2021年经济学人 自动驾驶汽车（1）（在线收听）

Science & technology

科技板块

AI for vehicles

自动驾驶汽车

Is it smarter than a seven-month-old

比七个月大的婴儿还聪明？

How to improve the intelligence of self-driving cars

如何提高自动驾驶汽车的智力

By the age of seven months, most children have learned that objects still exist even when they are out of sight.

大多数孩子在7个月大的时候就知道，有些东西虽然看不见，但确是存在的。

Put a toy under a blanket and a child that old will know it is still there, and that he can reach underneath the blanket to get it back.

如果把玩具放在毯子下面，他们就会知道玩具还在那里，然后伸手把玩具从毯子下面拿出来。

This understanding, of "object permanence", is a normal developmental milestone, as well as a basic tenet of reality.

这种对“物体恒存性”的理解是正常发展的里程碑，也是现实的基本原则。

It is also something that self-driving cars do not have. And that is a problem.

这也是自动驾驶汽车所没有的。这是一个问题。

Autonomous vehicles are getting better, but they still don't understand the world in the way that a human being does.

即便自动驾驶汽车越来越好，但它们仍无法像人类那样了解世界。

For a self-driving car, a bicycle that is momentarily hidden by a passing van is a bicycle that has ceased to exist.

对于一辆自动驾驶汽车来说，一辆被路过的货车暂时挡住的自行车就是一辆不存在的自行车。

This failing is basic to the now-widespread computing discipline that has arrogated to itself the slightly misleading moniker of artificial intelligence (AI).

这一缺点是如今被广泛应用的计算学科的基础，该学科自诩为人工智能(AI)，这个绰号有点让人误解。

Current AI works by building up complex statistical models of the world, but it lacks a deeper understanding of reality.

目前的人工智能是通过建立复杂的世界统计模型来工作的，但它缺乏对现实的更深层次的理解。

How to give AI at least some semblance of that understanding—the reasoning ability of a seven-month-old child, perhaps—is now a matter of active research.

如今，如何让人工智能具备至少一些类似的理解能力(比如一个7个月大的孩子的推理能力)是一个热门研究课题。

Modern AI is based on the idea of machine learning.

现代人工智能基于机器学习这一理念。

If an engineer wants a computer to recognise a stop sign, he does not try to write thousands of lines of code that describe every pattern of pixels which could possibly indicate such a sign.

如果工程师想让电脑识别一个停车标志，他不会写成千上万行描述每一个可能表示这种符号的像素模式的代码。

Instead, he writes a program that can learn for itself, and then shows that program thousands of pictures of stop signs.

相反，他会编写一个可以自我学习的程序，然后向该程序展示数千张停车标志的图片。

Over many repetitions, the program gradually works out what features all of these pictures have in common.

经过多次重复后，该程序能够逐渐找出所有这些图片的共同特征。