Jeff Hawkins: How brain science will change computing

翻译人员: 陆政宜 Lawrence Lok 校对人员: Ken Zheng

I do two things:

我有两个专业，设计微型电脑和研究大脑

I design mobile computers and I study brains.

Today's talk is about brains and -- (Audience member cheers)

今天的演说是关于大脑的

Yay! I have a brain fan out there.

嘿，我们听众里面好像有大脑研究的粉丝

(Laughter)

（笑声）

请把我演说的首页播放

If I could have my first slide,

你们可以看到我演说的标题和我的两个专业资格

you'll see the title of my talk and my two affiliations.

So what I'm going to talk about is why we don't have a good brain theory,

我会先说为什么我们没有一个好的大脑理论

why it is important that we should develop one

研究出一个大脑理论的重要性和怎么应用

and what we can do about it.

I'll try to do all that in 20 minutes.

我会尝试在20分钟内完成。我有两个职业

I have two affiliations.

Most of you know me from my Palm and Handspring days,

你们可能认识我其中的职业和我的发明，Palm 和 Handspring 掌上电脑

but I also run a nonprofit scientific research institute

但我还有一个非盈利的研究院 ：

called the Redwood Neuroscience Institute in Menlo Park.

位于 美国 Menlo Park的Redwood(红木)神经系统科学研究院

We study theoretical neuroscience and how the neocortex works.

在那里我们研究神经系统科学理论

和研究 新(大脑)皮层 是怎么运作的

I'm going to talk all about that.

我将会讲解有关的研究

I have one slide on my other life, the computer life,

我有一页演说是关于我电脑方面的工作，这张就是

and that's this slide here.

These are some of the products I've worked on over the last 20 years,

这些是我在近 20 年来设计过的电子产品

starting from the very original laptop

由最早的笔记本到第一台手写笔记本

to some of the first tablet computers

and so on, ending up most recently with the Treo,

到最近的 微型笔记本 Treo

and we're continuing to do this.

而我们会继续这方面的工作

I've done this because I believe mobile computing

我干这些是因为我深信移动计算技术

is the future of personal computing,

是个人计算系统的未来，而我会尝试通过这些工作

and I'm trying to make the world a little bit better

来造福人群

by working on these things.

But this was, I admit, all an accident.

但我得承认这些都是巧合

I really didn't want to do any of these products.

我其实没有想过时间这些产品

Very early in my career

而在我刚刚开始工作的时候我决定

I decided I was not going to be in the computer industry.

我不会从事计算机行业

Before that, I just have to tell you

在说那个之前，让我先告诉你

about this picture of Graffiti I picked off the web the other day.

我在网上找到这个小图片，

I was looking for a picture for Graffiti that'll text input language.

我在网上找有关涂鸦的图片，

I found a website dedicated to teachers who want to make script-writing things

而发现这专为教师们而设的网站

他们教学中在黑板上写的，

across the top of their blackboard,

and they had added Graffiti to it, and I'm sorry about that.

而他们却把这涂鸦上了，真可惜，

(Laughter)

（听众的笑声）

So what happened was,

经过是这样的，我还年轻的时候，刚刚从Cornell 康奈尔大学工程学院毕业

when I was young and got out of engineering school at Cornell in '79,

是 1979 年， 我决定去 Intel 英特尔工作

I went to work for Intel and was in the computer industry,

and three months into that, I fell in love with something else.

我在从事计算机行业，3 个月后

我爱上另一个东西，我发现我选错了行业

I said, "I made the wrong career choice here,"

and I fell in love with brains.

而我爱上了大脑

This is not a real brain.

这不是真的大脑， 这是一张大脑的图画

This is a picture of one, a line drawing.

And I don't remember exactly how it happened,

但我不太记得是怎么发生的

but I have one recollection, which was pretty strong in my mind.

但我还记得一段挺强烈的记忆

In September of 1979,

1979 年 9 月，Scientific America(美国科学杂志)发表了

Scientific American came out with a single-topic issue about the brain.

一本关于大脑研究的特刊

It was one of their best issues ever.

那是该杂志中最好的一期。那特刊讨论脑细胞

They talked about the neuron, development, disease, vision

的发展，疾病，视觉和其它

and all the things you might want to know about brains.

关于大脑的课题。真的是很棒的

It was really quite impressive.

One might've had the impression we knew a lot about brains.

你可能认为我们对大脑很了解

But the last article in that issue was written by Francis Crick of DNA fame.

特邗里最后有 Francis Crick 写有关 DNA 的文章

Today is, I think, the 50th anniversary of the discovery of DNA.

今天应该是发现 DNA 的 50 周年

And he wrote a story basically saying, this is all well and good,

他(Francis Crick)写了一段，

大概意思是，

but you know, we don't know diddly squat about brains,

我们基本上对大脑一点都不认识

and no one has a clue how they work,

而没有人知道它怎么运作

so don't believe what anyone tells you.

