DeepMind, every mention

11 scenes · ← back to DeepMind

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every year anyone Sonal Chokshi 3Matt Clifford 3Cameron Schuler 3Anjney Midha 3Murray Shanahan 2Michael Copeland 1Marc Andreessen 1Frank Chen 1Balaji Srinivasan 1

Verbatim, from the transcripts: the passages where DeepMind comes up

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Safety in Numbers: Keeping AI Open Dec 28, 2023 · 3 mentions

The Network State with Balaji Srinivasan Nov 16, 2022 · 1 mention

a16z Podcast | Revenge of the Algorithms (Over Data)... Go! No? Jan 2, 2019 · 2 mentions

  • ▶ 0:15 Sonal Chokshi Just to give people some quick context, you don't have to have heard our previous podcast on AlphaGo, but when AlphaGo, the algorithm produced by DeepMind, beat the world champ in Korea in playing 2 times in the scene

a16z Podcast | Machine Intelligence, from University to Industry Jan 2, 2019 · 3 mentions

  • ▶ 1:41 Cameron Schuler So, when DeepMind got bought, half the people there were actually Canadian-trained, and roughly 20 or 25% were our students. 3 times in the scene

a16z Podcast | Startups and Pendulum Swings Through Ideas, Time, Fame, and Money Jan 2, 2019 · 1 mention

  • ▶ 21:11 Marc Andreessen We've got, you know, AlphaGo, the great accomplishment that Google recently had, that DeepMind had.

a16z Podcast | The Dream of AI Is Alive in Go Jan 2, 2019 · 1 mention

  • ▶ 0:16 Sonal Chokshi And Frank Chen recently put out a tweet storm on why Google's deep mind algorithm beating Lee Sedol was so significant.

a16z Podcast | Building Tech Startups in a Place Where Tech Isn’t Everything Jan 2, 2019 · 4 mentions

  • ▶ 22:48 Matt Clifford It includes people with deep technology talent, you know, kind of, who actually, you know, I mean, the, the deep mind story, actually, I think is a important story for London as an ecosystem, because I think, maybe not for the first time,… 3 times in the scene
  • ▶ 27:25 Michael Copeland Or Google buying, you know, DeepMind.

a16z Podcast | Artificial Intelligence and the 'Space of Possible Minds' Jan 2, 2019 · 2 mentions

  • ▶ 10:28 Murray Shanahan And people, so re, so one of the fundamental techniques in, in DeepMind's work is reinforcement learning.
  • ▶ 32:49 Murray Shanahan Actually, DeepMind are another example of the same thing, because if you want to apply reinforcement learning to games, and that's enabled them to make some quite fundamental sort of progress, you don't need vast amounts of data either.

AI: What's Working, What's Not Dec 8, 2017 · 1 mention

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