all this different type of science published on top of this as a black box computer program, and the extent to which that has entered into scientific practice has been really, I think, beyond my imagination.”
“I used to work in simulation, and simulation is that I will write down the rules for how all the little pieces do their little thing locally, and then I'll put it all, mash it together, and turn a big crank, and then I will get it. But we don't even have a parts list for the cell. We have all these effects that I think are not going to give us a classical simulation simulated cell. I think what we're going to do is build really useful systems that draw information from AlphaFold, that draw information from the literature, that draw information from the genome and use that to say really useful things about biology that matter.”
“I will say dropping out was a very lucky thing for me. I was doing the wrong thing. I didn't really want to. And so I just left. And because I left, I actually fell into this computational biology group that was doing amazing work on custom computer chips to simulate proteins. And then I go back and I do my PhD now in chemistry by another set of accidents. And I didn't have those great computers. So why not get into AI? I have to be the first person to get into AI because of a lack of computational capability rather than an abundance.”
AlphaFold accidentally became a protein-design tool
“Wasn't the intention of them to see how they stick together. In fact, that was an early surprise from Twitter, where two different people said, you know, if you want to know if two proteins stick together, yeah, we were busy making a multi-protein, like properly done system. They said, well, just take those two proteins and put some random amino acids in the middle and see if they stick together that way. And that was the best system in the world for seeing if proteins stick together.”
Diffusion architecture introduced new hallucination risks
“In AlphaFold 3, we went to diffusion where you basically say, here's a blurry image of the protein. I kind of took all of the protein and added some noise, some error, like you looked at it in the wrong prescription glasses, and then guessed the right answer, and you have it constantly refine. The upside is that it made it really, really easy to kind of handle this wide universe of things that we study. The downside is that it led to a higher rate of hallucination, of weird stuff appearing, and so then we needed to handle that in different ways.”
Sperm-egg fertilization protein discovered via AlphaFold screen
“There was another really nice story that people were trying to understand human fertilization, when an egg and a sperm meet and come together and eventually fuse. They said, well, there are only 2000 proteins that we know that are on the outside of sperm. Why don't we just try all of them and see which ones stick to the proteins that we know are on egg? But AlphaFold is pretty fast, and they had some computers available, so they tried all of them, and then they both came out with this one protein, TMIM something, I can't remember the number.”
“My original plan was I'll sleep through it and a phone call wakes me up, then I've got the Nobel, but I couldn't sleep. So by about 10.30, I said, oh, well, I guess not this year. And I told my wife, and she goes, no, no, wait. And as like as she's telling me to wait, my phone lights up with a phone call from Sweden. And thankfully, it was not the world's meanest prank call.”
AlphaFold 3 dropped evolutionary data and got better
“AlphaFold 2 used evolutionary information in this exuberant way. At kind of every part of almost every block, it was saying, and here's the evolutionary information in case you need it. But a lot of what we studied in AlphaFold 3 that we knew we were moving toward didn't have evolutionary information. And so we decided to just take that out of most of the network, and otherwise emphasize the geometric information, the thing that really is always there. And that turned out to work exceedingly well, actually better than we expected.”
“I like to remind people that a protein structure costs about $100,000 and a drug costs about a billion, right? So they can tell you that it can't all be protein structure determination. I think it's really exceptional to see people trying to build on and take these ideas further and really find also a way in order to integrate it into application.”
Designed enzymes are already inside laundry detergent
“Although in fairness, actually, interestingly, on synthetically evolved enzymes, people are already using them. You know, there's a lot of washing powder that has designed proteins, which I find fascinating. I think one of the few applications of designed proteins and something people would recognize.”
