Why It Matters That Human Poker Pros Are Getting Trounced By an AI

We’re at the halfway point of the epic 20-day, 150,000-hand “Brains Vs. Artificial Intelligence” Texas Hold’em Poker tournament, and a machine named Libratus is trouncing a quartet of professional human players. Should the machine maintain its substantial lead—currently at $701,242—it will be considered a major milestone in the history of AI. Here’s why.
Given the early results, it appears that we’ll soon be able to add Heads-Up, No-Limit Texas Hold’em poker (HUNL) to the list of games where AI has surpassed the best humans—a growing list that includes Othello, chess, checkers, Jeopardy!, and as we witnessed last year, Go. Unlike chess and Go, however, this popular version of poker involves bluffing, hidden cards, and imperfect information, which machines find notoriously difficult to handle. Computer scientists say HUNL represents the “last frontier” of game solving, signifying a milestone in the development of AI—and an achievement that would represent a major step towards more human-like intelligence.

The “Brains Vs. Artificial Intelligence” tournament began on January 11th at Rivers Casino in Pittsburgh. It pits Libratus, an AI developed by computer scientists at Carnegie Mellon University, against four professional human players, Dong Kim, Jimmy Chou, Jason Les, and Daniel McAulay. The human players are competing for $200,000 in prize money, but serious bragging rights are at stake, too: they are among the best HUNL players in the world, but their opponent is formidable.

As of the weekend, Libratus (which means “balanced” in Latin) amassed a lead of $459,154 in chips in nearly 5,000 hands played by the end of its ninth day. By the end of play on Monday, the machine’s lead stood at a daunting $701,242 over the second place contender. Frustratingly for the players, they can’t seem to get a step up on the artificial poker player. “The bot gets better and better every day,” said Chou in a Carnegie Mellon statement. “It’s like a tougher version of us.”

Limit Texas Hold’em was “solved” by AI back in 2015, but HUNL represents a much bigger challenge for AI developers. Some cards are hidden, and competitors can only see a small portion of what’s happening in the game at any given time. In order to win, players have to rely on their gut instincts, guessing what other players might be doing. In other words, unlike previous game-playing AI, Libratus has to deal with uncertainties and game-playing characteristics that were considered the exclusive domain of humans.

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SOURCE: The gizmodo