所以别随便相信别人说的(以为我们很了了解大脑)

This is a quote from that article, he says:

他在文章里提到 ”我们现在显著地缺少的是 。。。“

"What is conspicuously lacking" -- he's a very proper British gentleman --

他是一个很传统的英国绅士， ”现在显著地缺少的是，

"What is conspicuously lacking is a broad framework of ideas

一个可以融入对大脑已经的不同想法和不同解释方式的框架“

in which to interpret these different approaches."

I thought the word "framework" was great.

我认为’框架‘这词用的很好

He didn't say we didn't have a theory.

他甚至没有提到’理论‘，他说，

He says we don't even know how to begin to think about it.

我们根本不知道怎么开始去想

我们连框架都没有

We don't even have a framework.

我们正处于 Thomas Kuhn 所说的规范前时期

We are in the pre-paradigm days, if you want to use Thomas Kuhn.

后来我就爱上大脑研究了，我想，

So I fell in love with this.

I said, look: We have all this knowledge about brains -- how hard can it be?

我们有这么多关于大脑的知识，能有多难呢？

It's something we can work on in my lifetime; I could make a difference.

后来这成为我毕生的工作， 我觉得我可以有所贡献，

So I tried to get out of the computer business, into the brain business.

我尝试离开计算机行业而专注大脑研究

First, I went to MIT, the AI lab was there.

首先我去了 MIT(麻省理工学院)的人工智能研究院，

I said, I want to build intelligent machines too,

我想，我也想设计和制作聪明的机器，

but I want to study how brains work first.

但我的想法是先研究大脑怎么运作

And they said, "Oh, you don't need to do that.

而他们说，呃，你不需要这样做

You're just going to program computers, that's all.

我们只需要计算机编程

I said, you really ought to study brains.

而我说，不，你应该先研究大脑。 他们说，呃，你知道吗，

They said, "No, you're wrong."

I said, "No, you're wrong," and I didn't get in.

你错了。而我说，不，你们错了，最后我没被取录

(Laughter)

（笑声）

I was a little disappointed -- pretty young --

但我真的有点失望，那时候年轻，但我再尝试

but I went back again a few years later,

几年后在加州的 Berkley(加州大学伯克利分校)

this time in California, and I went to Berkeley.

这次我尝试去学习生物研究方面

And I said, I'll go in from the biological side.

So I got in the PhD program in biophysics.

我开始攻读生物物理博士课程

I was like, I'm studying brains now. Well, I want to study theory.

我在学习大脑了，而我想学理论

They said, "You can't study theory about brains.

而他们说，不，你不可以学大脑的理论

You can't get funded for that.

这是不可以的，你不会拿到研究经费

And as a graduate student, you can't do that."

而作为研究生，没有研究经费是不可以的。我的天

So I said, oh my gosh.

I was depressed; I said, but I can make a difference in this field.

我很沮丧但我还坚信我可以在这一研究领域作出贡献

最后我回到计算机行业

I went back in the computer industry

and said, I'll have to work here for a while.

对自己说，我先工作，做些有意义的

That's when I designed all those computer products.

就是那时候我设计了你们认识的一系列的微型电子产品

(Laughter)

（笑声）

I said, I want to do this for four years, make some money,

我计划干四年，挣点钱，

I was having a family, and I would mature a bit,

组织自己的家庭，我可能会成熟点

and maybe the business of neuroscience would mature a bit.

也可能那时候神经系统科学也会成熟一点了

Well, it took longer than four years. It's been about 16 years.

结果干了比四年长多了，已经大概十六年

But I'm doing it now, and I'm going to tell you about it.

但我终于做到了，而我现在告诉你们

So why should we have a good brain theory?

那为什么我们需要有一个好的大脑理论呢？

Well, there's lots of reasons people do science.

嗯， 科学研究有很多目的

The most basic one is, people like to know things.

其中比较简单的是，我们喜欢了解各种的事物

We're curious, and we go out and get knowledge.

我们好奇，而我们渴求知识

Why do we study ants? It's interesting.

我们为什么研究蚂蚁？因为这个有趣

Maybe we'll learn something useful, but it's interesting and fascinating.

可能我们从中会学到一些很有用的知识，但本质上这研究很有趣

But sometimes a science has other attributes

有时候，科学有其他本质

which makes it really interesting.

令它很有趣

Sometimes a science will tell something about ourselves;

有时候科学会告诉我们一些关于我们自己的，

it'll tell us who we are.

告诉我们，我们到底是什么

Evolution did this and Copernicus did this,

这很罕有的，例如，进化论，哥白尼(Copernicus)

where we have a new understanding of who we are.

都让我们对自身有新一层的理解

And after all, we are our brains. My brain is talking to your brain.

毕竟，我们就是我们的大脑。我的大脑正在跟你们的大脑沟通

Our bodies are hanging along for the ride,

我们的身体只是随行的部分，但我的大脑正在跟你们的大脑沟通

but my brain is talking to your brain.

