双语阅读｜能下围棋的人工智AlphaGo挑战人类棋手
IN 1996 IBM challenged Garry Kasparov to a game of chess against one of its computers, Deep Blue. Mr Kasparov, regarded as one of the best-ever players, won—but Deep Blue won the rematch. Two decades on, computers are much better than humans at chess but remain amateurs when it comes to the much tougher, ancient game of Go. Or at least, they did. Now a computer has managed to thrash a top-drawer human player.
1996年，IBM用其“深蓝”（Deep Blue）电脑挑战加里·卡斯帕罗夫（Garry Kasparov），进行了一场国际象棋对弈。被认为是史上最厉害的国际象棋棋手之一的卡斯帕罗夫赢了比赛，但却在第二次比赛中败给了“深蓝”。近二十年来，电脑在国际象棋比赛中的表现超过了人类，不过，在围棋这种更为复杂和古老的游戏中，电脑只能算是个“菜鸟”。至少它们过去如此。现在，一台电脑成功击败了人类顶级棋手。
The computer used a program, called AlphaGo, developed by DeepMind, a London-based artificial intelligence (AI) company bought by Google in 2014 for $400m. It took onFan Hui, European Go champion, beating him 5-0, according to a reportin Nature. Beating a champion at Go has long been considered a “grand challenge” in AI research, for the game is far harder for computers than chess. Go players alternately place black or white stones on a grid of 19x19 squares with the aim of occupying the most territory. The size of the board, and the number and complexity of potential moves, make the game impossible to play via brute-forcecalculation. Demis Hassabis, DeepMind’s founder and one of the paper’s authors, reckons that a typical Go turn offers around 200 legal moves, compared with just 20 or so in chess.
这台电脑运行一个名为“AlphaGo”的程序。该程序由伦敦人工智能公司名称DeepMind开发。该公司于2014年由谷歌以4亿美金价格收购。根据《自然》（Nature）杂志报道，AlphaGo与欧洲围棋冠军樊麾对弈，并以5:0的战绩击败对手。在人工智能研究中，击败围棋冠军长久以来都被视为一项“巨大挑战”，因为对于计算机来说围棋要比象棋难很多。围棋玩家轮流在19x19的正方形网格棋盘上落下黑子和白子，双方均以尽可能多占地盘为目标。棋局的规格、数量以及每一步可能的棋路的复杂性，都决定了围棋不是通过蛮力计算就能玩得转的。DeepMind的创始人，也是上文作者之一的戴密斯·哈萨比斯（Demis Hassabis）预估一盘典型的围棋棋局大概有200步正规的走法，而象棋仅有20来种。
Whereasa chess-playing computer like Deep Blue was programmed directly by humans, AlphaGo used AI to teach itself about how to play Go and then make its own decisions. This was done with a technique called machine learning, which allows computers to figure out for themselves how to do things, such as to recognise faces, respond to speech and even translate between languages.
尽管像“深蓝”这样会下象棋的计算机是由人类直接编程控制的，但是AlphaGo运用人工智能来自学下围棋，然后自己作出决定。这是通过机器学习的技术来实现的。这种技术能让计算机自己判断如何行事，比如面部识别、言语对答甚至是翻译。
AlphaGo works in two parts. When it is the computer’s turn, the program first suggests moves based on the sorts of general tactics that human players have used in the past—much as Deep Blue would. Then the second part of the system siftsthose moves for those that look like they might lead to a win, again based on patterns it has picked up through memorising zillions of previous games.
AlphaGo分两个部分运行。在轮到电脑下子时，程序会首先利用人类棋手之前使用过的一般性策略来指出棋步——这点和“深蓝”基本一样。然后，系统的另一个部分会挑选出那些赢面比较大的棋步，同样也是通过记忆先前的无数棋局模式来实现的。
The ultimatetest of AlphaGo’s capabilities, though, will come in March. DeepMind has persuaded Lee Sedol, a Korean player widely regarded—like Mr Kasparov in his day—as one of the best-ever players, to take on their machine in a series of games in Seoul. If AlphaGo wins—and given its performance against Mr Hui, that seems like a distinct possibility—then human brains, and their possessors, will have to cedeanother defeat to the machines.
不过，对于AlphaGo性能的最终测试将在三月份进行。DeepMind说服了韩国棋手李世乭（Lee Sedol）与他们旗下的计算机在首尔进行几场对弈。李世乭被认为是有史以来最厉害的棋手之一，就像当时炙手可热的卡斯帕罗夫一样。如果此次AlphaGo赢了，再加上其先前与樊麾对弈时的表现，这很可能会让人脑和人类再次输给机器。
译文来源：网络
审校&编辑：翻吧君
英文来源：经济学人