The Decade of May 15-22, 2025: Google's 50X AI Growth & Transformation with Logan Kilpatrick

**Nathan Labenz** (0:00)
Hello, and welcome back to The Cognitive Revolution. Today's guest, Logan Kilpatrick, needs no introduction. This is his fifth appearance on the show, and his tireless work in support of AI application developers, previously at OpenAI and now for the last year in change at Google, is legendary. In this conversation, with the benefit of at least a little time to process, we're looking back and digesting the overwhelming volume of major new AI models and products that Google and others have recently released.
Logan describes his personal experience at Google as their AI usage has grown some 50x, from 10 trillion tokens per month just a year ago after he started, to 500 trillion tokens per month today, which is notably more than 50,000 tokens per month for every person living on planet Earth. Logan also shares his perspective on Google's incredible organizational transformation, from what once was described as a sleeping giant, to now an indisputable top-tier AI powerhouse, with assets headlined by the strongest overall compute infrastructure of any company, top-tier and Pareto frontier models including Gemini 2.5 Pro, highly original and viral products like NotebookLM, game-changing applications in medicine and science that are starting to ship to trusted users, and what I have always and still consider to be the deepest bench of AI research talent and the most diversified, well-rounded research agenda to be found anywhere in the world. He also offers thoughtful analysis on whether we'll continue to see convergence among leading AI companies or more divergence as the low-hanging fruit gets picked, why he believes that startups still have unprecedented opportunities despite Big Tech's advantages, the implications of Anthropic cutting off Windsurf after they partnered with OpenAI, how the blinding speed of Google's latest diffusion language model could bring about yet another revolution in software, and why despite all the AI capabilities advances he's seen and helped to popularize, he's still betting that humans will continue to matter and taking a relationship-centric approach to his work. Speaking of relationships, perhaps the highest alpha part of this episode was when I asked Logan for advice for those who want to break into the early access programs and other support structures that he and people in similar positions can provide. I won't spoil his response here, but it did include his personal email and an invitation to reach out. As always, if you're finding value in the show, we'd appreciate it if you'd share it with friends or leave us a review. We always welcome your feedback too either via our website, cognitiverevolution.ai, or by DMing me on your favorite social network. With that, I hope you once again enjoy hearing from Logan Kilpatrick of Google DeepMind. Logan Kilpatrick, everybody knows who you are. Welcome back to The Cognitive Revolution.

**Logan Kilpatrick** (2:37)
Thank you, Nathan. This is the world record for the most number of times. I feel like actually you should just make me an independent reoccurring segment on some regular cadence because I feel like we get to do this a lot and it's wonderful to be back.

**Nathan Labenz** (2:50)
It's only your calendar that would prevent that from happening. So be careful what you wish for. So we were joking about titling this podcast the decade of the week of May 15 to May 22, 2025 Holy moly, we've got just an absolute avalanche. I've been kind of saying for a long time, my grip on like all AI news is slipping. And with this moment, I think it's officially slipped for everybody. We've come a real long way since GPT-4 and a ton of stuff is happening. Kind of want to run it down, but I also realize at this point we can't even be comprehensive. So I also kind of want to take some strategic opportunities to zoom out a little bit and just get your bigger picture perspective on some things. First one in that vein is over the last however many months, we've seen like several waves of leading AI companies launching very similar things in pretty short periods of time. This has happened with reasoning models. Most recently, it has happened again with the coding agents. And on a feature level, we're also seeing quite a bit of like connect into your Gmail, connect into your Google Docs, different kind of context retrieval type things. Some of that's obvious, but some of it is like pretty core research driven, right? Like getting the models to reason. How do you understand why the different leading companies seem to have such a similar development trajectory and like also launch timelines?

**Logan Kilpatrick** (4:17)
Yeah, that's a great question. I think there's a couple of dimensions to this. One, I think like on the research side, I think there's like true innovations that when people go out and talk about them, but it becomes clear in hindsight why something should be done. And I think like maybe like reasoning is like kind of that story. Obviously, DeepMind has been working on that reasoning stuff for a long time. I think it was like some of the particular techniques just became clear that let's make this level of art of magnitude of investment and things end up working out pretty well. And then you bake in all the other stuff that we had been trying that was sort of independent and different and you start to see some really interesting things. So I think some of this is people like the path. And this is what's awesome about about an ecosystem is like other people light a path. You get to benefit from the path that they've lit and then you go in and sort of, you know, can bake in those innovations into what you're doing, plus benefit from the bets that you were making that were sort of independent of that. So I think that's excited on the research side. I think on the product side, I think there's a lot of people, AI is the most competitive, both of the model and of the product side, is the most competitive ecosystem in the entire world right now. There is not a more competitive ecosystem with the amount of money, talent, intellectual capital, speed of execution, etc., etc., than there is in this AI ecosystem right now. So I think there's just a lot of competitive people who are actually really good at what they do and they don't want to be pushed behind by their competitors. And there's this feeling that you have to like stay on par with what everyone else is doing. And that actually ends up being like, I feel that tension is somebody who builds products in the AI ecosystem, which is there's this tension between like doing what you think the long term future is versus like not trying to look like you're behind in the present moment. And like finding that balance point between like the long term bets that are distinct, that are actually going to give you a differentiated perspective over time.