And if we want to understand who we are and how we feel and perceive,

如果我们想了解我们是什么和我们怎么去感受和察觉

我们就先要明白大脑是什么

we need to understand brains.

Another thing is sometimes science leads to big societal benefits, technologies,

又有时候科学会

让我们有新的科技和为社会带来很大好处

or businesses or whatever.

甚至商业，和其它。 而大脑科学研究也会有这些好处

This is one, too, because when we understand how brains work,

因为如果我们明白了大脑怎么运作，我们就可以

we'll be able to build intelligent machines.

制作有智能的机器，而这总体来说是好的

That's a good thing on the whole,

with tremendous benefits to society,

而且对社会带来好处

just like a fundamental technology.

就好像很基本的科技一样

So why don't we have a good theory of brains?

那为什么我们没有一个好的大脑理论？

People have been working on it for 100 years.

虽然人们已经研究了大概100多年了

Let's first take a look at what normal science looks like.

我们先看看一般的科学研究是怎么进行的

This is normal science.

这是一般的科学

Normal science is a nice balance between theory and experimentalists.

一般的科学是平衡于理论和实验的

The theorist guy says, "I think this is what's going on,"

比方说，理论家先认为是这样的，

the experimentalist says, "You're wrong."

而实验家说，不，你错了

It goes back and forth, this works in physics, this in geology.

反复的验证，你们明白吗？

物理学是这样研究的，地质学也是这样研究的，但这是一般的科学

But if this is normal science, what does neuroscience look like?

那神经系统科学研究又怎样进行呢？我们看看

This is what neuroscience looks like.

我们有巨多的数据，包括：解剖学的，生理学的和行为学的

We have this mountain of data,

which is anatomy, physiology and behavior.

You can't imagine how much detail we know about brains.

你们很难想象我们已经有多少数据

There were 28,000 people who went to the neuroscience conference this year,

今年的神经系统科学研讨会我们有 28000 个专家参与

and every one of them is doing research in brains.

而每一个都在研究大脑

A lot of data, but no theory.

很多的数据，但没有理论，可能有一点点，就像最上边的那小的可怜的箱子

There's a little wimpy box on top there.

And theory has not played a role in any sort of grand way

而在神经系统科学研究领域当中，理论从没有像它们在一般科学里的主导地位

in the neurosciences.

And it's a real shame.

这是很可惜的，为什么会这样呢？

Now, why has this come about?

If you ask neuroscientists why is this the state of affairs,

如果你问神经系统科学专家，为什么情况会这样？

first, they'll admit it.

他们会同意情况是这样，但如果你问为什么，他们会说

But if you ask them, they say,

there's various reasons we don't have a good brain theory.

有很多原因导致我们没有一个好的大脑理论

Some say we still don't have enough data,

有些专家会说，我们还没有足够的数据

we need more information, there's all these things we don't know.

我们要拿更多的数据，我们还有很多不明白的

Well, I just told you there's data coming out of your ears.

嗯， 我刚刚告诉过你们了

We have so much information, we don't even know how to organize it.

我们有太多的数据但不知道怎么去组织

What good is more going to do?

那就算有更多的数据又有何用？

Maybe we'll be lucky and discover some magic thing, but I don't think so.

可能我们会幸运的突然发现谜底，但我不认为会发生

This is a symptom of the fact that we just don't have a theory.

种种证据都在说明我们根本没有一个好的理论

We don't need more data, we need a good theory.

我们不需要更多的数据，我们只需要一个好的理论

Another one is sometimes people say,

另一些专家会说，大脑太复杂了

"Brains are so complex, it'll take another 50 years."

这研究会再花 50 年

I even think Chris said something like this yesterday, something like,

我想 Chris 昨天也说过类似的话

我不肯定 Chris 你所说的内容，但大概是，

it's one of the most complicated things in the universe.

(大脑研究)是宇宙中最复杂的。我不认同

That's not true -- you're more complicated than your brain.

你们都比大脑复杂，你们都有大脑

You've got a brain.

而且，大脑只是看似复杂，

And although the brain looks very complicated,

所以事物在弄明白前都是复杂的

things look complicated until you understand them.

That's always been the case.

我们可以说，

So we can say, my neocortex, the part of the brain I'm interested in,

新大脑皮层(neocortex)，大脑里面我们最感兴趣的部分，有 300 亿细胞

has 30 billion cells.

But, you know what? It's very, very regular.

但你们知道吗，它(新大脑皮层）非常有规律

In fact, it looks like it's the same thing repeated over and over again.

实际上，它就像同样的组织不停的重覆

It's not as complex as it looks. That's not the issue.

它不像想象中复杂，那不是问题

Some people say, brains can't understand brains.

有些人说，大脑不能明白大脑

Very Zen-like. Woo.

