分析 本文是一篇科教类阅读,文章主要讲解了过度使用高科技所带来的种种不利并劝诫我们不要过度依赖高科技.
解答 29-32.BADC
29题答案:B考查细节推理,结合第二段的第一句People have been influenced to become technology addicted.人们受影响从而变得对科技有瘾.可知allure一词的含义为"吸引",故本题答案为B选项.
30题答案:A考查细节推理,根据文章第三段的The main goal of technology companies is to get people to spend more money and time on their products,not to actually improve our quality of life.科技公司的主要目标是使人们在他们的产品上花时间和金钱而并非真正提高你的我们的生活质量.可知本题答案为A选项.
31题答案:D考查细节推理,根据文章最后一段的we can be swept away by our technologies.To break the grand digital connection people must consider how life long ago could be fantastic without today's overused technology.我们会被我们的科技所毁灭.为了打破这种巨大的数码联系(过度依赖于科技)人们必须考虑没有当今过度使用的科技生活很久之前的生活是如何能精彩的.可知本题答案为D选项.
32题答案:C考查情感态度,纵观全文作者都在讲过度使用高科技所带来的种种不利并劝诫我们不要过度使用高科技.故本题答案为C选项.
点评 本文是一篇科教类阅读,题目涉及多道细节理解题,做题时结合原文和题目有针对 性找出相关语句进行仔细分析,结合选项选出正确答案.推理判断也是要在抓住关键句子的基础上合理的分析才能得出正确的答案.
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A. | a;/ | B. | a; an | C. | /;the | D. | the; an |
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Computers have beaten human world champions at chess and, earlier this year, the board game Go. So far, though, they have struggled at the card table. So we challenged one AI to a game.
Why is poker(扑克)so difficult? Chess and Go are “information complete” games where all players can see all the relevant information. In poker, other players’ cards are hidden, making it an “information incomplete” game. Players have to guess opponents’ hands from their actions----tricky for computers. Poker has become a new benchmark for AI research. Solving poker could lead to many breakthroughs, from cyber security to driverless cars.
Scientists believe it is only a matter of time before AI once again vanquishes humans, hence our human-machine match comes up in a game of Texas Hold’s Em Limit Poker. The AI was developed by Johannes Heinrich, researcher studying machine learning at UCL. It combines two techniques: neural(神经的)networks and reinforcement learning(强化学习).
Neural networks, to some degree, copy the structure of human brains: their processors are highly interconnected and work at the same time to solve problems. They are good at spotting patterns in huge amounts of data. Reinforcement learning is when a machine, given a task, carries it out, learning from mistakes it makes. In this case, it means playing poker against itself billions of times to get better.
Mr Heinrich told Sky News: “Today we are presenting a new procedure that has learned in a different way, more similar to how humans learn. In particular, it is able to learn abstract patterns, represented by its neural network, which allow it to deal with new and unseen situations.”
After two hours of quite defensive play, from the computer at least, we called it a draw.
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A. Because humans are cleverer than the computer
B. Because humans practice playing the poker game every day
C. Because the computer can’t know the other players’ cards completely
D. Because the computer can’t learn the regular rules of the poker game
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