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Deep Learning + Al: How machines are becoming master problem solvers

机译:深度学习+ Al:机器如何成为主要的问题解决者

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Fourteen years later, Al made its television debut in grand style, when IBM's Watson took down a pair of former "Jeopardy!" winners in a televised match. In milliseconds, the machine culled the most probable answer to each question from more than 200 million pages of content, including the complete Wikipedia catalog. (Watson was not connected to the Internet during the match.) Now, Google's Al system, AlphaGo, is making cognitive computing history. Last month, the system outdueled Go Grandmaster Lee Sedol in a five-game match (4-1). Go is an East Asian "chess on steroids" strategy game that uses a larger board and many more pieces than chess, creating a scenario with more possible board positions (10~(170) positions) than atoms in the known universe (10~(80)), according to Google.
机译:十四年后,当IBM的沃森(Watson)击败了一对前“ Jeopardy!”时,艾尔(Al)以宏伟的风格首次亮相电视。电视直播比赛的获胜者。机器以毫秒为单位,从超过2亿页的内容(包括完整的Wikipedia目录)中选出了每个问题的最可能答案。 (沃森在比赛中没有连接到互联网。)现在,谷歌的Al系统AlphaGo正在创造认知计算的历史。上个月,该系统在五场比赛(4-1)中超越了Go大师李世多(Le Sedol)。 Go是一种东亚“象棋棋子”策略游戏,使用的棋盘比棋子大得多,棋子多得多,从而创建了一个场景,其中棋盘位置(10〜(170)位置)比已知宇宙中原子(10〜( 80))。

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