很玄，喔

(Laughter)

（笑声）

You know, it sounds good, but why? I mean, what's the point?

听起来挺好，但有什么用？

It's just a bunch of cells. You understand your liver.

它只是一堆细胞，就好像你了解你的肝脏

It's got a lot of cells in it too, right?

肝脏也是一堆细胞是吗

So, you know, I don't think there's anything to that.

所以，我不见得大脑有什么分别的

And finally, some people say,

还有一些人说

"I don't feel like a bunch of cells -- I'm conscious.

“我不认为自己只是一堆细胞，我是神志清醒的

I've got this experience, I'm in the world.

我又很多经历，我处在一世界，明白不，

I can't be just a bunch of cells."

我不可能只是一堆细胞”

Well, people used to believe there was a life force to be living,

人们曾经相信有‘生命力’

and we now know that's really not true at all.

我们现在已经知道那根本不正确

And there's really no evidence,

而且根本就没有证据证明，除了人类之外

other than that people just disbelieve that cells can do what they do.

只是不相信一堆细胞能做人能做的事

So some people have fallen into the pit of metaphysical dualism,

有些人沉迷于形而上学唯物论

some really smart people, too, but we can reject all that.

包括一些很聪明的人，但我们可以全否定

(Laughter)

（笑声）

不，我会告诉你们另外的

No, there's something else,

something really fundamental, and it is:

很基础很根本的

another reason why we don't have a good brain theory

原因导致我们无法拥有一个好的大脑理论

is because we have an intuitive, strongly held but incorrect assumption

因为我们有很根深蒂固

但错误的假设，这阻止了我们去寻找答案

that has prevented us from seeing the answer.

There's something we believe that just, it's obvious, but it's wrong.

我们相信这个明显的假设，但它是错的

Now, there's a history of this in science and before I tell you what it is,

这在科学研究中是有先例的，但在说那之前，

I'll tell you about the history of it in science.

我先告诉你一些科学的历史

Look at other scientific revolutions --

看看其它的科学革命

the solar system, that's Copernicus,

比方说哥白尼的天体运行学说

Darwin's evolution, and tectonic plates, that's Wegener.

达尔文的进化论，和魏格纳的大陆漂移学说

它们跟大脑理论有很多共同点

They all have a lot in common with brain science.

First, they had a lot of unexplained data. A lot of it.

第一，很多无法解析的数据

But it got more manageable once they had a theory.

但有理论后就变的容易处理了

The best minds were stumped -- really smart people.

那时候众多很聪明的学者都被困惑

We're not smarter now than they were then;

我们并不比他们聪明，

it just turns out it's really hard to think of things,

只是想出理论是很困难的，

but once you've thought of them, it's easy to understand.

但一想到了，就很容易明白

My daughters understood these three theories,

我的女儿都明白那三个理论

的大概，在幼儿园的时候就明白

in their basic framework, in kindergarten.

It's not that hard -- here's the apple, here's the orange,

所以并不是那么困难，像这有一苹果，这一橘子，

the Earth goes around, that kind of stuff.

地球围着走，等等

Another thing is the answer was there all along,

还有，答案早就存在

but we kind of ignored it because of this obvious thing.

我们只是忽视了而已

It was an intuitive, strongly held belief that was wrong.

第二，有很根深蒂固但错的想法

In the case of the solar system,

天体运行学的比方，地球在自转

the idea that the Earth is spinning,

the surface is going a thousand miles an hour,

地球表面在以千多英里在移动，

and it's going through the solar system at a million miles an hour --

同时地球在太阳系里的轨道以百万多英里运行

this is lunacy; we all know the Earth isn't moving.

疯了吧，我们都知道地球不在动

Do you feel like you're moving a thousand miles an hour?

你感觉到我们在以千多英里移动吗？

肯定没有，还有人说

If you said Earth was spinning around in space and was huge --

它(地球)在太空里自转而它很大

they would lock you up, that's what they did back then.

会把你锁上，他们当时是这样想的

（笑声）

So it was intuitive and obvious. Now, what about evolution?

这是显而易见的，我们再看看进化论

Evolution, same thing.

我们教孩子圣经里面说

We taught our kids the Bible says God created all these species,

上帝创造万物，猫是猫，狗是狗

cats are cats; dogs are dogs; people are people; plants are plants;

人是人，植物是植物，他们都不会变的

they don't change.

诺亚(Noah) 把他们都放进方舟，等等

Noah put them on the ark in that order, blah, blah.

The fact is, if you believe in evolution, we all have a common ancestor.

事实上，如果你相信进化论，我们都有共同的祖先，

We all have a common ancestor with the plant in the lobby!

我们跟大厅里的植物也有共同的祖先

This is what evolution tells us. And it's true. It's kind of unbelievable.

进化论是这样说的，而这是这真的，虽然有点难以置信，

And the same thing about tectonic plates.

