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商业 - 科技

人工智能横扫围棋界,未来可能替人类做决策

David z.Morris 2017年01月10日

谷歌的围棋软件已经打遍天下无敌手,其背后的机器学习技术,将帮助解决更加复杂的现实问题。

在一系列非官方的在线对弈中,谷歌的人工智能旗手AlphaGo的升级版在与世界围棋顶级棋手的对弈中,创下了60-0的纪录,就连世界排名第一的柯洁亦被其轻松击败。

2016年3月,AlphaGo曾击败韩国的李世石。

AlphaGo利用在线账号Magister和Master,通过计算机进行了比赛——这两个名字似乎也预示了最终的结果。《华尔街日报》称,人工智能的策略不合乎传统棋理,令人无法预测,它的一些着法要经过很多手之后才能展显现其完整的意图。它的棋路也让它的人类对手开始深深地反思,这也折射出了计算机智能所带来的更广泛的问题。

被人工智能击败的九段棋手古力在微博中表示:“AlphaGo的出现已经彻底颠覆了我们棋手对局势原有的掌控、判断。那我不禁要问,多年后的某一天,当你发现自己曾经的意识、认知、抉择都是错误的时候,你会一如即往的错下去,还是否定自己,给自己重新开始的机会呢?”

另外一位来自以色列的棋手阿里·贾巴林称,他偶然碰到了刚刚被AlphaGo击败的柯洁。据贾巴林表示,柯洁“有点被震撼到了”……只是反复说“它太厉害了”。

可以预料,开发团队DeepMind的官方声明并没有这么焦虑。声明中强调希望人工智能能够与人类“在相互启发的气氛中共同领会围棋的奥妙”——并且承诺将很快安排AlphaGo下一阶段的正式比赛。

这种乐观情绪恐怕无法在现实社会的经济领域引起共鸣,例如上周被人工智能取代的日本保险行业从业者。

就像工业机器人对工厂工人的影响一样,如今,决策程序似乎也对正白领工人产生了同样的影响。虽然AlphaGo掌握的是一种游戏,但开发它采用的机器学习技术,将有助于制造能解决更加复杂的现实问题的人工智能,从而接管更多的人类工作。(财富中文网)

作者:David z.Morris

译者:刘进龙/汪皓

In a series of unofficial online games, an updated version of Google’s AlphaGo artificial intelligence has compiled a 60-0 record against some of the game’s premier players. Among the defeated, according to the Wall Street Journal, were China’s Ke Jie, reigning world Go champion.

The run follows AlphaGo’s defeat of South Korea’s Lee Se-dol in March of 2016, in a more official setting and using a previous version of the program.

The games were played by the computer through online accounts dubbed Magister and Master—names that proved prophetic. As described by the Journal, the AI’s strategies were unconventional and unpredictable, including moves that only revealed their full implications many turns later. That pushed its human opponents into deep reflections that mirror the broader questions posed by computer intelligence.

“AlphaGo has completely subverted the control and judgment of us Go players,” wrote Gu Li, a grandmaster defeated by the program, in an online post. “When you find your previous awareness, cognition and choices are all wrong, will you keep going along the wrong path or reject yourself?”

Another Go player, Ali Jabarin, described running into Ke Jie after he had been defeated by the program. According to Jabarin, Jie was “a bit shocked . . . just repeating ‘it’s too strong’.”

Predictably, the official statement from developers DeepMind is less angsty, emphasizing the potential for AI to “explore the profound mysteries of the game further in this spirit of mutual enlightenment”—and promising that AlphaGo will take its next-level game to more official venues soon.

That optimism might not resonate with the Go players’ real-economy counterparts—for instance, the group of Japanese insurance workers supplanted by an artificial intelligence this week.

What industrial robots have been to factory jobs, it seems, decision-making programs are becoming for white-collar workers. And though AlphaGo has mastered a game, the machine learning techniques behind its development will help build AIs to solve ever more complex real-world problems—and take ever more human jobs.

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