考研英語閱讀理解命題思路透析和真題揭秘(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.

從人類萌發(fā)了創(chuàng)造力，他們就一直在設計各種日益精巧的工具來處理那些危險、枯燥、繁重或者只是令人討厭的工作。這種不得已的行為導致了機器人學科的產(chǎn)生--一門將人類的能力賦予機器的科學。如果說科學家們還沒有在機械上實現(xiàn)科幻小說的幻想，那么他們也已經(jīng)很接近這個目標了。

因此，現(xiàn)代世界日益充斥著各種智能裝置，雖然我們幾乎都注意不到它們，但它們的普遍存在已使人們擺脫了很多勞動。工廠里轟鳴著機器手臂生產(chǎn)線的節(jié)奏；自動柜員機處理銀行業(yè)務，并且用機器語言有禮貌地感謝你的惠顧；地鐵由不知疲倦的機器人來駕駛。由于電子器件和微觀機械的結(jié)構(gòu)不斷小型化，現(xiàn)在已有一些機器人系統(tǒng)能夠進行精確到亞毫米的腦部和骨髓手術(shù)，其精確性遠遠超過技術(shù)嫻熟的醫(yī)生僅僅用雙手所能達到的水平。

但是如果機器人要進入幫助人們節(jié)省勞力的下一個階段，它們的運行就應該在更大程度上無需受人監(jiān)控，并且至少能夠獨立地做一些決定。這些目標給我們提出了真正的挑戰(zhàn)。"雖然我們知道如何讓機器人去處理一個特定的錯誤，"美國宇航局（NASA）的機器人項目經(jīng)理戴維·拉維里說，"我們?nèi)匀徊荒苜x予機器人以足夠的‘常識'，使它們能夠與不斷變化的動態(tài)世界進行可靠的交流。"

實際上對真正的人工智能的探索已經(jīng)產(chǎn)生了諸多不同的效果。雖然在20世紀60年代和70年代人們有過一段樂觀的時期--那時候人們認為晶體管電路和微處理器的發(fā)展似乎將使他們在2010年能夠模仿人類大腦的活動--但是最近研究人員已經(jīng)把這個預測延后數(shù)十年，甚至數(shù)百年。

在試圖建造思維模型的過程中，研究人員發(fā)現(xiàn)，人類大腦中的近1000億個神經(jīng)細胞遠比以前想像的更聰明，人類的認知能力也比以前想像的更復雜。他們制造的機器人在嚴格控制的工廠環(huán)境里，能夠在儀表盤上識別毫米以下的誤差。但是人的大腦能夠掃描一個快速變化的場景，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、或者人群中的一張可疑的臉。這點連地球上最先進的計算機系統(tǒng)也望塵莫及，而且神經(jīng)學科學家至今仍然不知道我們是怎樣做到這一點的。