Sergey Brin
11 statements across 4 episodes · 5 bullish · 1 bearish · 4 people on the record · first statement Apr 20, 2024 by Kara Swisher · said 49 times in 24 episodes since 2022 · across every show →
On the record as a speaker too: Sergey Brin's record, appearances and statements → this page counts the times other people say the name.
Mentions by year
brought up most by Ranjan Roy (14), Alex Kantrowitz (13), Marissa Mayer (5), Kara Swisher (4), Aaron Levie (4), Gaurav Nemade (3), Sir Nick Clegg (2), Sridhar Ramaswamy (1)
tap a year for its mentions
2026 11 mentions in 6 episodes 2 per episode
- Is AI Killing Software? — With Bret Taylor, OpenAI's board chair and CEO of Sierra
- Is Google's Gemini Winning?, Thinking Machines Drama, Claude Cowork’s Potential
- Claude Code’s Shining Moment, ChatGPT for Healthcare, End Of Busywork?
- Kimi K3 & AI’s Price War, What’s Happening To Google?, OpenAI’s Partner Trouble
- Did Google Just Fall Behind Again?, WWDC Preview, Anthropic Files To Go Public
- Who’s Winning The AI Race? + Software’s Future — With Sridhar Ramaswamy
- every mention in 2026, scene by scene →
2025 23 mentions in 13 episodes 2 per episode
- OpenAI’s Windsurf Crash, Grok’s Wild Week, Replace Tim Cook? — With Aaron Levie
- OpenAI's Jony Ive Moment, Anthropic's Big New Model, Google In AI Mode
- Can We Trust Silicon Valley With Superintelligence? — With Nick Clegg
- $100 Million AI Engineers, Vending Machine Claude, Legend Of Soham
- Dwarkesh Patel: AI Continuous Improvement, Intelligence Explosion, Memory, Frontier Lab Competition
- Mass AI-Driven Unemployment, NVIDIA Surges, CEOs' AI Avatars Unleashed
- Sam Altman: How OpenAI Wins, ChatGPT’s Future, AI Buildout Logic, IPO in 2026?
- Google’s Best Week Ever, AI’s Rising Costs, Putin and Xi’s Immortality Quest
- 5 more episodes that year, every mention in 2025 →
2024 9 mentions in 2 episodes 5 per episode
2023 5 mentions in 2 episodes 3 per episode
2022 1 mention in 1 episode
Everything said about Sergey Brin, oldest first
Apr 20, 2024 negative
May 21, 2025 positive
Brin: Inference-time compute offsets 5,000x in training compute
“What they did with AlphaGo and AlphaZero, as you mentioned it showed, as I recall, something you would take 5000 times as much training to match what you were able to do with still a lot of training and the inference time compute that you were doing with Go.”
May 21, 2025 neutral
May 21, 2025 bullish
May 21, 2025 positive
May 21, 2025
Brin: I work daily on Gemini pre-training and post-training models
“I'm across the street you know, pretty much every day and they're just people who are working on the key Gemini text models, on the pre-training, on the post-training, mostly those I periodically delve into some of the multimodal work”
May 21, 2025 neutral
Brin: Humans Lack Capacity to Reason About Higher-Level Simulations
“I think that we're taking a very anthropocentric view, like when we say simulation in the sense that some kind of conscious being is running a simulation that we are then in, and that, that they have some kind of semblance of desire and consciousness that's si…”
May 21, 2025 bullish
May 21, 2025 neutral
Brin: Multiple entities will reach AGI quickly following the first breakthrough
“I guess I would suppose that one company or country or entity will reach AGI first. Now it is a little bit of a, you know, kind of a spectrum. It's not like a completely precise thing, so it's conceivable that there will be more than one roughly in that range …”
Jul 14, 2025 bullish
Levie: Google is not going to lose the AI coding battle
“This is a company that has A great operator in Sundar, an incredible, you know, AI innovator in, in Demis Jeff Dean, you know, deep on research and science, and then now this kind of hardcore founder in Sergei, like this is not a company that is going to lose …”
Jul 23, 2025 neutral
Sergey Brin believes future AI progress will be primarily algorithmic
“Just to go back to a conversation that I had a couple of weeks ago, or now month plus with Sergey Brin, where he said he thinks that the improvement is going to largely be algorithmic. Of these models, meaning not by adding more GPUs and data by like actually …”