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".
单选题
The underlined word "hype" (Para. 1, Line 3) may be closest to ______.
【正确答案】
C
【答案解析】解析：文章背景的cycles of hype and disappointment (______和失望的循环)中出现了cycle(循环)一词，因此可以判断hype应该与disappointment的意思相反。故四个选项中我们应该选择与“disappointment(失望)”意思相反的词。四个选项分别是：困惑、惊奇、激动和绝望。显然“失望”是否定词，四项中唯一一个表示肯定的词是excitement，故答案为C。
单选题
DeepMind Technologies is ______.
【正确答案】
D
【答案解析】解析：根据题干中的“DeepMind Technologies”定位到第二段。该段第三行指出：Deep-Mind Technologies, a startup in London… 其中，“a startup(一家新兴企业)”与选项A，“a giant(一家大型企业)”和C“a leading technological company(一家带头的技术公司)”完全不符，故可以排除A和C两项。而B项中的“develops video games”与原文倒数第二行“previously created video games”不符。再根据文章第二句“But this week Google enhanced its lead in this field by paying around $660m for DeepMind Technologies…”一句我们可以得知，谷歌付给DeepMind Technologies这些费用，说明二者是合作关系，因此选项D，a newly started firm that cooperates with Google是对DeepMind Technologies的最佳描述，故答案为选项D。
单选题
Google has done the following EXCEPT ______.
【正确答案】
D
【答案解析】解析：根据题干中的“Google”和选项D中的“Nest and Boston Dynamics”这些大写词共同定位到第三段。选项A对应该段首句：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. 由此可见选项A表述正确，其中“gathering”对应“assembling”；“talents on machine-learning”对应“machine-learning experts”。即该项不是该题的答案。选项B对应第二句：Google's main source of income, its search engine and the accompanying ad-placement system… 其中该项的“earning money from”对应原文中的“source of income”。故该项表述正确，非答案。选项C中的“purchasing”让我们定位到最后一句的“buying”，该句的“other robotics outfits it has been buying(它一直以来购进的其他自动化装备)”对应选项C，purchasing a large number of automatic devices，其中“buying”对应“purchasing”；“has been buying(一直购买)”对应“purchasing a large number of(大量购买)”；“robotics outfits(机器人设备，自动化设备)”对应“automatic devices(自动化设备)”，故该项表述也正确，非答案。选项D对应最后一句：...made by Nest，a firm it has just taken over，and the robots made by Boston Dynamics…该句指出，Nest被Google接管，但是Boston Dynamics则没有提到，故该项taking over firms like Nest and Boston Dynamics是错误的，故答案为D。
单选题
Technology contributes to all EXCEPT ______.
【正确答案】
A
【答案解析】解析：根据出题顺序以及题干中的“technology”一词定位到第四段。该段讨论technology的一些作用，“It is why Facebook and Linkedln have that slightly creepy ability to find people you know”一句对应选项B，discovering people's acquaintance，其中“find people you know”=“discovering people's acquaintance”。“…and why Amazon and Netflix are good at suggesting books and films you might like．”一句对应选项C，recommending good books and movies，其中，“suggesting books and films”对应“recommending good books and movies”。“It also helps intelligence agencies to identify terrorist networks”对应选项D，confirming hacker attack for spy agencies，其中“identify(确认)”对应“confirming(证实)”；“terrorist networks(网络恐怖)”对应“hacker attack(黑客攻击)”；“intelligence agencies(情报部门)”对应“spy agencies(间谍机构)”。故B、C、D三项原文均有涉及，唯一没有提到的是选项A，故该项为答案。
单选题
What can be learned about machine learning?
【正确答案】
B
【答案解析】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。