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Tuomas Sandholm: Poker and Game Theory | Lex Fridman Podcast #12

Tuomas Sandholm is a professor at CMU and co-creator of Libratus, which is the first AI system to beat top human players at the game of Heads-Up No-Limit Texas Hold'em.

Lex FridmanhostTuomas Sandholmguest
Dec 28, 20181h 6mWatch on YouTube

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Episode Details

EPISODE INFO

Released
December 28, 2018
Duration
1h 6m
Channel
Lex Fridman Podcast
Watch on YouTube
▶ Open ↗

EPISODE DESCRIPTION

Tuomas Sandholm is a professor at CMU and co-creator of Libratus, which is the first AI system to beat top human players at the game of Heads-Up No-Limit Texas Hold'em. He has published over 450 papers on game theory and machine learning, including a best paper in 2017 at NIPS / NeurIPS. His research and companies have had wide-reaching impact in the real world, especially because he and his group not only propose new ideas, but also build systems to prove these ideas work in the real world. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep12-sb See below for timestamps, and to give feedback, submit questions, contact Lex, etc. *CONTACT LEX:* *Feedback* - give feedback to Lex: https://lexfridman.com/survey *AMA* - submit questions, videos or call-in: https://lexfridman.com/ama *Hiring* - join our team: https://lexfridman.com/hiring *Other* - other ways to get in touch: https://lexfridman.com/contact *PODCAST LINKS:*

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SPEAKERS

  • Lex Fridman

    host
  • Tuomas Sandholm

    guest

EPISODE SUMMARY

In this episode of Lex Fridman Podcast, featuring Lex Fridman and Tuomas Sandholm, Tuomas Sandholm: Poker and Game Theory | Lex Fridman Podcast #12 explores AI Mastering Poker Reveals Future of Game Theory and Strategy Lex Fridman interviews Tuomas Sandholm about Libratus, the first AI to decisively beat top professionals in heads-up no-limit Texas Hold'em, and what that implies for AI, game theory, and real-world strategy. Sandholm explains how imperfect-information games differ fundamentally from perfect-information games like chess and Go, and why abstractions, equilibrium computation, and belief modeling are central. They discuss extensions to learning-based methods, exploitation and collusion in multi-player settings, and moving beyond benchmark games into business, military, and market design applications. Sandholm also reflects on mechanism design, real-world impact (kidney exchanges, auctions), and why he is optimistic about AI’s societal benefits despite theoretical concerns about misalignment.

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