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阅读理解。 Many people have talked about whether or not computing machines can think. Can they or can't they? Almost certainly, a machine can do any work in thinking that a person can do-if the correct way for doing the thinking work can be told exactly. Besides, many programs have been made to direct machines so that they work in very clever ways. Machines have been taught to play chess and to leam from what happens in the games so as to make their play better and better. Machines can beat many persons who play chess. Machines can translate from one language to another. They can prove statements in geometry (几何) as taught in school. Machines can notice printed marks on paper, so that a person is no longer needed to look at the marks. Computers can be used in many ways, such as business, science, industry, and govemment. Computers study oil-field examinations made by airplanes; they keep record of oil sales; they study the working condition of the machines; they help in plan- ning and producing oil; and much more. If people cannot tell exactly the correct way to do certain work in thinking, it is still a question how much of this work a machine can do. Suppose a person is 'teaching' the machine and telling the machine 'yes' when the machine is right, and 'no' when the machine is wrong. Then the machine can keep on searching among possible ways for solving a problem-until the machine can do as well as the person, and per haps much better. But, what is thinking? People can agree about much that is thinking, and much that is not thinking; but they can't reach agreement because the word 'think' is not a scientific word with an exact meaning. A lot of the discussion is wasted breath because the persons are using different meanings of the word 'think'. People, however, have only had experience with machines that appear to think since 1944. It would be too early to say that after the next 200 years, machines will not be thinking. And to consider that machines can think gives people a big push to give to machines more and more work in thinking. 1. The underlined part in paragraph three is about computers used in ________. A. Education. B. Govemment. C. Sports. D. Industry. 2. What does 'this work' mean in paragraph four? A. Thinking. B. Teaching. C. Searching. D. Telling. 3. What is the main idea of paragraph five? A. There is much to say about thinking. B. People discuss a lot about thinking. C. There is no answer to what thinking is. D. People already know what thinking is. 4. What does the writer want to say in the passage? A. A machine will do any work in thinking like a human being. B. A machine can do better translation than human beings. C. A machine won't be able to beat every chess player. D. A machine will be able to make plan programs. 5. Which probably is the best title for the passage? A. What Is Thinking? B. Can Machines Think? C. Can Machines Be Taught to Think? D. Can Machines Beat All Checkers Players?
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【简答题】理想二极管D 1 ,D 2 构成的电路如题图所示,求I=______。
【单选题】现在我国损益表的格式一般为( )。
A.
单步式
B.
多步式
C.
报告式
D.
余额式
【单选题】下列句中的方框里,依次应填入的一组词是( )
A.
打破  闪烁  疏落 新鲜
B.
点破  闪烁  稀疏  清新
C.
点破  灿烂  疏落   清新
D.
打破  灿烂  稀疏  新鲜
【单选题】下列句中的方框里,依次应填入的一组词是( ) 1小屋的出现,________了山的寂寞。 2每个晚上,山下亮起________的万家灯火,山上闪出________的灯光。 3山上的空气特别 , 的空气使我觉得呼吸的都是香。
A.
打破 闪烁 疏落 新鲜
B.
点破 闪烁 稀疏 清新
C.
点破 灿烂 疏落 清新
D.
打破 灿烂 稀疏 新鲜
【单选题】假分数与它的倒数的关系是(  )
A.
小于
B.
等于
C.
大于
D.
大于或等于
【多选题】关于摩擦力的描述正确的是 ( )
A.
摩擦力的大小与正压力的大小有关
B.
摩擦力的大小与摩擦系数的大小有关
C.
粗糙平面的摩擦系数大于平滑面的摩擦系数
D.
滚动摩擦力系数最小
E.
滚动摩擦力是对圆形物体滚动的阻力
【单选题】汽车驱动力与附着力之间的关系是驱动力( )附着力。
A.
小于或等于
B.
大于或等于
C.
关于或小于
D.
大于等于
【简答题】下列下列句中的方框里,依次应填入的一组词是() 1小屋的出现,________了山的寂寞。 2每个晚上,山下亮起________的万家灯火,山上闪出________的灯光。 3例外的只有破晓或入暮,那时山上只有一片微光,一片________,一片宁谧。A. 打破 闪烁 疏落 安静 B. 点破 闪烁 稀疏 安静 C. 点破 灿烂 疏落 柔静 D. 打破 灿烂 稀疏 柔静
【简答题】若a是小于0的有理数,则2a与a的大小关系是(    ).
【单选题】理想二极管构成的电路如题1图(a)所示,设输入电压u i =5sinωtV,忽略二极管的正向压降,输出电压u o 为(    )
A.
1V
B.
2V
C.
3V
D.
4V
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