Google’s AlphaGo computer system sealed a 4-1 victory over a South Korean Go grandmaster on Tuesday, in a landmark moment for the development of artificial intelligence.

周二，谷歌(Google)的AlphaGo计算机系统以4比1的总比分战胜了韩国围棋大师李世石(Lee Se-dol)。这是人工智能发展中的一个里程碑时刻。

Mastery of the east Asian game of Go was long seen as a stern challenge for computers given its huge complexity. AlphaGo’s creators estimate that there are about 250 potential moves at each point of a game, against 35 in chess, yielding a possible number of board configurations of 10 squared by 170.

鉴于围棋极其复杂，长期以来，精通围棋一直被视为计算机面临的一项严峻挑战。AlphaGo的创建者估计，围棋的每一步都有250种可能走法（国际象棋只有35种），产生的可能局面数量为10的170次方。

Lee Se-dol, arguably the best player of the past decade, had expected to win a crushing victory, arguing that AlphaGo lacked the “intuition” needed to beat him. But the program won the first three games in the series, which began last Wednesday, before Mr Lee clawed back a victory on Sunday.

李世石可以说是过去10年最棒的围棋手，他曾预计自己会取得压倒性胜利。他认为，AlphaGo缺少击败他所需的“直觉”。但在上周三开始这场对决中，计算机程序赢了前三局，而后李世石在上周日扳回一局。

Tuesday’s final game was one of the closest: AlphaGo recovered from an early error to force Mr Lee into resignation in overtime, with each player having used up the allotted two hours.

周二的最后一局是双方拼杀得最难解难分的一局：AlphaGo起先出现了一次失误，但后来挽回了局面，把李世石拖入读秒，李世石在读秒阶段投子认输。双方都用尽了分配给自己的两小时。

The victory demonstrates the power of the “deep learning” systems employed by AlphaGo’s creators at DeepMind, a London-based start-up acquired by Google two years ago.

AlphaGo的胜利证明了创建者使用的“深度学习”系统的威力。AlphaGo是由谷歌在两年前收购的伦敦创业型企业DeepMind创建的。

Go’s huge complexity rules out the “brute force” approach of IBM’s Deep Blue chess computer, which beat Garry Kasparov in 1997 by evaluating 200m positions per second. Instead, AlphaGo learned to recognise promising moves by playing huge numbers of Go matches against itself.

围棋的巨大复杂性超出了IBM深蓝(Deep Blue)国际象棋计算机“蛮力”方法的处理能力。1997年，每秒评估2亿步的深蓝战胜了加里•卡斯帕罗夫(Garry Kasparov)。AlphaGo则是通过自己跟自己大量对弈，学会了如何推测对手可能的走法。

Demis Hassabis, DeepMind’s chief executive, said the series would enable his team to make further improvements to the system, which had some flaws exposed during the contest — notably when an unorthodox move by Mr Lee in the fourth match prompted AlphaGo to make a series of amateurish blunders.

DeepMind首席执行官杰米斯•哈萨比斯(Demis Hassabis)表示，此次对弈将使他的团队能对AlphaGo系统进行更多改进。该系统在对弈过程中暴露出了一些缺陷——尤其是在第四局中，李世石走出了反常规的一步，导致AlphaGo出现一连串业余选手般的失误。

The system’s log showed that it had assessed the likelihood of Mr Lee’s move at less than one in 10,000, Mr Hassabis tweeted on Tuesday.

周二，哈萨比斯在Twitter上发帖称，系统日志显示，AlphaGo认为李世石走出那一步的可能性低于万分之一。

Mr Lee, meanwhile, refused to concede that the era of human supremacy in Go was at an end. “I don’t necessarily think AlphaGo is superior to me — there’s more that a human being can do against artificial intelligence,” he said. “I don’t feel this was a loss for human beings. It showed my weaknesses, not the weaknesses of humanity.”

李世石拒绝承认人类统治围棋的时代已经终结。“我并不完全认为AlphaGo比我高明——人类在对抗人工智能方面还能做得更多。”他说，“我不认为这是人类的失败。它暴露出了我个人的弱点，而非人类的弱点。”