考研英语阅读理解命题思路透析和真题揭秘(55)

Since the dawn of human ingenuity, people have devised ever more cunning tools to cope with work that is dangerous, boring, burdensome, or just plain nasty. That compulsion has resulted in robotics-the science of conferring various human capabilities on machines. And if scientists have yet to create the mechanical version of science fiction, they have begun to come close.

As a result, the modern world is increasingly populated by intelligent gizmos whose presence we barely notice but whose universal existence has removed much human labor. Our factories hum to the rhythm of robot assembly arms. Our banking is done at automated teller terminals that thank us with mechanical politeness for the transaction. Our subway trains are controlled by tireless robo-drivers. And thanks to the continual miniaturization of electronics and micro-mechanics, there are already robot systems that can perform some kinds of brain and bone surgery with submillimeter accuracy-far greater precision than highly skilled physicians can achieve with their hands alone.

But if robots are to reach the next stage of laborsaving utility, they will have to operate with less human supervision and be able to make at least a few decisions for themselves-goals that pose a real challenge. "While we know how to tell a robot to handle a specific error," says Dave Lavery, manager of a robotics program at NASA, "we can't yet give a robot enough ‘common sense' to reliably interact with a dynamic world."

Indeed the quest for true artificial intelligence has produced very mixed results. Despite a spell of initial optimism in the 1960s and 1970s when it appeared that transistor circuits and microprocessors might be able to copy the action of the human brain by the year 2010, researchers lately have begun to extend that forecast by decades if not centuries.

What they found, in attempting to model thought, is that the human brain's roughly one hundred billion nerve cells are much more talented-and human perception far more complicated-than previously imagined. They have built robots that can recognize the error of a machine panel by a fraction of a millimeter in a controlled factory environment. But the human mind can glimpse a rapidly changing scene and immediately disregard the 98 percent that is irrelevant, instantaneously focusing on the monkey at the side of a winding forest road or the single suspicious face in a big crowd. The most advanced computer systems on Earth can't approach that kind of ability, and neuroscientists still don't know quite how we do it.

从人类萌发了创造力，他们就一直在设计各种日益精巧的工具来处理那些危险、枯燥、繁重或者只是令人讨厌的工作。这种不得已的行为导致了机器人学科的产生--一门将人类的能力赋予机器的科学。如果说科学家们还没有在机械上实现科幻小说的幻想，那么他们也已经很接近这个目标了。

因此，现代世界日益充斥着各种智能装置，虽然我们几乎都注意不到它们，但它们的普遍存在已使人们摆脱了很多劳动。工厂里轰鸣着机器手臂生产线的节奏；自动柜员机处理银行业务，并且用机器语言有礼貌地感谢你的惠顾；地铁由不知疲倦的机器人来驾驶。由于电子器件和微观机械的结构不断小型化，现在已有一些机器人系统能够进行精确到亚毫米的脑部和骨髓手术，其精确性远远超过技术娴熟的医生仅仅用双手所能达到的水平。

但是如果机器人要进入帮助人们节省劳力的下一个阶段，它们的运行就应该在更大程度上无需受人监控，并且至少能够独立地做一些决定。这些目标给我们提出了真正的挑战。"虽然我们知道如何让机器人去处理一个特定的错误，"美国宇航局（NASA）的机器人项目经理戴维·拉维里说，"我们仍然不能赋予机器人以足够的‘常识'，使它们能够与不断变化的动态世界进行可靠的交流。"

实际上对真正的人工智能的探索已经产生了诸多不同的效果。虽然在20世纪60年代和70年代人们有过一段乐观的时期--那时候人们认为晶体管电路和微处理器的发展似乎将使他们在2010年能够模仿人类大脑的活动--但是最近研究人员已经把这个预测延后数十年，甚至数百年。

在试图建造思维模型的过程中，研究人员发现，人类大脑中的近1000亿个神经细胞远比以前想像的更聪明，人类的认知能力也比以前想像的更复杂。他们制造的机器人在严格控制的工厂环境里，能够在仪表盘上识别毫米以下的误差。但是人的大脑能够扫描一个快速变化的场景，迅速排除98％的不相干部分，立即聚焦于森林中婉蜒道路旁的一只猴子、或者人群中的一张可疑的脸。这点连地球上最先进的计算机系统也望尘莫及，而且神经学科学家至今仍然不知道我们是怎样做到这一点的。