![]() It radically overhauled the search algorithm. The research team created Pluribus by building on what it learned from Libratus. On average, Pluribus won $480 from its human competitors for every 100 hands-on par with what professional poker players aim to achieve. It played 10,000 hands of poker against five others from a pool of million-dollar earners in poker. It won by a staggering amount and walked away with $1.8 million in chips. Libratus played 120,000 hands in a 20-day poker competition against four top-ranked Texas Hold 'em players. This system required 100 central processing units (CPUs) to run. Libratus is an AI, built by Noam Brown and Tuomas Sandholm of Carnegie Mellon University in 2017, that was ultimately unbeatable at two-person poker. Libratus: Masters Two-Player Texas Hold ’Em After playing 44,852 games, DeepStack’s results were ten times what a professional poker player considers a sizable margin. DeepStack played two-player Texas Hold 'em against professional poker players from the International Federation of Poker. ![]() The AI relies on its neural networks to determine the best moves. ![]() DeepStack’s neural networks were trained by solving more than 10 million poker game situations. The DeepStack team, from the University of Alberta in Edmonton, Canada, combined deep machine learning and algorithms to create AI capable of winning at two-player, “no-limit” Texas Hold ’em, a game more complex for AI to master than others because of its random nature, hidden cards and players’ bluffs. ![]()
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