破除對人工智能的誤解大綱
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”.
偉大的冠軍懂得如何在巔峯時刻激流勇退。Alphabet旗下人工智能實驗室DeepMind已決定，其計算機程序AlphaGo將不再專注於下贏圍棋。取而代之的是，根據DeepMind首席執行官傑米斯?哈薩比斯(Demis Hassabis)與別人合寫的一篇博文，焦點將是“研發先進的通用算法，有朝一日幫助科學家解決我們面臨的一些最複雜的問題，例如爲疾病尋找新的治療方法”。
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.
這一雄心合情合理。人工智能也許將帶來重大突破，尤其是當它掌握在考慮周密的人手中時。然而，如果對人工智能的一個誤解能夠被破除的話，或許會更容易實現這方面的偉大成就。
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.
有些人似乎認爲，人工智能就是在新的程序中耦合人造的主觀能動性與智能行爲。然而，反過來理解才更有道理：人工智能是關於將成功的問題解決與表現出智能的需要解耦。只有實現這一點，人工智能纔算成功。
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
人工智能的最佳定義是由美國計算機科學家約翰?麥卡錫(John McCarthy)及其同事在1955年提出的，那是確立了人工智能這一研究領域的達特茅斯學院暑期人工智能研討項目經典提議的一部分。他們寫道，問題在於“讓機器達到這樣的行爲，即人類如果做出同樣行爲將被稱爲智能”。
