Poker isn't like other games artificial intelligence has mastered, such as chess and go. In poker, each player has different information from the others and, thus, a different perspective on the game. This means poker more closely mirrors the kinds of decisions we make in real life but also presents a huge challenge for AI. Now, an AI system called DeepStack has succeeded in untangling this imperfect information, refining its own strategy to win against professional players at a rate nearly 10 times that of a human poker pro. We speak with Michael Bowling, who leads the team that designed DeepStack, to learn how.

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