What Jeff Dean thinks about semiconductors

@jeff-dean · 22 positions · On ppll ↗

Chief Scientist at Google DeepMind and Google Research, at Google since 1999, where he co-created MapReduce, Bigtable, TensorFlow and the TPU.

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Only Jeff Dean on semiconductors. See everyone on semiconductors

2 dated positions, 2026, in their own words. Our reading of what Jeff Dean has said — not written or endorsed by them.

2 positions so far — this page is not yet offered to search engines.

1. 30 Jul 2026

   Our readingInference, not training, is now the constraint, and specialized low-energy hardware will beat general-purpose GPUs and TPUs on latency.

   energy

   Their wordsYeah, I mean it's a little different, but I think uh you're going to see more and more uh uh high performance and um low energy uh inference hardware systems because I think everyone is now realizing that inference is the key to making you know these agent-based systems be available to more and more people and that latency is really important and that specialization of the hardware is a really key way you can make uh things that are more energy efficient and lower latency than more general purpose uh computational devices like say GPUs or TPUs

   ↗Jeff Dean: The 1% Rule for Building in AIyoutube.com 2nd of 22 in this recording

3. 30 Jul 2026

   Our readingA chip that can do nothing but low-precision dense linear algebra is enough for machine learning, even though it cannot run Chrome.

   Their wordsAnd um if you build a specialized chip for low precision dense linear algebra and can't do anything else that turns out to be really useful for machine learning inference uh even though it can't run Chrome or Word or whatever.

   ↗Jeff Dean: The 1% Rule for Building in AIyoutube.com 4th of 22 in this recording