The mathematician who cracked Wall Street | Jim Simons

翻译人员: Chen Livia 校对人员: dahong zhang

Chris Anderson: You were something of a mathematical phenom.

您可以说是数学界出类拔萃的人物了

You had already taught at Harvard and MIT at a young age.

年轻时就已经在哈佛和麻省理工授课了

And then the NSA came calling.

后来NSA主动找上门来

What was that about?

那是怎么回事呢？

Jim Simons: Well the NSA -- that's the National Security Agency --

NSA就是国家安全局

they didn't exactly come calling.

确切来说 也不是他们找上我的

They had an operation at Princeton, where they hired mathematicians

他们在普林斯顿专设有一个机构

to attack secret codes and stuff like that.

专门雇佣数学家 用于破解密码之类的

And I knew that existed.

我本来就知道这个机构的存在

And they had a very good policy,

他们的政策非常诱人

because you could do half your time at your own mathematics,

因为你可以把半数时间花在你自己的数学研究上

and at least half your time working on their stuff.

还有至少一半的时间要为他们解决事务

And they paid a lot.

而且他们给的报酬很丰厚

So that was an irresistible pull.

这有着无法抵抗的诱惑力

So, I went there.

所以我就去那儿了

CA: You were a code-cracker.

所以你曾是个密码破译者？

JS: I was.

对

CA: Until you got fired.

直到你被炒了？

JS: Well, I did get fired. Yes.

嗯我确实被炒了，对

CA: How come?

为什么呢？

JS: Well, how come?

啊 为什么呢

I got fired because, well, the Vietnam War was on,

我之所以被解雇是因为

当时正值越南战争之际 我组织内的最高领导是个好战分子

and the boss of bosses in my organization was a big fan of the war

and wrote a New York Times article, a magazine section cover story,

他给《纽约时报》杂志版块的封面故事

about how we would win in Vietnam.

写了一篇关于 我们如何在越南获得胜利的文章

And I didn't like that war, I thought it was stupid.

我不喜欢那场战争 我觉得那很蠢

And I wrote a letter to the Times, which they published,

我给《纽约时报》写了封信 他们后来刊登了出来

saying not everyone who works for Maxwell Taylor,

那封信写了 如果还有人记得Maxwell Taylor（就是他最高领导）的话

if anyone remembers that name, agrees with his views.

不是每个在他手下工作的人 都同意他的观点

And I gave my own views ...

我给出了我自己的观点

CA: Oh, OK. I can see that would --

好吧 我可以想见那将……

JS: ... which were different from General Taylor's.

（我的观点）是和Taylor将军不一样的

But in the end, nobody said anything.

但最后 也没人说什么

But then, I was 29 years old at this time, and some kid came around

后来，我当时是29岁，有个孩子来采访我

and said he was a stringer from Newsweek magazine

说他是《新闻周刊》的特约记者

and he wanted to interview me and ask what I was doing about my views.

他想要与我面谈 问我是如何实践我的观点的

And I told him, "I'm doing mostly mathematics now,

我告诉他 我现在（战争期间）主要是做数学研究

and when the war is over, then I'll do mostly their stuff."

战争结束后 我才会主要给他们做事

Then I did the only intelligent thing I'd done that day --

接着我做了那天最明智的一件事

I told my local boss that I gave that interview.

我告诉我当地的上司 我接受了那个访问

And he said, "What'd you say?"

他问我 你怎么说的？

And I told him what I said.

我就把我说的告诉他了

And then he said, "I've got to call Taylor."

然后他说：“我必须要给Taylor打个电话”

He called Taylor; that took 10 minutes.

他打给了Taylor 花了十分钟

I was fired five minutes after that.

又过了五分钟 我就被解雇了

CA: OK.

OK

JS: But it wasn't bad.

但那并不是一件坏事

CA: It wasn't bad, because you went on to Stony Brook

那并不糟 因为你接下来去了纽约石溪大学

and stepped up your mathematical career.

使你的数学生涯更上一层楼

You started working with this man here.

你开始和这个人一起共事

Who is this?

这是谁呢

JS: Oh, [Shiing-Shen] Chern.

噢 陈（陈省身）

Chern was one of the great mathematicians of the century.

陈是本世纪最伟大的数学家之一

I had known him when I was a graduate student at Berkeley.

我在伯克利当研究生的时候 就已经知道他了

And I had some ideas,

我带着一些想法去找他

and I brought them to him and he liked them.

他很喜欢这些想法

Together, we did this work which you can easily see up there.

我们一起开展这项理论研究 你可以在这里看到

There it is.

