In the new research AlphaZero played around 60 million games against itself to reinforce its “understanding” of the rules. It does so via reinforcement learning, the concept of a machine learning about an interactive environment through trial, error and reward. Yet the AlphaZero algorithm learns how to “play” games on its own. Many prior game-playing technologies initially required information provided by humans-they must be prepped to handle a specific task. It is technology that once fully developed could have a wide range of uses-from drug development to mathematics to material design. Published today in Science, DeepMind’s AlphaZero system has demonstrated superhuman success at not just chess but also shogi-aka “Japanese chess”-and go, an ancient Chinese board game with a staggering number of move possibilities (around 300 times that of chess). And the latest research by the AI company DeepMind (owned by Alphabet, Google’s parent company) has just taken the field another step forward. Whereas Deep Blue took down Kasparov via sheer computing power, newer computer technologies actually learn and deduce solutions on their own. Over 20 years on artificial intelligence has barreled ahead. The famed dethroning of the reigning chess world champion by IBM’s Deep Blue computer signaled a brave new world of computer intelligence-of machines overtaking humanity. Chess master Garry Kasparov ambled off stage in disbelief, arms up in defeat, having just lost to a computer. It was in 1997 on the 35th floor of a Midtown Manhattan skyscraper.
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