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.
单选题
The phrase "plying their various trades" (Line 3, Para. 1) most probably means______.
【正确答案】
B
【答案解析】解析：语义题。原文第一段提到：scientists and coders sit busily on benches，plying their various trades．其中，plying their various trades是伴随状语，与上文意思相近，互为同义替换关系。故该题答案提示为sit busily on benches“坐在座位上忙碌”。选项[A]running their own business“经营各自的生意”，该项的run business是对trade一词的错误理解，故排除。选项[B]being engaged with their work“忙着各自的工作”，该项与原文sit busily on benches意思接近，故为答案。选项[C]working with different companies“与不同公司合作”，该项与原文毫无关系，可以排除。选项[D]being busy with their private affairs“忙于处理私事”，其中private affairs一词属于无中生有，故排除。综上，本题答案为[B]。
单选题
According to Paragraph 2, BenevolentAI's version of AI can______.
【正确答案】
A
【答案解析】解析：细节题。根据关键词BenevolentAI’s version of AI定位到第二段第一行：But Benevolent AI’s version of it is a form of machine learning that can draw inferences about what it has learned．选项[A]make some inferences“作出一些推断”=draw inferences about what it has learned，故该项为答案。选项[B]think like human beings“像人类一样思考”，该项属于无中生有。选项[C]teach machines to learn“教授机器学习”是针对machine learning“机器学习”的干扰，其中teach一词无中生有。选项[D]learn complex language“学习复杂语言”，该项与it can process natural language一句相关，但是并不等同，learn“学习”不等于“处理”，故该项也与原文不符。综上，本题选择[A]。
单选题
A growing number of companies believe that AI can be used to ______.
【正确答案】
D
【答案解析】解析：观点题。定位到第三段。其中a growing number of companies=more and more people and firms；AI can be used to=AI is well placed to，故该题答案句为：to help unpick biology and advance human health“有助于破解生物学的奥秘，促进人类健康”。选项[A]exploit human potential“开发人类潜力”，该项的human potential一词属于无中生有，故排除。选项[B]impair physical health“损害身体健康”，该项与原文advance human health“促进人类健康”完全相反，故排除。选项[C]solve social problems“解决社会问题”，该项同样属于无中生有，可以排除。选项[D]benefit human beings“对人类有益”与原文advance human health“促进人类健康”是同义替换关系，故[D]项为正确答案。
单选题
According to the last paragraph, which of the following is true?
【正确答案】
B
【答案解析】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]。
单选题
The traditional way to find new drugs can be characterized by being______.
【正确答案】
C
【答案解析】解析：细节题。定位到最后一段。其中traditional way=conventional approach；find new drugs=search for novel products：而题干问be characterized by“具有……的特征”，答案句来自文章最后一句：This way of doing things is，however，declining in productivity and rising in cost．其中this way=traditional way，故答案为however之后的declining in productivity and rising in cost“生产率下降，成本上升”；其中declining“下降”一词是明显的负面词汇，故可以排除选项[A]hopeful“有希望的”与选项[D]productive“多产的”。选项[B]expensive“昂贵的”=rising in cost，但无法概括declining in productivity，故该项属于片面选项，也非答案。选项[C]inefficient低效率的=declining in productivity and rising in cost，故该项为正确答案。