2025-06-18 17:07:49
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 robot-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.
46.Human ingenuity was initially demonstrated in ________.
[A] the use of machines to produce science fiction
[B] the wide use of machines in manufacturing industry
[C] the invention of tools for difficult and dangerous work
[D] the elite’s cunning tackling of dangerous and boring work
47.The word “gizmos” (Line 1, Paragraph 2) most probably means ________.
[A] programs
[B] experts
[C] devices
[D] creatures
48.According to the text, what is beyond man’s ability now is to design a robot that can ________.
[A] fulfill delicate tasks like performing brain surgery
[B] interact with human beings verbally
[C] have a little common sense
[D] respond independently to a changing world
49.Besides reducing human labor, robots can also ________.
[A] make a few decisions for themselves
[B] deal with some errors with human intervention
[C] improve factory environments
[D] cultivate human creativity
50.The author uses the example of a monkey to argue that robots are ________.
[A] expected to copy human brain in internal structure
[B] able to perceive abnormalities immediately
[C] far less able than human brain in focusing on relevant information
[D] best used in a controlled environment
难词生词ingenuity―智能
cunning―狡猾的，聪明的
burdensome―繁重的，累人的
gizmos―工具
assembly―装配
teller terminals―柜员终端
transaction―交易
miniaturization―缩微化
electronics―电子元件
surgery―外科手术
submillimeter―亚毫米
laborsaving―省力的
utility―作用
artificial intelligence―人工智能
transistor circuits―晶体管电路
microprocessor―微处理器
fraction―小数
glimpse―一瞥
instantaneously―讯速地
neuroscientists―神经科学家
长难句解析第一段末句
And if scientists have yet to create the mechanical version of science fiction, they have begun to come close.
本句要注意“yet to”的用法，它表示“尚未”；所以前半句是让步状语从句，意思是“即使……但是……”
第二段第一句
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.
本句主干是“the modern world is increasingly populated by intelligent gizmos”，后面跟了两个并列的定语从句，分别由“whose”引导
第四段末句
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.
此句开头是despite短语作让步状语，spell在这里指的是“时期”；“when it appeared…”是定语从句修饰前面的“1960s and1970s”这段时间。“it appeared that”中，it是形式主语，真正主语是that 从句。此句话真正的主句是“researchers lately have begun to extend that forecast…”；by+数字表示变化的量。
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全文翻译自从人类智能诞生以来，人们就不断地发明越来越多的精巧的工具来处理危险的、无聊的、繁重的或者是肮脏的工作。这种冲动催生了机器人技术――这种技术给机器赋予了各种人类的能力。哪怕科学家还尚未写出关于机械的科幻小说，距离那一步也不远了。
结果，当今世界越来越充满了智能工具。我们几乎注意不到这些工具，但是它们无所不在，并替代了很多人类劳作。伴随着机械臂有节奏的舞动，工厂发出阵阵轰鸣。我们用自动柜员机进行银行交易，交易完后还会听到机器发出礼貌的感谢。地铁也由不知疲倦的机器人驾驶。电子元件不断缩微化，机器也越做越小。现在有的机器人系统已经可以做一些脑部与骨骼手术，其精度达到了亚毫米级别，这比熟练医师单凭双手要精确得多。
但是如果机器人想要更进一步地减轻人类劳作，起码得能在减少人类监控的情况下做出一点独立决策――这个目标现在还是个巨大的挑战。NASA某机器人项目经理Dave Lavery 指出“尽管我们现在知道如何让机器人改正错误，但是我们现在还没办法教给机器人足够的‘常识’来和这个动态的世界进行有效互动”。
着实，追求真正的人工智能产生了多种结果。尽管在1960到70年代中，有很短一段时间，人们都很乐观，觉得在2010年前，晶体管电路和微处理器好像就可以复制人脑活动了。但是最近研究者认为，这个阶段可能要再延长几十年，甚至几百年。
他们努力想模拟人脑，却发现，人脑约有一千亿个神经细胞，要比人们之前想象的更加智能，而人类的认知就更是复杂得多了。他们制造出的机器人可以在受控的工厂环境下识别出机器面板上不到一毫米的误差。但是人脑可以迅速识别快速变化的情景，并立即忽略掉98%无关的信息。人脑可以飞速地注意到蜿蜒的林间道路边上的猴子，亦或是人山人海中的唯一一个可疑分子。世界上最先进的电脑系统还达不到这种能力，神经科学家尚不清楚我们是如何做到这一点的。