就是这个

CA: It led to you publishing a famous paper together.

基于这项研究 你们一起发表了一篇著名的文章

Can you explain at all what that work was?

你可以给大家解释一下这项研究吗？

JS: No.

不

(Laughter)

（笑）

JS: I mean, I could explain it to somebody.

我的意思是 我可以向某些人解释

(Laughter)

（笑）

CA: How about explaining this?

要不讲下这个？

JS: But not many. Not many people.

但不是很多人

CA: I think you told me it had something to do with spheres,

我记得你告诉我 它和球体有关

so let's start here.

我们从这里说起吧

JS: Well, it did, but I'll say about that work --

确实 但我要讲一讲那项研究

it did have something to do with that, but before we get to that --

它确实和这球体有关 但在此之前我要说

that work was good mathematics.

这是一个非常棒的数学理论

I was very happy with it; so was Chern.

我非常喜欢研究它的过程，陈也一样

It even started a little sub-field that's now flourishing.

它甚至开创了一个现在很繁荣的副领域

But, more interestingly, it happened to apply to physics,

但更有趣的是 它正巧可以应用于物理

something we knew nothing about -- at least I knew nothing about physics,

一个我们完全不了解的东西 至少我是完全不了解的

and I don't think Chern knew a heck of a lot.

我觉得陈也不会了解太多

And about 10 years after the paper came out,

在文章发表大约十年后

a guy named Ed Witten in Princeton started applying it to string theory

普林斯顿一个叫Ed Witten的人 开始把它应用于弦理论

and people in Russia started applying it to what's called "condensed matter."

俄罗斯人开始把它应用在 被称作“凝聚体”的物理学中

Today, those things in there called Chern-Simons invariants

如今 这些被称为“陈-西蒙斯不变量”的东西

have spread through a lot of physics.

衍伸进了很多物理学理论中

And it was amazing.

这非常不可思议

We didn't know any physics.

我们根本不懂物理

It never occurred to me that it would be applied to physics.

我从没想到 它可以被应用于物理学

But that's the thing about mathematics -- you never know where it's going to go.

但这就是数学的迷人之处 你永远不知道它将去往何处

CA: This is so incredible.

这太奇妙了

So, we've been talking about how evolution shapes human minds

我们谈到 人类的思想 无论是否触及到真理

that may or may not perceive the truth.

是如何被进步的理论所改变的

Somehow, you come up with a mathematical theory,

无意间 在不了解任何物理学的情况下

not knowing any physics,

你提出了一个数学理论

discover two decades later that it's being applied

发现数十年之后 它已经被深度应用于

to profoundly describe the actual physical world.

描述真实的物理世界了

How can that happen?

那是怎样发生的呢？

JS: God knows.

天知道

(Laughter)

（笑）

But there's a famous physicist named [Eugene] Wigner,

有个著名的物理学家 Wigner

and he wrote an essay on the unreasonable effectiveness of mathematics.

他写过一篇名为《数学在自然科学中不可思议的有效性》的文章

Somehow, this mathematics, which is rooted in the real world

某种程度上 数学植根于真实世界

in some sense -- we learn to count, measure, everyone would do that --

某种意义上 我们学着计算 测量 每个人都会这样

and then it flourishes on its own.

接着它就自己繁荣了起来

But so often it comes back to save the day.

却又常常回过头来挽救大局

General relativity is an example.

广义相对论就是一个例子

[Hermann] Minkowski had this geometry, and Einstein realized,

闵可夫斯基给出了他的四维空间理论 而爱因斯坦意识到

"Hey! It's the very thing in which I can cast general relativity."

嘿！就是这玩意儿 可以用来表达我的广义相对论

So, you never know. It is a mystery.

你永远也想不到 就是这么神奇

It is a mystery.

对 很神奇

CA: So, here's a mathematical piece of ingenuity.

这是一个精巧的数学模型

Tell us about this.

给我们讲讲吧

JS: Well, that's a ball -- it's a sphere, and it has a lattice around it --

噢 这是一个球 球体 外面有格子状的框架

you know, those squares.

你知道 这些正方形

What I'm going to show here was originally observed by [Leonhard] Euler,

我接下来要展示的 最初是由十八世纪伟大的数学家

the great mathematician, in the 1700s.

欧拉发现的

And it gradually grew to be a very important field in mathematics:

后来逐步发展成为 数学中非常重要的一个领域

algebraic topology, geometry.

代数拓扑 几何学

That paper up there had its roots in this.

上面的那篇文章是基于这个理论基础的

So, here's this thing:

是这样子的

it has eight vertices, 12 edges, six faces.

