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.
解析手把手教你：
1. 第一段开头“Since the dawn of...”别直译成“自从黎明以来”，这里指“从人类智慧起源开始”。“cunning tools”别翻成“狡猾工具”，用“巧妙工具”或“智能工具”。“plain nasty”就是“非常脏/讨厌的工作”。
2. 第二段“gizmos”直接译成“装置”或“设备”。“hum to the rhythm of”译成“在...节奏中轰鸣”，体现工厂运转状态。“mechanical politeness”处理为“机械式的礼貌”，保持原文略带讽刺的语气。
3. 第三段关键在“laborsaving utility”，译成“节省劳力的实用性”。“dynamic world”必须译成“动态世界”，别用“变化的世界”。
4. 第四段“a spell of initial optimism”译成“最初一波乐观情绪”，“extend that forecast by decades”直接译为“将这个预测延长数十年”。
5. 最后一段“glimpse a rapidly changing scene”用“扫一眼快速变化的场景”，“disregard the 98 percent”译为“忽略98%无关信息”，保留具体数字。
核心考点：
答题口诀：
遇到长句先切块，定语从句往后甩，被动主动灵活翻，抽象名词找具体。
模板句式：
“正如...所说”“...的结果是”“事实上...”“最...的是...”
蒙题技巧：
代词指代往前找最近名词，陌生词汇看词根+上下文正负向，并列结构前后词性必一致。