大陆漂移学说也一样，

All the mountains and the continents

所有高山和大洲都在浮动

are kind of floating around on top of the Earth.

于地球上，听起来好像不合情理

It doesn't make any sense.

So what is the intuitive, but incorrect assumption,

那什么是直觉但错的假设

that's kept us from understanding brains?

阻止我们理解大脑呢？

I'll tell you. It'll seem obvious that it's correct. That's the point.

我现在就告诉你们，而且很明显是正确的，

那才是重点对吗？然后我会提出论据，

Then I'll make an argument why you're incorrect on the other assumption.

为什么其它的假设是错误的

The intuitive but obvious thing is:

直觉告诉我们智慧

somehow, intelligence is defined by behavior;

界定于行为

we're intelligent because of how we do things

我们聪明因为我们做事的方法

and how we behave intelligently.

和我们行为上表现聪明，我会告诉你们这想法是错的

And I'm going to tell you that's wrong.

Intelligence is defined by prediction.

智慧应该界定于推测能力

I'm going to work you through this in a few slides,

我会用这几张笔记

and give you an example of what this means.

给你们看看一例子， 这是一系统，

Here's a system.

Engineers and scientists like to look at systems like this.

工程师喜欢看系统，科学家也喜欢，

They say, we have a thing in a box. We have its inputs and outputs.

我们有一箱子，我们有输入和输出

The AI people said, the thing in the box is a programmable computer,

人工智能专家会说，那箱子里面是可编程计算机

because it's equivalent to a brain.

因为它等同大脑，而我们输入数据，

We'll feed it some inputs and get it to do something, have some behavior.

我们会得到输出的行为

艾伦.图灵(Alan Turing)的图灵测试说，

Alan Turing defined the Turing test, which essentially says,

如果行为跟人类接近就是有智慧的

we'll know if something's intelligent if it behaves identical to a human --

这是测度智慧的行为指标，

a behavioral metric of what intelligence is

that has stuck in our minds for a long time.

而我们被这想法困住了很长时间

Reality, though -- I call it real intelligence.

实际上，我称这为真正智慧，

Real intelligence is built on something else.

真正智慧是建筑于其它层面上的

We experience the world through a sequence of patterns,

我们通过一系列的模式来感受世界环境，然后贮存，

and we store them, and we recall them.

再回想，当我们回想时，我们会比较和对应

When we recall them, we match them up against reality,

实际情况，就这样我们不断的推测

and we're making predictions all the time.

It's an internal metric; there's an internal metric about us,

这是永恒的指标，一个测度我们对世界环境了解的指标和

saying, do we understand the world, am I making predictions, and so on.

我是否在推测环境，等等

You're all being intelligent now, but you're not doing anything.

你们都在表现有智慧会的行为中，虽然你们什么对没有做

可能你在搔痒，可能在挖鼻子 ，

Maybe you're scratching yourself, but you're not doing anything.

但没有在做什么特别的，

But you're being intelligent; you're understanding what I'm saying.

但你们还是有理性有智慧的，你们明白我在说什么，

Because you're intelligent and you speak English,

因为你们都有智慧，而你们都会英语，

you know the word at the end of this

你们都知道我说这句 --

子

sentence.

The word came to you; you make these predictions all the time.

你们都猜到那字，因为你们不断的推测，

What I'm saying is,

而我想说，

the internal prediction is the output in the neocortex,

新大脑皮层的输出就是不断的推测，

推测导致有理性有智慧的行为

and somehow, prediction leads to intelligent behavior.

Here's how that happens:

而过程是这样的，我们从大脑里没有智慧的部分开始，

Let's start with a non-intelligent brain.

我认为我们脑里面有部分是没有智慧的，是古老的，

I'll argue a non-intelligent brain, we'll call it an old brain.

And we'll say it's a non-mammal, like a reptile,

它甚至不属于哺乳类的，是属于爬行类年代的，

say, an alligator; we have an alligator.

比方说，鳄鱼，

And the alligator has some very sophisticated senses.

鳄鱼有很复杂强大的感官系统，

It's got good eyes and ears and touch senses and so on,

有很好的眼睛，耳朵，触觉，等等

a mouth and a nose.

还有口和鼻， 也有很复杂的行为，

It has very complex behavior.

It can run and hide. It has fears and emotions. It can eat you.

会走会躲，会害怕会有情绪，会吃人，

It can attack. It can do all kinds of stuff.

会攻击， 等等

But we don't consider the alligator very intelligent,

但我们不会视鳄鱼为很有智慧，不像人类的智慧，

not in a human sort of way.

But it has all this complex behavior already.

虽然它已拥有很复杂的行为，

Now in evolution, what happened?

进化论里怎么说的？

First thing that happened in evolution with mammals

哺乳类的进化，

is we started to develop a thing called the neocortex.

从开发新大脑皮层开始，

I'm going to represent the neocortex by this box on top of the old brain.

