When a search engine guesses what you want before you finish typing it, or helpfully ignores your bad spelling, that is the resu

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问题     When a search engine guesses what you want before you finish typing it, or helpfully ignores your bad spelling, that is the result of machine learning, a branch of artificial intelligence. Although AI has been through cycles of hype and disappointment before, big technology companies have recently been scrambling to hire experts in the field, in the hope of building machines that can learn even more sophisticated tasks.
    IBM said this month it would invest $1 billion in a new division to develop uses for Watson, its computer that understands human language. But this week Google enhanced its lead in this field by paying around $660m for DeepMind Technologies, a startup in London that has yet to announce a product. The boss of DeepMind, Demis Hassabis, previously created video games such as "Evil Genius" and "Theme Park".
    DeepMind’s 75 geniuses will join the world’s leading group of machine-learning experts, which Google has been assembling in the past few years. Google’s main source of income, its search engine and the accompanying ad-placement system, is driven by machine learning. The firm’s self-driving cars rely on it, as do the intelligent thermostats made by Nest, a firm it has just taken over, and the robots made by Boston Dynamics and other robotics outfits it has been buying.
    The technology is already the backbone of many other internet firms. It is why Facebook and Linkedln have that slightly creepy ability to find people you know, and why Amazon and Netflix are good at suggesting books and films you might like. It also helps intelligence agencies to identify terrorist networks.
    As machine learning leaves the lab and goes into practice, it will threaten white-collar, knowledge-worker jobs just as machines, automation and assembly lines destroyed factory jobs in the 19th and 20th centuries. For example, the technique has been applied by researchers at Stanford University to tell whether a biopsy of breast cells is highly cancerous, something that until now has required a human expert to assess.
    Another of DeepMind’s founders, Shane Legg, has predicted that artificial intelligence running wildly will be the biggest existential risk to humans in this century. Its founders have asked Google to set up an "ethics board" to consider the appropriate use of machine learning in its products. The creator of "Evil Genius" is ensuring that his new overlord sticks to its motto, "Don’t be evil".
What can be learned about machine learning?

选项 A、Machine learning in the lab poses a great threat to jobs done by workers.
B、Some jobs may be eaten up when machine knowledge is turned into practice.
C、It can lead to development in automation and diminish all job opportunities.
D、It can tell whether a biopsy of cells is cancerous without human experts.

答案B

解析 选项A可定位到倒数第二段第一句,而该句“As machine learning leaves the lab and goes into practice, it will threaten white-collar, knowledge-worker jobs just as machines, automation and assembly lines destroyed factory jobs in the 19th and 20th centuries”前半部分表示当machine learning离开实验室进入实际应用时才会危及到这些人的工作,所以单纯的machine learning是不会威胁工人工作的。因此A错误。选项B符合该句内容,some jobs表示“一些工作”,可以替换该句中的“white-collar,knowledge-worker jobs”。C、D选项依然脱离了应用到实际中去的前提。选项C中的“all job opportunities”也夸大了原文表达。
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