Koray Kavukcuoglu on frontier models, coding agents, and building AGI

Logan Kilpatrick (0:00)

There's always a lot of discussion about is there a test for AGI? There's no test for AGI. I don't think anyone has a test that they can say, okay, if you get this much on this test, that means you are at AGI. And I don't think that is— - If you do have that benchmark, send it to us, please, because we want to— we'll use it, we'll run our models on it.

Hey, everyone, welcome back to Release Notes. My name is Logan Kilpatrick. I'm on the Google DeepMind team. Today we're joined by Koray Kavukcuoglu. Koray, I'm super excited for this conversation. We sat down probably three or four months ago, and so I'm excited to catch up, reflecting on a lot of the progress that's been made over the last few months, looking into the future, Gemini 4 on the horizon. The third iteration of the 3.5, post-3.5 series, lots of progress in literally only three weeks. We launched 3.5 at I/O, 3.6, and then three weeks later landed 3.7. Reception has been super positive. Congrats to you and the team. Yeah, it's been positive. Do you want to— I don't know if there's anything you want to say about what made that model. We teased a little bit of architectural innovation or something like that, which I'm not sure we'll spill the beans on, but— - Not really. - Yeah. - Going from the initial 3 launch, my reflection is we learned a lot in terms of understanding what it means to do coding and not just coding, right? Like what it means to do software engineering, what it means to work with tools or work with the functions that people use every day. Basically, turn this whole thing into an agent, from a model to an agent. And that transition, I think we were walking around it, and that was the thing that we wanted to directly tackle. And of course, software engineering is the most critical domain and environment that you want your systems to be successful at, because it's at the root of many different things that you can do. During that time, we learned a lot in terms of how to train a model, how to train an agent that can actually code with you. And after that, I think the steps have started becoming faster. And in any research project, there are many parallel tracks that is going on at the same time too.

So, what we are trying to do right now is combine all these learnings, of course, add on top of them, understand, what it means to do agentic actions and agentic workflows better together with new architectural improvements, together with new ideas that we have been working on for a while. Many of these things that we have done in 3.6, 3.7 go back like a year or more, and then those start paying off and you converge them into the model. And it's great to see the quality impact that we got from that. We were very excited, in the run-up to 3.7, when we were doing 3.6, of course, we could see we could see what 3.7 could be or what the next step could be. And then it came together. And internally we started enjoying that model a lot. So that's the parallel track effect that you are going, that you are seeing. - There's a lot of parallel tracks. I don't know if we've done this in the past, but a few weeks ago we publicly said that Gemini 4, we're working on it. It's the most ambitious pre-training run that we've done so far, which is really exciting. People seem excited by it. I think folks are excited internally. Lots of research going into this.

Yeah, I'm curious, this has historically been one of our strengths and the team, seems incredible and they've always done a great job. And so I don't know if there's anything top of mind or anything more you want to say about that. Yes, it's the most ambitious run, correct.

And yes, so far, touch wood, it's going well. I am very excited. The team is very excited. I look at these as step by step, right? So, far, everything is looking good. We are excited. But it's all about realizing that potential until we get to a moment that we are actually putting the model in front of users, first internally, then externally. I'm always in a very cautiously optimistic state. - I think maybe to tee you up for a very specific question there's a meme about whether or not we care about being at the frontier. I see you in meetings all the time and know what your point of view is but what's your point of view as far as whether or not, you know, you think it's important for us as Google DeepMind and as a team to trying to be at the frontier? -