Google machine-learning system is first to defeat professional Go player

Go is played on a grid of black lines (usually 19×19). Game pieces, called stones, are played on the line intersections. (credit: Goban1/Wikipedia) A deep-learning computer system called AlphaGo created by Google’s DeepMind team has defeated reigning three-time European Go champion Fan Hui 5 games to 0 — the first time a computer program has ever beaten a professional Go player, reports Google Research blog today (Jan. 27) — a feat previously thought to be at least a decade away. “AlphaGo uses general machine-learning techniques to allow it to improve itself, just by watching and playing games,” according to David Silver and Demis Hassabis of Google DeepMind. Using a vast collection of more than 30 million Go moves from expert players, DeepMind researchers trained their system to play Go on its…


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