我们用这个来代表新大脑皮层，

这个在(老)小脑上面的箱子，

Neocortex means "new layer." It's a new layer on top of your brain.

新大脑皮层的解释是大脑上面的新一层，

It's the wrinkly thing on the top of your head

它看上去是皱褶着的

that got wrinkly because it got shoved in there and doesn't fit.

因为它被挤进去而没有空间了，

(Laughter)

（笑声）

Literally, it's about the size of a table napkin

是真的！它大概是一张台布的大小

and doesn't fit, so it's wrinkly.

而放不下，所以就皱褶起来了，现在我们看看我画 的这个，

Now, look at how I've drawn this.

The old brain is still there.

(旧)小脑还在这里，那鳄鱼的脑袋还在，

You still have that alligator brain. You do. It's your emotional brain.

你们都有，是你脑里情绪和感官的部分

It's all those gut reactions you have.

它负责所有直觉，本能反应，

On top of it, we have this memory system called the neocortex.

在它上面，是我们说的新大脑皮层，

And the memory system is sitting over the sensory part of the brain.

它是包围着脑里感官系统的记忆系统，

So as the sensory input comes in and feeds from the old brain,

感官输入先进小脑，

it also goes up into the neocortex.

再走上新大脑皮层，而新大脑皮层只是记忆着，

And the neocortex is just memorizing.

It's sitting there saying, I'm going to memorize all the things going on:

它记着所以发生的事情，

where I've been, people I've seen, things I've heard, and so on.

像去了哪里，见过的人，听过的事，等等，

And in the future, when it sees something similar to that again,

在以后见到类似的情况，

in a similar environment, or the exact same environment,

类似的环境，或一样的环境，

it'll start playing it back: "Oh, I've been here before,"

它会把记忆‘重播’，

就会发现以前来过这地方，而如果你曾经来过这里，

and when you were here before, this happened next.

你记得什么会发生，让你可以猜测将来

It allows you to predict the future.

It literally feeds back the signals into your brain;

就好象，外界的信号传入大脑，

they'll let you see what's going to happen next,

让你看到什么将会发生，

will let you hear the word "sentence" before I said it.

就像刚才你们会知道我准备会说的词

And it's this feeding back into the old brain

正是这个信号的传递回小脑

that will allow you to make more intelligent decisions.

让你们去作出很理性的决定

This is the most important slide of my talk, so I'll dwell on it a little.

这是我演说里最重要的一点，

And all the time you say, "Oh, I can predict things,"

所以，你们不断的在猜测食物，

so if you're a rat and you go through a maze, and you learn the maze,

如果我们像白老鼠一样在走迷宫，那就学习那个迷宫，

next time you're in one, you have the same behavior.

下次再走，行为一样，

But suddenly, you're smarter; you say, "I recognize this maze,

但会变聪明了，

因为会认得那迷宫，知道怎么走，

I know which way to go; I've been here before; I can envision the future."

曾经走过，可以预想，

That's what it's doing.

This is true for all mammals --

人类和其他哺乳类动物都会这样，

in humans, it got a lot worse.

人类的情况会更极端，

Humans actually developed the front of the neocortex,

我们会发展新大脑皮层的前端，

called the anterior part of the neocortex.

然后大自然会弄一小把戏

And nature did a little trick.

It copied the posterior, the back part, which is sensory,

将新大脑皮层后端，感官的部分，拷贝

and put it in the front.

到前端

Humans uniquely have the same mechanism on the front,

人类大脑前端有独特的构造，跟后端一样

but we use it for motor control.

但我们用来控制运动

So we're now able to do very sophisticated motor planning, things like that.

所以我们可以进行很复杂的计划运动，

I don't have time to explain, but to understand how a brain works,

这个我们先不说，要理解大脑怎么运作，

you have to understand how the first part of the mammalian neocortex works,

我们先了解第一代哺乳类动物新大脑皮层的运作，

和怎么去贮存资料样式和作出猜测

how it is we store patterns and make predictions.

我先列几个猜测的例子

Let me give you a few examples of predictions.

I already said the word "sentence."

我已说过句子了，在音乐中，

In music, if you've heard a song before,

如果你听过一首歌，如果你听过吉尔(Jill)唱歌，

when you hear it, the next note pops into your head already --

当她唱的时候，下一个音符就会在你脑海中了，

you anticipate it.

你会有预感，如果是一张音乐专辑，

With an album, at the end of a song, the next song pops into your head.

听完一首歌，下一首已在你脑海出现，

It happens all the time, you make predictions.

这情况经常发生，你在不断的猜测，

I have this thing called the "altered door" thought experiment.

我有一个用门的实验，

It says, you have a door at home;

是这样的，你家有一门，

when you're here, I'm changing it --

当你在这里的时候，我去把它改了，我们有一个人，

I've got a guy back at your house right now, moving the door around,

现在在你家，把门改过来，

moving your doorknob over two inches.

