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HOME/PEOPLE/DAVID SILVER
// PERSON

David Silver

ROLE FOUNDER / EX-PRINCIPAL SCIENTISTAT INEFFABLE INTELLIGENCEMENTIONS 8LAST SEEN OCTOBER 13, 2026
// BIO

Ex-Google DeepMind Principal Scientist and founder of Ineffable Intelligence.

Discussed in
// RECENT MENTIONS
// SIGNALS
8 SIGNALS
01
mention·Training Data·OCTOBER 13, 2026

“you demonstrated for the world for the first time that superhuman in one domain machine intelligence was possible, and I think you were really the figure that inspired the entire current generation of of reinforcement learning.”

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02
mention·Training Data·OCTOBER 13, 2026

“we started with this kind of gray mush in our head... everything we learned, we we discovered it for ourselves and that's an incredible thing that no one has cracked yet in AI.”

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03
mention·Training Data·OCTOBER 13, 2026

“It took us 2 years to get to AlphaGo and beat Lee Sedol. When we got AlphaZero right... it took just a few hours.”

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04
mention·Training Data·OCTOBER 13, 2026

“I'm supportive of... the kind of direction that, that people like, um, you know, Demis and, and Dario and so forth are, are suggesting.”

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05
mention·Training Data·JULY 29, 2026

“Rich Sutton and David Silver have this paper, The Age of Experience... Reinforcement learning is not a particularly new approach, particularly new thing to do. So in some way, The Age of Experience I think always has been there.”

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06
funding·StrictlyVC·APRIL 28, 2026

“Ineffable Intelligence, a British startup founded a few months ago by ex-Google DeepMind Principal Scientist David Silver that aims to build AI systems that learn without human data using reinforcement learning, raised a $1.1 billion round at a $5.1 billion post-money valuation.”

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07
mention·StrictlyVC·APRIL 28, 2026

“A British startup founded a few months ago by ex-Google DeepMind Principal Scientist David Silver.”

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08
hire·StrictlyVC·APRIL 28, 2026

“ex-Google DeepMind Principal Scientist David Silver that aims to build AI systems that learn without human data using reinforcement learning”

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AI-extracted from podcast / newsletter / paper summaries. May contain errors.