Great champions know how to end their career at the peak of their success. DeepMind, Alphabet’s artificial intelligence lab, has decided that its computer program, AlphaGo, will no longer focus on winning the board game Go. Instead, according to a blog post co-written by Demis Hassabis, DeepMind chief executive, the focus will be on “developing advanced general algorithms that could one day help scientists as they tackle some of our most complex problems, such as finding new cures for diseases”.
伟大的冠军懂得如何在巅峰时刻激流勇退。Alphabet旗下人工智能实验室DeepMind已决定，其计算机程序AlphaGo将不再专注于下赢围棋。取而代之的是，根据DeepMind首席执行官杰米斯?哈萨比斯(Demis Hassabis)与别人合写的一篇博文，焦点将是“研发先进的通用算法，有朝一日帮助科学家解决我们面临的一些最复杂的问题，例如为疾病寻找新的治疗方法”。
The ambition is justified. AI may lead to remarkable breakthroughs, especially in the hands of thoughtful people. Yet these spectacular developments may be more easily achieved if a misunderstanding is removed.这一雄心合情合理。人工智能也许将带来重大突破，尤其是当它掌握在考虑周密的人手中时。然而，如果对人工智能的一个误解能够被破除的话，或许会更容易实现这方面的伟大成就。Some seem to think that AI is about coupling artificial agency and intelligent behaviour in new programs. Yet the opposite makes more sense: it is about decoupling successful problem solving from any need to be intelligent. Only when this is achieved is it successful.
有些人似乎认为，人工智能就是在新的程序中耦合人造的主观能动性与智能行为。然而，反过来理解才更有道理：人工智能是关于将成功的问题解决与表现出智能的需要解耦。只有实现这一点，人工智能才算成功。The best definition of AI was written in 1955 by US computer scientist John McCarthy and colleagues, part of the classic proposal for the Dartmouth summer research project on人工智能的最佳定义是由美国计算机科学家约翰?麦卡锡(John McCarthy)及其同事在1955年提出的，那是确立了人工智能这一研究领域的达特茅斯学院暑期人工智能研讨项目经典提议的一部分。他们写道，问题在于“让机器达到这样的行为，即人类如果做出同样行为将被称为智能”。