Facebook’s Poker Bot Shows How A.I. Can Adapt to Liars

In a new study with significant real-world implications, a poker bot crushed human pros at six-player, no-limit Texas Hold ’em

Dave Gershgorn
OneZero

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Illustration: Jess Ebsworth

SSometimes, poker is all about the bluff. Make the table believe you have a full house when you really have a low pair, and it can pay off big time. Read your opponents — a grimace here, a smirk there — and bet accordingly.

It’s not a skill you’d think computers would be particularly good at. But new research published in Science today shows that A.I. can learn to respond to fibs without needing to even see anyone else at the table, and outwit the best human poker players. It’s a development that may have implications far beyond the casino.

A poker-playing bot called Pluribus recently crushed a dozen top poker professionals at six-player, no-limit Texas Hold ’em over a 12-day marathon of 10,000 poker hands. Pluribus was created by Noam Brown, an A.I. researcher who now works at Facebook, and Tuomas Sandholm, a computer science professor at Carnegie Mellon University in Pittsburgh. (The two co-authored the paper in Science.)

If each chip in the experiment were worth a dollar, Pluribus would have made $1,000 an hour against the pros, according to Facebook, which published…

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Dave Gershgorn
OneZero

Senior Writer at OneZero covering surveillance, facial recognition, DIY tech, and artificial intelligence. Previously: Qz, PopSci, and NYTimes.