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MIT Professor Gives Language Lessons to Computers

There’s a scene in the 2008 movie Iron Man where Tony Stark, the film’s inventor-superhero, threatens to donate one of his robots to a city college. You can tell by its cowed response that the computerized assistant understands the connotation is decidedly negative. In real life, software can’t yet comprehend that kind of abstract scolding. Programmers refer to such banter as “natural language,” and it’s tricky for computers to get because of its ambiguity and dependence on context.

Regina Barzilay, an associate professor at the Massachusetts Institute of Technology, is trying to make computers better listeners by making them play Civilization, a 20-year-old strategy game in which players build a city into an empire by vanquishing and absorbing neighboring cultures. A member of MIT’s Computer Science & Artificial Intelligence Lab, Barzilay, 40, developed a software program that begins with no grasp of the game. The computer “reads” the manual and then keeps returning to it while playing. As it races through thousands of simulations, the computer learns to connect words in the directions (“attack,” “build,” “capture,” and “revolt”) as the game unfolds.

The computer gets positive reinforcement—a higher score and a win—when it makes correct guesses about the meaning of words. When the computer loses, it traces back through its reading of the manual to see where its interpretation went wrong. A similar program without access to the manual won the game 46 percent of the time; after reading the instructions, Barzilay’s computer won 79 percent of the time.

Barzilay grew interested in natural-language processing in the early 1990s, as an undergraduate at Ben-Gurion University in Beersheba, Israel. She was inspired in part by her own experience as a young emigrant from Moldavia who had to learn Hebrew and English. Just as she struggled at first to understand the use of articles such as “the,” which have no equivalent in her native Russian, logic-based computers have difficulties with the inconsistencies of natural language.

Research like Barzilay’s may help computers eventually interact with humans in a more normal way. “You’d like to be able to ask for the largest state bordering New York and have it come back with the answer, ‘Pennsylvania,’” says Dan Roth, a computer science professor at the University of Illinois at Urbana-Champaign who does work similar to Barzilay’s. “And what happens inside the computer is none of your business.” Barzilay has been pushing this line of work forward, he says, in part by using a more interesting and complex game. She has a grant from the Defense Advanced Research Projects Agency to help robots understand natural language, not unlike those in Iron Man. As she puts it: “I want to see the computer benefit directly from human knowledge, without having a person in the middle who does a translation.”

評析：本文出自美國商業(yè)類主流雜志《商業(yè)周刊》。通過閱讀標(biāo)題，大致可以了解本篇的主旨是講麻省理工的教授又有了新動作，給電腦上起了語言課。開篇邊通過引用電 影《鋼鐵俠》中的場景，對比引出現(xiàn)實中的計算機是不可能像電影中那么智能的。隨后第二段就講到，麻省理工副教授Regina Barzilay在讓計算機“聽話”方面所做的研究。最后，總結(jié)了Barzilay的研究可以幫助計算機和人類以一種更加正常的方式進行交流，用她的話來 說，就是實現(xiàn)更好的人機交互，而不需要一個中間人來做翻譯。

全文字數(shù)在460-470左右，篇幅不算太長，但是對于那些對科技不感興趣的人來說，做到透徹理解還是較難?？荚嚨臅r候，不妨根據(jù)考題，到原文中去定位， 提取關(guān)鍵信息，細枝末節(jié)則暫且忽略，只要不影響整體理解就行。而在平時，還是建議廣大考生多關(guān)注這類文章，即使不敢興趣，也要嘗試去多閱讀，多了解，廣泛 涉獵，充實自己的知識儲備總歸不是壞事。要想考場發(fā)揮地游刃有余，就要通過平常不斷的積累。

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