Inside Google's Billion Dollar Bet To Win The AI Race | Logan Kilpatrick
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Is Google falling behind in the AI race?
I think we are like laser focused right now at the frontier.
What is the strategy behind Gemini 4’s massive pre‑training run?
We're seeing all these early signs of recursive self improvement.
How does Google decide between building its own models versus acquiring AI companies?
I think the other labs are seeing this as well.
What can we learn from China’s open‑source AI labs and their competitive threat?
And so I think it's like underscoring the value of like
Why does Google focus on the “frontier” and where does it choose to compete?
Today's conversation is with Logan Kilpatrick.
Will Google prioritize general intelligence or specialized AI products?
He's a member of the technical staff at Google DeepMind.
How does DeepMind’s genome research fuel the AI innovation flywheel?
In this conversation, we talk about the AI industry, the model lab wars, what's going on at Google?
Why are better benchmarks and the AI data economy critical for measuring progress?
Are they actually committed to the frontier? How are they investing capital internally? What are the specific products and the decision making that's going on inside of Google Deepmind? How are the AI efforts at some of the other labs actually affecting their decision making? And then how should you, as an individual, Think about benchmarking, coding agents, different types of bots, and many other aspects of the AI industry that everyone's talking about. Logan is somebody who has worked at a number of different companies in the industry. He's very well versed not only what Google's doing, but how the industry is developing. And I think you'll find this conversation very valuable. Here's my conversation with Logan Kilpatrick.
All right, Logan, everyone thinks that Google is behind an AI race. Uh, what do you think? What is your response to the critics who believe that uh Google maybe is not near where they should be?
Yeah, it's a good question. And I think it is uh I think my reflection of the last two and a half years is like I think it's a fair criticism, um, because people expect a lot of Google. This is what I try to remind myself. It's like, you know, it's not people trying to be rude saying that Google is behind. It's like Google's an incredible company, have such a storied legacy. Um, people expect high things of us. I think the tension point for us is you look at this portfolio of stuff that we're doing. We're actually talking off camera about this, everything from like, you know, genomics work to weather and science to, you know, new frontier models with Gemini Four to we just released a bunch of new audio models, um, et cetera, et cetera.
Like I I have this firm conviction that like Google and Deep Mind, we have the world's best portfolio of stuff. Um the tension is like the portfolio spikes in different ways. And sort of this is a a very natural thing. Um I don't think that's like an excuse to not be at the frontier. And so I think I think we are like laser focused right now at the frontier. We're seeing all these early signs of recursive self improvement. I think the other labs are seeing this as well. And so I think it's like underscoring the value of like being at the frontier. And so hopefully we'll see that with with Gemini four. But an immense amount of progress. And I think you've seen this with the Gemini uh three point five, three point six, three point seven, three point eight lineup of like in
Literally like three to four week increments, uh, sometimes less, sometimes a little bit more. We're seeing like very reasonable progress. And again, this is like the early signs of this recursive self-improvement loop. Um, so hopefully we'll see that sort of like translate over in the same way to Gemini 4. And it'll be our, it's our largest, most ambitious pre-training run so far. Um, so I think you'll you'll it'll it'll sort of get us back in in contention with. Some of the the Frontier laps.
Talk talk a little bit more about this like commitment to the frontier, right? I think that is one of the things that people have always wondered is um you can go after general intelligence, you can go after specialized workflows, you guys have a business to run, you get a lot of cash, but also you're making a lot of bets on, you know, this kind of being the future of the company. But I do think that when I speak to people at Google, maybe there's more of a commitment to the frontier than people realize kind of outside of the company.
Yeah. It it's part of why w I had this conversation with Korai and he was sort of like making this verbal commitment to the frontier.
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Chapters
8 chapters
1
Is Google falling behind in the AI race?
0:00–0:03
2
What is the strategy behind Gemini 4’s massive pre‑training run?
0:03–0:05
3
How does Google decide between building its own models versus acquiring AI companies?
0:05–0:07
4
What can we learn from China’s open‑source AI labs and their competitive threat?
0:07–0:10
5
Why does Google focus on the “frontier” and where does it choose to compete?
0:10–0:12
6
Will Google prioritize general intelligence or specialized AI products?
0:12–0:15
7
How does DeepMind’s genome research fuel the AI innovation flywheel?
0:15–0:19
8
Why are better benchmarks and the AI data economy critical for measuring progress?
0:19–54:55
Speakers
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