歷年考研英語(yǔ)閱讀理解2002年02

[00:03.77]2002 Text2 [00:07.50]Since the dawn of human ingenuity, [00:10.22]people have devised ever more cunning tools [00:13.05]to cope with work that is dangerous, [00:15.66]boring, burdensome, or just plain nasty. [00:20.83]That compulsion has resulted in robotics [00:24.27]--the science of conferring various human [00:26.59]capabilities on machines. [00:29.12]And if scientists have yet to create [00:31.54]the mechanical version of science fiction, [00:34.27]they have begun to come close. [00:37.09]As a result, the modern world [00:39.51]is increasingly populated by intelligent gizmos [00:43.16]whose presence we barely notice [00:45.27]but whose universal existence [00:47.60]has removed much human labor. [00:50.42]Our factories hum to the rhythm of robot assembly arms. [00:54.87]Our banking is done at automated teller terminals [00:58.00]that thank us with mechanical politeness for the transaction. [01:03.24]Our subway trains are controlled by tireless robot-drivers. [01:07.98]And thanks to the continual miniaturization of electronics [01:12.22]and micro-mechanics, [01:14.03]there are already robot systems [01:15.94]that can perform some kinds of brain [01:17.97]and bone surgery with submillimeter accuracy [01:22.01]--far greater precision than highly skilled physicians [01:25.02]can achieve with their hands alone. [01:28.08]But if robots are to reach the next stage of [01:30.72]laborsaving utility, [01:32.53]they will have to operate with less human supervision [01:35.96]and be able to make at least a few decisions [01:38.48]for themselves--goals that pose a real challenge. [01:42.62]"While we know how to tell a robot [01:44.19]to handle a specific error," [01:46.50]says Dave Lavery, manager of a robotics program at NASA, [01:51.34]"we can't yet give a robot enough 'common sense' [01:54.77]to reliably interact with a dynamic world." [01:58.41]Indeed the quest for true artificial intelligence [02:02.25]has produced very mixed results. [02:05.67]Despite a spell of initial optimism in the 1960s and 1970s [02:10.91]when it appeared that transistor circuits [02:13.23]and microprocessors might be able to copy the action [02:16.47]of the human brain by the year 2010, [02:19.99]researchers lately have begun to extend [02:22.71]that forecast by decades if not centuries. [02:26.95]What they found, in attempting to model thought, [02:30.17]is that the human brain's roughly one hundred billion [02:33.09]nerve cells are much more talented [02:36.12]--and human perception far more complicated [02:38.94]--than previously imagined. [02:41.26]They have built robots [02:42.67]that can recognize the error of a machine panel [02:45.29]by a fraction of a millimeter in a controlled [02:48.22]factory environment. [02:50.43]But the human mind can glimpse a rapidly changing scene [02:54.16]and immediately disregard the 98 percent that is irrelevant, [02:58.70]instantaneously focusing on the monkey [03:01.02]at the side of a winding forest road [03:04.05]or the single suspicious face in a big crowd. [03:07.77]The most advanced computer systems on Earth [03:10.50]can't approach that kind of ability, [03:12.82]and neuroscientists still don't know quite how we do it.

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