【時事新聞】
AlphaGo Conquers Korean Grandmaster Lee Se-dol
超級電腦打敗南韓圍棋大師
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.
星期二那天，Google公司的AlphaGo電腦系統以4比1的總比分贏了韓國圍棋大師李世石。這是人工智慧發展上的一個重大時刻。
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.
由於下圍棋是一件非常複雜的事情，一直以來，要讓電腦能夠精通圍棋這項東亞特有的技藝一直被視為一項嚴峻的挑戰。AlphaGo的製作團隊估計，圍棋的每一步都有250種可能的走法（相較西洋棋只有35種），因此產生的可能局面數量為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，可說是過去10年來最棒的圍棋選手，起先也曾預計自己會取得壓倒性的勝利。他認為，AlphaGo缺少擊敗他所需的「直覺」。但在上週三開始這場對決中，電腦程式贏了前三局，而後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.
週二的最後一局是雙方廝殺到最難分難解的一次：AlphaGo起先出現了一次失誤，但後來挽回了局面，並在雙方都用盡了所分配到的兩小時後，把李世石拖入了延長賽，最後他在該階段棄子認輸。
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的勝利展現了其製作群所使用「深度學習」系統的威力。AlphaGo是由Google在兩年前收購的倫敦創新公司DeepMind所一手打造的。
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 200 million positions per second. Instead, AlphaGo learned to recognize promising moves by playing huge numbers of Go matches against itself.
圍棋的高複雜度超出了IBM公司研發的西洋棋電腦深藍(Deep Blue) 所運用的「蠻力」方式的處理能力。1997年，每秒評估2億步的深藍戰勝了加里•卡斯帕羅夫(Garry Kasparov)。AlphaGo則是通過自己跟自己大量對弈，學會了如何推測對手可能的走法。
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執行長Demis Hassabis表示，此次對弈將使他的團隊能對AlphaGo系統進行更多改進。該系統在對戰過程中暴露出了一些缺陷——尤其是在第四局中，當李世石走出了反常規的一步時，促使AlphaGo出現一連串業餘選手般的失誤。
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.
星期二時，Hassabis在Twitter上發文指稱，系統紀錄顯示了，AlphaGo認為李世石走出特別的那一步是低於萬分之一可能性的。
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.”
與此同時，李世石拒絕承認人類統治圍棋的時代已經終結。「我並不完全認為AlphaGo比我高明——人類在對抗人工智慧方面還能做得更多。」他進一步表示，「我不認為這是人類的失敗。超級電腦只是顯露了我個人的缺陷，而非人類的弱點。」
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