他会把你的门把手移 2 寸，

When you go home tonight, you'll put your hand out, reach for the doorknob,

当你今晚回家，找把手开门，

你会发现把手

notice it's in the wrong spot

在错的位置，你会感觉，有点问题，

and go, "Whoa, something happened."

It may take a second, but something happened.

可能等一秒才发现问题，但感觉到不对劲，

I can change your doorknob in other ways --

我也可以用别的方法改变门把手，

make it larger, smaller, change its brass to silver, make it a lever,

弄大一点或小一点，从铜改为银的，

也可以把门改了，改颜色，

I can change the door; put colors on, put windows in.

加玻璃，有很多方法去改，

I can change a thousand things about your door

而就在你开门的两秒钟，

and in the two seconds you take to open it,

你会发现不对劲，

you'll notice something has changed.

Now, the engineering approach, the AI approach to this,

那传统的工程或人工智能对这问题的方法是，

is to build a door database with all the door attributes.

起一个门的数据库，有所以关于门的参数，

And as you go up to the door, we check them off one at time:

当你到了门前，便进数据库一个一个比较，

door, door, color ...

所以样式的门，不同颜色的，

We don't do that. Your brain doesn't do that.

我们人类肯定不会这样做的，你们的大脑不会这样运作，

Your brain is making constant predictions all the time

你的大脑会不停的作出猜测，

about what will happen in your environment.

对你附近环境有可能会发生的作出猜测，

As I put my hand on this table, I expect to feel it stop.

当我把手放着桌上，我预料手会停在上面，

When I walk, every step, if I missed it by an eighth of an inch,

当我走路的时候，每一步，如果只是差了八分之一寸，

I'll know something has changed.

我会知道有情况改变，

You're constantly making predictions about your environment.

你们不停的对身边环境作出猜测，

I'll talk about vision, briefly.

让我们看看视觉系统，这是一张女人的图片，

This is a picture of a woman.

When we look at people, our eyes saccade over two to three times a second.

当你看人的时候，你的眼神会停留，

大概两到三秒，

We're not aware of it, but our eyes are always moving.

你应该意识不到，但你的眼球不停在动，

所以当你看一个人的脸，

When we look at a face, we typically go from eye to eye to nose to mouth.

你通常会从看着眼到鼻到口，

When your eye moves from eye to eye,

如果你在看眼的位置的时候，

if there was something else there like a nose,

出现像鼻子的东西，

you'd see a nose where an eye is supposed to be and go, "Oh, shit!"

你看见鼻子长在眼睛的地方，

你会吓一跳

(Laughter)

"There's something wrong about this person."

（笑声）

这个人有点问题，

That's because you're making a prediction.

这都以为你在推测，

It's not like you just look over and say, "What am I seeing? A nose? OK."

不会是因为你在看东西而在想着到底是什么，

你不会预料看到一鼻子在眼睛的位置，

No, you have an expectation of what you're going to see.

（笑声）

Every single moment.

现在我们看看我们怎样测试智慧的，

And finally, let's think about how we test intelligence.

We test it by prediction: What is the next word in this ...?

我们用猜测能力来测试的，下一个词是什么？

This is to this as this is to this. What is the next number in this sentence?

这个配这个，那个配那个，下一个数是什么？

Here's three visions of an object. What's the fourth one?

这是这东西的三个看法，

第四个是什么？我们就是这样测试猜测能力

That's how we test it. It's all about prediction.

So what is the recipe for brain theory?

那什么是大脑理论的秘诀？

First of all, we have to have the right framework.

第一，我们需要合适的框架，

And the framework is a memory framework,

一个记忆的框架，

not a computational or behavior framework,

不是计算的或行为的框架，是一个记忆的框架，

it's a memory framework.

How do you store and recall these sequences of patterns?

你怎么贮存和回忆有关联的样式组合？这是时间空间样式，

It's spatiotemporal patterns.

Then, if in that framework, you take a bunch of theoreticians --

然后，如果在框架里，我们找一群理论研究者，

biologists generally are not good theoreticians.

生物学者一般不是好的理论学者，

不一定，但历史里没有好的生物理论，

Not always, but generally, there's not a good history of theory in biology.

I've found the best people to work with are physicists,

我觉得物理学者，

engineers and mathematicians,

工程师和数学家都适合，他们想法都很规则很系统的，

who tend to think algorithmically.

Then they have to learn the anatomy and the physiology.

然后他们要学解剖学和生理学，

You have to make these theories very realistic in anatomical terms.

我们需要让这理论非常的实在，从解剖学角度来看，

如果有人解释大脑理论时，

Anyone who tells you their theory about how the brain works

and doesn't tell you exactly how it's working

而不告诉你大脑里面怎么运作，

and how the wiring works --

和大脑各部分的联系，那就不是真正的理论了

it's not a theory.

And that's what we do at the Redwood Neuroscience Institute.

