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历年考研英语阅读理解2002年02

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[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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