Q&A with Google Chief AI Scientist Jeff Dean about the evolution of Google Search, TPUs, coding agents, balancing model efficiency and performance, and more
From rewriting Google's search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs …
Thanks for having me on the @latentspacepod, @swyx and @FanaHOVA! I enjoyed our discussion! Site with summary: https://latent.space/... Video: https://www.youtube.com/...
the jeff dean pod is doing very well, grateful for all the positive shoutouts from u guys 🙇♂️ some fun lore: we're trying to learn the youtube game so everything is a/b tested. allen did a slop @NanoBanana thumbnail and i made 2 human clear ones, higher effort, more relevant. [i…
excited to follow up our Gemini Deep Think coverage of @yitayml and now @JeffDean, and in my other capacity, host @_philschmid and other fantastic @GoogleDeepMind colleagues at AIE Europe! my favorite part of the Jeff conversation was how he gamely handled everything I could [ima…
“Benchmarks, particularly external ones that are publicly available, have their utility, but they often have a lifespan of utility... I like to think the best kinds of benchmarks are ones where the initial scores are like 10% to 20% or 30% and then you can sort of work on [video]
From rewriting Google's search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind…
Deepseek mentioned [18:20], DeepseekOCR. One mentioned passingly in a larger point about how some modalities are more imp than others like vision which can encode both text and audio. So expected Jeff didnt address the whale specifically