而我们的研究院正是研究这方面的，

I'd love to tell you we're making fantastic progress in this thing,

我很希望有更多的时间告诉你们最近的研究成果

and I expect to be back on this stage sometime in the not too distant future,

我以后会再回来

在不久的将来，来告诉大家

to tell you about it.

I'm really excited; this is not going to take 50 years.

我真的很兴奋，这肯定不会花 50 年，

What will brain theory look like?

那大脑理论像什么呢？

First of all, it's going to be about memory.

首先，它会是一个关于记忆的理论，

Not like computer memory -- not at all like computer memory.

不是计算机的记忆

It's very different.

很不一样

It's a memory of very high-dimensional patterns,

是多维样式的记忆，就像从你们眼睛输出的，

like the things that come from your eyes.

It's also memory of sequences:

它也会是很多组有关联记忆，

you cannot learn or recall anything outside of a sequence.

你不会学习或回忆没有关联的东西，

A song must be heard in sequence over time,

就像一首歌在时间上是有先后的记忆

and you must play it back in sequence over time.

要回忆起来也是一连串的回忆，

And these sequences are auto-associatively recalled,

这些关联记忆组群会在回忆时会自动联系连结，所以当我们看到，

so if I see something, I hear something, it reminds me of it,

听到一些类似的东西，就会把记忆重播，

and it plays back automatically.

It's an automatic playback.

是自动的重播，最后输出是未来的猜测，

And prediction of future inputs is the desired output.

And as I said, the theory must be biologically accurate,

我们提过，这理论在生物学上合理，

it must be testable and you must be able to build it.

能测试的，可推理出来的

If you don't build it, you don't understand it.

如果你不推理出来，你不会明白，还有一张笔记，

One more slide.

What is this going to result in?

这研究结果有什么作用呢？我们真的会制造有智慧的机器？

Are we going to really build intelligent machines?

这是肯定的，而会跟我们想像的不一样，

Absolutely. And it's going to be different than people think.

我绝不怀疑，

No doubt that it's going to happen, in my mind.

First of all, we're going to build this stuff out of silicon.

首先，我们会用硅来制造，

The same techniques we use to build silicon computer memories,

制造计算机内存的方法，

we can use here.

我们可以用上，

But they're very different types of memories.

但是将会是很不一样的记忆体，

And we'll attach these memories to sensors,

我们会把感应器和这些记忆体连接上，

and the sensors will experience real-live, real-world data,

感应器会接受真实环境的数据，

and learn about their environment.

而这些机器会学习它们的环境，

Now, it's very unlikely the first things you'll see are like robots.

一开始发展出来就像机器人的可能比较低，

Not that robots aren't useful; people can build robots.

不是说机器人没有用处或我们制造不出来，

But the robotics part is the hardest part. That's old brain. That's really hard.

但是机器人硬件是最难制造的，那像旧(小)脑，

The new brain is easier than the old brain.

(新)大脑比小脑容易，

So first we'll do things that don't require a lot of robotics.

所以刚开始我们会造一些不需要太多机器人硬件的，

So you're not going to see C-3PO.

应该不会见到 C-3PO

You're going to see things more like intelligent cars

你会见到比较多类似，智能车，

that really understand what traffic is, what driving is

会理解交通情况和驾驶，

and have learned that cars with the blinkers on for half a minute

和懂得比方说，有些车的转向显示灯亮了半分钟

probably aren't going to turn.

应该不是真的想转向，

(Laughter)

（笑声）

We can also do intelligent security systems.

我们也可以制造智能保安系统

Anytime we're basically using our brain but not doing a lot of mechanics --

任何需要很多大脑分析但不需要很多的机械的领域，

those are the things that will happen first.

都会是在初期有发展的。

But ultimately, the world's the limit.

但最终，会发展到各方面，

I don't know how this will turn out.

我也不知道会发展成怎样，

I know a lot of people who invented the microprocessor.

我认识很多发明微处理器的专家，

And if you talk to them,

你如果问他们，那时候他们知道正在做很有意义的事，

they knew what they were doing was really significant,

but they didn't really know what was going to happen.

但也不知道会发展成什么，

They couldn't anticipate cell phones and the Internet

他们也没有预计手机，互联网等等的发展，

and all this kind of stuff.

They just knew like, "We're going to build calculators

他们只知道，会制造计算机，

and traffic-light controllers.

交通灯的控制器等等，但都感觉到是很重大的，

But it's going to be big!"

In the same way, brain science and these memories

同样地，大脑的研究和记忆体，

are going to be a very fundamental technology,

将会成为很基本的科技，它将会在未来100年带领着

and it will lead to unbelievable changes in the next 100 years.

一些很难想象的发展

And I'm most excited about how we're going to use them in science.

而令我最兴奋的是我们怎样利用这科技，

So I think that's all my time -- I'm over,

我想我已经超过限时了，我的演讲就在这

and I'm going to end my talk right there.

结束