Jeff Dean
12 statements across 3 episodes · 6 bullish · 0 bearish · 3 people on the record · first statement Dec 31, 2025 by Andy Konwinski · said 25 times in 8 episodes since 2025 · across every show →
On the record as a speaker too: Jeff Dean's record, appearances and statements → this page counts the times other people say the name.
Mentions by year
brought up most by Shawn Wang (8), Alessio Fanelli (5), Chris Lattner (1), Andy Konwinski (1)
tap a year for its mentions
2026 16 mentions in 3 episodes 5 per episode
2025 9 mentions in 5 episodes 2 per episode
- 2024 Year in Review: The Big Scaling Debate, the Four Wars of AI, Top Themes and the Rise of Agents
- [State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute
- Better Data is All You Need — Ari Morcos, Datology
- The Shape of Compute (Chris Lattner of Modular)
- DeepSeek V3, SGLang, and the state of Open Model Inference in 2025 (Quantization, MoEs, Pricing)
- every mention in 2025, scene by scene →
Everything said about Jeff Dean, oldest first
Dec 31, 2025 positive
Feb 12, 2026 positive
Dean: A one-page internal memo sparked the Gemini unification effort
“I actually wrote a one-page memo saying we were being stupid by fragmenting our resources. So in particular at the time we had you know efforts within Google research on and in the brain team in particular on large language models. We also had efforts on multi…”
Feb 12, 2026 bullish
Dean: Personalized models with full personal context will beat generic models
“A personalized model that knows you and knows all your state and is able to retrieve overall state you have access to that you opt into is going to be incredibly useful compared to a more generic model that doesn't have access to that. So like, can something a…”
Feb 12, 2026
Dean: Memorizing retrievable facts wastes model parameter space
“Having the model devote precious parameter space to remembering obscure facts that could be looked up is actually not the best use of that parameter space, right? Like you might prefer something that is more generally useful in more settings than this obscure …”
Feb 12, 2026
Dean: Google evaluates models against held-out internal benchmarks absent from training data
“So we have a bunch of held out internal benchmarks that we really look at where we know That wasn't represented in the training data at all. There are capabilities that we want the model to have that it doesn't have now, and then we can work on, you know, asse…”
Feb 12, 2026
Dean: AI benchmarks above 95% accuracy offer diminishing returns due to data leakage
“I think once it hits kind of 95% or something, you get very diminishing returns from really focusing on that benchmark because it's sort of, it's either the case that you've now achieved that capability or there's also the issue of leakage in public data or ve…”
Feb 12, 2026
Jeff Dean: Design systems to scale 5x to 10x, not 100x
“And I think a good design principle is you're going to want to design a system so that the most important characteristics could scale by like factors of five or 10, but probably not beyond that, because often what happens is if you design a system for X and so…”
Feb 12, 2026 bullish
Feb 12, 2026
Dean: AI model demand is non-stationary because increased capabilities expand user requests
“I mean, I think that's true if your distribution of what people are asking people the models to do is stationary, right? But I think what often happens is as the models become more capable, people ask them to do more, right?”
Feb 12, 2026 bullish
Jeff Dean: Low latency is critical as AI shifts to complex multi-token tasks
“Latency is actually a pretty important characteristic for these models, because we're gonna want Models to do much more complicated things that are going to involve, you know, generating many more tokens from when you ask the model to do something until it act…”
Feb 12, 2026 bullish