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  3. In a former leather factory just off Euston Road in London, a hopeful firm is starting up. BenevolentAI’s main room is large and

In a former leather factory just off Euston Road in London, a hopeful firm is starting up. BenevolentAI’s main room is large and

admin2018-06-28  23
问题    In a former leather factory just off Euston Road in London, a hopeful firm is starting up. BenevolentAI’s main room is large and open-plan. In it, scientists and coders sit busily on benches, plying their various trades. The firm’s star, though, has a private, temperature-controlled office. That star is a powerful computer that runs the software which sits at the heart of BenevolentAI’s business. This software is an artificial-intelligence system.
   AI, as it is known for short, comes in several forms. But BenevolentAI’s version of it is a form of machine learning that can draw inferences about what it has learned. In particular, it can process natural language and formulate new ideas from what it reads. Its job is to sift through vast chemical libraries, medical databases and conventionally presented scientific papers, looking for potential drug molecules.
   Nor is BenevolentAI a one-off. More and more people and firms believe that AI is well placed to help unpick biology and advance human health. Indeed, as Chris Bishop of Microsoft Research, in Cambridge, England, observes, one way of thinking about living organisms is to recognize that they are, in essence, complex systems which process information using a combination of hardware and software.
   That thought has consequences. Whether it is the new Chan Zuckerberg Initiative (CZI) , from the founder of Facebook and his wife, or the biological subsidiaries being set up by firms such as Alphabet (Google’s parent company), IBM and Microsoft, the new Big Idea in Silicon Valley is that in the worlds of biology and disease there are problems its software engineers can solve.
   The discovery of new drugs is an early test of the belief that AI has much to offer biology and medicine. Pharmaceutical companies are finding it increasingly difficult to make headway in their search for novel products. The conventional approach is to screen large numbers of molecules for signs of relative biological effect, and then weed out the useless partin a series of more and more expensive tests and trials, in the hope of coming up with a golden nugget at the end. This way of doing things is, however, declining in productivity and rising in cost.
According to the last paragraph, which of the following is true?
选项 A、AI has made a great contribution to biology and medicine.
B、Whether AI can serve much to medicine is not yet clear.
C、Drug firms find it unaffordable to discover new products.
D、Pharmaceutical companies hope to find real gold in the tests.
答案B
解析 细节题。根据题干锁定最后一段。选项[A]AI has made a great contribution to biology and medicine．“人工智能为生物学和医学作出了巨大贡献。”；选项[B]Whether AI can serve much to medicine is not yet clear．“人工智能能否为医学作贡献还尚无定论”：这两项都与该段首句相关。原文说The discovery of new drugs is an early test of the belief that AI has much to offer biology and medicine．“人工智能是否真的能为生物学和医学作出巨大贡献，寻找新药便是一个初步考验。”其中test of the belief“考验这个信念”=[B]项的not yet clear “尚无定论”。故[B]项正确，[A]错在has made a great contribution。选项[C]Drug firms find it unaffordable to discover new products．“制药公司认为发现新药品的经济负担令人难以承受。”该项与最后一段第二句相关：Pharmaceutical companies are finding it increasingly difficult to make headway in their search for novel products．其中drug firms=pharmaceutical companies；discover=in their search for；new products=novel products；但是unaffordable一词在原文中却无体现，原文说的是difficult to make headway“难以取得进展”，而不是unaffordable“负担不起”，故该项错误。选项[D]Pharmaceutical companies hope to find real gold in the tests．“制药公司希望在实验中找到真的金子。”该项与原文倒数第二句in the hope of coming up with a golden nugget at the end相关，其中golden nugget“金块”在原文中用来比喻有价值的东西，而非真正的金子，故该项错在real gold。综上，本题答案为[B]。
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