Google DeepMind

“I think there's quite a lot of LLM research and related to be done for, I mean, five, 10 years at least.”

“Depending how you attack the problem, it's definitely not at that end. And I think even because it's so hard to have a perfect reward when you interleave language, I think by, even by accident, the field will move forward as we get to discover these more gener…”

“So then you, of course, are absorbing all the knowledge on the internet and then sharpening those models around being, following instructions, being aligned with humans, but you still have this Probability distribution that will assign non-zero probability to …”

“Probably we can, and we might see more and more bootstrapping from Gemini and these models to then a specific solution that, that the model is going to be throw away, except for, you know, maybe cracking protein folding or, you know, figuring out nuclear fusio…”

“Historically, if you look at AlphaGo, which actually followed quite closely the recipe of you pre-train your model on all human data, you then use RL to make it better, and then you do some search at inference time, the compute there was very skewed for the mi…”

“The contrarian view would be, I'm not sure it matters that, that we achieved AGI. I think it might not look like Hey, like, it's gonna be exactly like the cognitive task we can do, and then we reach parity. It's gonna be a distribution of things that these mod…”

“I think to me, it seems like a feature not a bug that we do have a bit of a hybrid mode perhaps going into the future and research will be driven like this.”

“That directionality of taking a generalist model and doing something by fine tuning it, there's going to be a loopback as well, right? Then you're going to do something amazing, let's say in math, right? We recently did that. And then while the data or as a re…”

“Shane, I just had a discussion with him about AGI timelines recently. And I mean, in 2009, he predicted it's 2028.”

“One way I kind of characterize general models is they are, I mean, The level of performance is irrelevant, but they're like, 20% good at everything, ok? So they, that's the level of performance they reach, but it's general, which, I mean, it's powerful, so you…”

“And honestly, it's gonna be also impossible to get agreement, so it's gonna be quite, Cloud of moments that people might feel it has happened now, but it doesn't matter because the models might be used for amazing things and products and research itself, right…”

“So to me, that balance feels correct, like some on pre-training, and here we, we're trying to learn every task. So certainly that's going to be, you know, let's say it can be as high as 50%, not as high as over 90 like today. And then the rest mostly on reinfo…”

“To accelerate that, that sort of progress, you want to start sort of really exploring what's the reasoning the model has, and by making it more redundant, more logical, by iterating more on these kind of ideas, you could imagine generating a very small program…”

“And to be honest with you know, like kind of we, at the moment we can't rival at all with someone like Terry Tao. We, I think we demonstrated that what we've demonstrated is that we can learn general mathematics almost from scratch and arrive at kind of an imp…”

“The way alpha proof currency operates there is that it discovers its own proofs, and when they are valid, it learns from them and develop its own style which has been commented upon as looking, yeah, quite, quite alien.”

“Maybe the main thing that Alphaproof doesn't do is theory building. It doesn't invent its own theories.”

“So the IMO problems have come in four categories. So there's algebra number theory, combinatrix, and geometry. The two that it's strongest at are algebra and number theory. It's relatively weaker at combinatrix, although it can do quite good at some IMO combin…”

“Alphaproof had this really amazing results of solving four of the six problems this year.”

“To prove harder problems, you start to need to be able to introduce these new kind of mathematical objects to decompose the problems or problems. And we see that already happening for the IMO at a, you know, small scale.”

“The advantage of that is that once kind of the proof is complete then you know, the machine would give you a signal back to say, yes, your proof is correct or not. And so we could search for kind of correct proofs. Once we find a correct proof, we can learn fr…”

“One of the ways in which it navigates this massive search space is via an idea that we came up with, which we call test time RL. So this is an idea where, like, let's say you're confronted with a problem that you don't know how to solve. And you know, you can …”

“Another option you can take is actually we have already worked on this problem for a really long time. Here is a very strong initial solution that we can provide to the system and you can start from here. And that's what we did for the application to discoveri…”

“FunSearch, which was an LLM-based agent, which for the first time, by searching in the space of programs, showed that you can come up with completely new solutions, like, and this, and made the first scientific discovery from an LLM.”

“We have started a trusted tester program where we have asked people to submit proposals, and what we intend to do with that program is to figure out what are the right ways in which people can really leverage alpha evolved.”

“It's hugely valuable that the artifact you get out of Alpha Evolve is a piece of code, and then you deploy that piece of code. And so before you do that experts, engineers who have worked on that system can visually inspect that piece of code, understand it, a…”

“And kind of the first breakthrough we had in this space was in twenty-twenty-two when we released a system called Alpha Tensor. And so that was a system that was an AI system using reinforcement learning. That for a very specific, but a fundamental computation…”

“The problems we chose to apply Alpha Evolve to in the first instance both on the scientific side and the practical side, We deliberately chose problems which have been worked on for a very long time by the very best people. So on the, you know, on the scientif…”

“And we have shown that this AI co-scientist which we have used for hypothesis generation, it basically uses a multi-agent sort of setup and where LLMs themselves are able to sort of figure out that certain hypotheses are better in terms of novelty and signific…”

“As you sort of go to larger sizes, the space is so huge. The constructions are not sort of something which is very natural. These are very involved and intricate, intricate, intricate sort of constructions that would be very hard to discover by chance. So it's…”

“Working with Jordan Ellenberg in the first, in the earlier version of Alpha Evolve, when you were working on the cap set problem, the programs that it discovered had very interesting symmetries that that mathematicians did not know about. And so, so not only t…”