AI is better at bluffing than professional gamblers

The act of gambling on games of chance has been around for as long as the games themselves. For as long as there’s been money to be made wagering on the uncertain outcomes of these events, bettors have been leveraging mathematics to give them an edge on the house. As gaming has moved from bookies and casinos into the digital realm, gamblers are beginning to use modern computing techniques, especially AI and machine learning (ML), to increase their odds of winning.

AI has proved itself quite literally capable of beating humans at their own games, but does that hold true when the chips are down and real money is on the line? As the Libratus system from Carnegie Mellon University showed in 2017, the answer remains a resounding yes.

It wasn’t so much of a poker tournament as it was a three-week curb stomping. Professional poker players Jason Les, Dong Kyu Kim, Daniel McAulay and Jimmy Chou spent 20 days playing 120,000 hands of heads-up, no-limit Texas Hold’em against the AI but wound up losing by a margin of more than $1.76 million in the end.

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