Anthony Pompliano asks Logan Kilpatrick what to take away from Google DeepMind's large pre-training run for Gemini 4. Logan says it shows the company's commitment to the frontier, explaining that pre-training has long been a strength for DeepMind thanks to its talent, its TPU fleet and Google's infrastructure. He also shares how he thinks about competitors, including the Chinese model labs.
Pomp asks how to separate signal from noise in an industry that sometimes feels like the TMZ of tech. Logan explains how he filters the noise to stay focused on building better models, and why his biggest c...
What Anthony Pompliano said
Written from the verified transcript and checked against it. Every figure links to the moment it was said.
Anthony Pompliano interviewed Demis Hassabis about Google's Gemini 4 pre-training run and competitive landscape. Hassabis said the large pre-training run signals Google's commitment to the frontier, leveraging TPU fleet and data infrastructure as advantages. He acknowledged competitors like OpenAI, Anthropic, and Chinese labs, praising Chinese model labs for genuine frontier research despite constraints. Hassabis noted startups want open-weight models they can host and customize, citing Gemma for on-device models and potential US open-source efforts. On information overload, he advised filtering noise and being intentional, using the Hugging Face OpenAI situation as an example of signal amid noise. He discussed opportunity cost and his filtering mechanism for product opportunities, focusing on areas where Google's structural advantages like Workspace and Cloud create natural lift, exemplified by AR Studio's deep integrations.
Key takeaways
Gemini 4 pre-training run is a large order of magnitude investment, signaling Google's commitment to frontier AI.
Chinese model labs are doing actual frontier research, not just copying, and should not be discounted as competitors.
Google's filtering mechanism for products is to pursue opportunities with structural advantages like Workspace and Cloud.
With Gemini 4, you guys have talked about this large pre-training run that you're doing. What should we take away from that? Like, are there specific things that you can share in terms of what that's going to look like?
Yeah, I think the thing to take away from this is like the commitment to the frontier. Doing large pre-training runs is extremely expensive. It is like a large order of magnitude of investment. It's like a... I don't... I don't... the numbers are quite large.
Yeah, I actually don't even know what the numbers are off the top of my head, but I can do some of the math in my head and like it's a lot. And I think it's important... I think the other point of this actually is like pre-training has been a significant strength for DeepMind in the past. And so I think this is like one of the areas where I think we have like some of the best talent in the world. We have like actually this is like the infrastructure scale of Google is an advantage in this context. Like this TPU fleet is an advantage in this context. A bunch of the data infrastructure stuff we have is an advantage. And so I think the point of telling people about this pre-training run is to tell people that like it's not like we're rolling over and playing dead. Like we are pushing the frontier. Everybody's working as hard as humanly possible. We'll hopefully see a bunch of incredible results from this new pre-training run. And actually interestingly, like you do the model comparison today and like all of our, you know, I think this pre-training run will very specifically like get us to the category that we need to be at to be competitive with where our competitors are at. And so I think the proof will be in the pudding when we hopefully launch this model and customers get their hands on it. But I think that's the expectation and that's the hope right now.
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Pompliano, A. (2026, October 20). Inside Google's Massive Gemini 4 BET [Interview transcript]. Anthony Pompliano Clips. CEOInterviews.AI. https://ceointerviews.ai/interview/3102345/
MLA
Anthony Pompliano. "Inside Google's Massive Gemini 4 BET." Anthony Pompliano Clips, 20 Oct. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/3102345/.
BibTeX
@misc{pompliano2026_3102345,
author = {Anthony Pompliano},
title = {Inside Google's Massive Gemini 4 BET},
howpublished = {Interview transcript, Anthony Pompliano Clips. CEOInterviews.AI},
year = {2026},
month = {oct},
url = {https://ceointerviews.ai/interview/3102345/},
note = {Speaker-attributed transcript with timestamps}
}
