原文

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 sub millimeter 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 the1960s 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.

译文

从人类产生智慧初期至今,人们一直在设计越来越巧妙的工具来应付那些危险的、枯燥的、繁重的或者直接就是肮脏的工作。这种动力产生了机器人科学——一门将人类的能力赋予机器的科学。如果科学家们还没有创造出科幻小说的机械版本,他们也已经很接近这个目标了。

由此引起的结果是,现代世界已经充斥着越来越多的智能装置,尽管我们几乎都注意不到他们,但他们的普遍存在却节省了许多人类劳力。我们的工厂里轰鸣着机器人生产线的节奏;我们的金融服务在自动柜员机上完成,它们还会机械地、礼貌地感谢我们使用业务;我们的地铁车辆由不知疲倦的机器人司机驾驶。多亏了电子和微观机械仪器的不断缩小,现在已有一些机器人系统能够进行脑部和骨髓手术,准确性精确到亚毫米,远远超过熟练的医生用他们的双手所能达到的水平。

但是如果机器人要进入节省劳力的下一个阶段,他们必须能够在更少的人工监控下运行,并且至少能够独立地做一些决定。这些目标提出了一个真正的挑战。“虽然我们知道如何让机器人去纠正一个特定的错误,”NASA的一个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’,使它们能够与动态的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各种各样的结果。虽然刚开始在20世纪60和70年代有过一段乐观的时期,那时候看起来晶体管电路和微处理器的发展将使它们在2010年能够模仿人类大脑的活动——但是最近研究人员已经开始将这个预测延后了不是数百年至少也有数十年。

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1000亿个神经细胞要比以前想像的更聪明,人类的感知也比以前想像的更复杂。他们建造出来的机器人在严格控制的工厂环境里,能够在仪识别表盘上一毫米以下的误差。但是人的大脑能够扫描一个快速变化的场景,迅速排除98%的不相干的物体,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。地球上最先进的计算机系统也不能达到这种能力,并且神经学科学家仍然不知道我们是怎样做到这一点的。

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