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TED十佳演讲之神奇奥秘 艾莉森·高普尼克:婴儿在想什么?(5)

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If this is true, if these babies are designed to learn -- and this evolutionary story would say children are for learning, that's what they're for --
如果第二种解释是真的。那这些小宝宝天生就是学习的料,从进化论来看,他们天生就在学习,学习就是他们的本性——
we might expect that they would have really powerful learning mechanisms.
我们可以想象,他们可能有非常巧妙的学习技巧。
And in fact, the baby's brain seems to be the most powerful learning computer on the planet.
事实上,小孩子的大脑仿佛是整个星球上最强的计算机。
But real computers are actually getting to be a lot better. And there's been a revolution in our understanding of machine learning recently.
但真正的计算机其实暂时已经无法超越了。最近,在我们对机器学习的理解上发生了一场革命。
And it all depends on the ideas of this guy, the Reverend Thomas Bayes, who was a statistician and mathematician in the 18th century.
这场革命完全是靠这个人的想法,他就是神父托马斯贝斯,18世纪时的一个统计学家和数学家。
And essentially what Bayes did was to provide a mathematical way using probability theory to characterize, describe, the way that scientists find out about the world.
他最大的贡献是通过数学,使用机率定理描述了科学家探索世界的方式,并将其个性化。

艾莉森·高普尼克:婴儿在想什么?(5).png

So what scientists do is they have a hypothesis that they think might be likely to start with.

科学家们的方法是先准备一个假设,
They go out and test it against the evidence. The evidence makes them change that hypothesis.
然后为该假设找根据,根据会使他们改变假设。
Then they test that new hypothesis and so on and so forth. And what Bayes showed was a mathematical way that you could do that.
然后他们就开始新的假设,过程就是这样。贝斯将该过程转换为一个数学公式。
And that mathematics is at the core of the best machine learning programs that we have now.
数学在目前最好的机器学习项目开发中起了重要作用。
And some 10 years ago, I suggested that babies might be doing the same thing.
大约10年前,我提出过小孩的思考过程和科学家相同。
So if you want to know what's going on underneath those beautiful brown eyes, I think it actually looks something like this.
所以你想知道在他们漂亮的棕色眼睛下面是什么样的一个世界,我有自己的看法。
This is Reverend Bayes's notebook. So I think those babies are actually making complicated calculations with conditional probabilities that they're revising to figure out how the world works.
这是贝斯神父的笔记。我认为这些小孩子在做复杂的计算,通过自定的条件机率来理解世间万物。
All right, now that might seem like an even taller order to actually demonstrate.
当然,这个要实际说明很困难。
Because after all, if you ask even grownups about statistics, they look extremely stupid. How could it be that children are doing statistics?
因为就算你问大人统计问题,他们也会一问三不知。那孩子们怎么可能会做统计呢?

重点单词   查看全部解释    
describe [dis'kraib]

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vt. 描述,画(尤指几何图形),说成

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conditional [kən'diʃənəl]

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adj. 有条件的,假定的,假设的 n. [语]条件句

 
core [kɔ:]

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n. 果心,核心,要点
vt. 挖去果核

 
essentially [i'senʃəli]

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adv. 本质上,本来

 
planet ['plænit]

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n. 行星

 
evolutionary [.i:və'lu:ʃnəri]

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adj. 进化的,发展的,演变的

 
probability [.prɔbə'biliti]

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n. 可能性,或然率,机率

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hypothesis [hai'pɔθisis]

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n. 假设,猜测,前提

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evidence ['evidəns]

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n. 根据,证据
v. 证实,证明

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figure ['figə]

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n. 图形,数字,形状; 人物,外形,体型
v

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