它有8个顶点 12条边 6个面

And if you look at the difference -- vertices minus edges plus faces --

如果你算一下 定点数 - 边的个数 + 面的个数（8-12+6）

you get two.

会得到2

OK, well, two. That's a good number.

好 2 是个好数字

Here's a different way of doing it -- these are triangles covering --

我们还可以这样算 表面覆盖了三角形

this has 12 vertices and 30 edges

这样的话 有12个顶点 30条边

and 20 faces, 20 tiles.

和20个面 铺了20片

And vertices minus edges plus faces still equals two.

顶点数 - 边的个数 + 面的个数（12-30+20）还是等于2

And in fact, you could do this any which way --

事实上 你随便怎么算

cover this thing with all kinds of polygons and triangles

用各种多边形和三角来覆盖表面

and mix them up.

混在一起

And you take vertices minus edges plus faces -- you'll get two.

再计算 顶点数 - 边的个数 + 面的个数 总是会等于2

Here's a different shape.

这儿有另外一个形状

This is a torus, or the surface of a doughnut: 16 vertices

它有一个环面 或者说轮状表面

表面附有长方形 形成的16个顶点 32条边 16个面

covered by these rectangles, 32 edges, 16 faces.

Vertices minus edges comes out to be zero.

点-边+面（16-32+16）结果是0

It'll always come out to zero.

并且总是0

Every time you cover a torus with squares or triangles

每次你用正方形或三角形或类似的形状

or anything like that, you're going to get zero.

覆盖一个环形 你总会得到0

So, this is called the Euler characteristic.

这就是欧拉示性数

And it's what's called a topological invariant.

也是一种拓扑不变量

It's pretty amazing.

相当神奇

No matter how you do it, you're always get the same answer.

无论你怎么做 总会得到相同的答案

So that was the first sort of thrust, from the mid-1700s,

这是自十八世纪中叶以来 首次 算是进入了一个

into a subject which is now called algebraic topology.

如今被称作 代数拓扑的学科

CA: And your own work took an idea like this and moved it

您自己的研究 是把像这样的一个概念

into higher-dimensional theory,

推进到了高维空间理论

higher-dimensional objects, and found new invariances?

高维空间物体 并发现了新的不变量？

JS: Yes. Well, there were already higher-dimensional invariants:

对 之前已经有高维空间不变量了

Pontryagin classes -- actually, there were Chern classes.

庞特里亚金类（Pontryagin classes） 事实上 还有陈类（Chern classes）

There were a bunch of these types of invariants.

这些类型的不变量有很多

I was struggling to work on one of them

我努力研究其中一个

and model it sort of combinatorially,

用组合数学的方法 而非传统方法

instead of the way it was typically done,

给他们建模

and that led to this work and we uncovered some new things.

从而得出了这个成果 我们揭示了一些新的东西

But if it wasn't for Mr. Euler --

但如果没有欧拉先生

who wrote almost 70 volumes of mathematics

写下了近70卷数学著作

and had 13 children,

还有13个子女

who he apparently would dandle on his knee while he was writing --

显然在他写作时 承欢膝下

if it wasn't for Mr. Euler, there wouldn't perhaps be these invariants.

如果没有欧拉先生 可能就不会有这些不变量了

CA: OK, so that's at least given us a flavor of that amazing mind in there.

所以这至少 给这个精彩的思想 增加了一丝风味

Let's talk about Renaissance.

让我们谈谈文艺复兴（Simons所创立的科技公司）

Because you took that amazing mind and having been a code-cracker at the NSA,

因为你带着那个精彩的想法 曾在国安局做着一名密码破译者

you started to become a code-cracker in the financial industry.

你开始在金融业做密码破译者

I think you probably didn't buy efficient market theory.

我觉得你应该没买有效市场理论(有效市场假说认为市场价格波动是随机的，交易者不可能持续从市场中获利。)

Somehow you found a way of creating astonishing returns over two decades.

二十年后 你突然找到一种创造惊人收益的方法

The way it's been explained to me,

你解释给我的方法

what's remarkable about what you did wasn't just the size of the returns,

你所做之事的卓越之处 并不只是收益的规模

it's that you took them with surprisingly low volatility and risk,

更是因为 相比其他对冲基金

compared with other hedge funds.

你的方法有着出奇低的波动性和风险

So how on earth did you do this, Jim?

你究竟是怎么做到的呢 Jim

JS: I did it by assembling a wonderful group of people.

我能做到是因为 我聚集了一个非常优秀的团队

When I started doing trading, I had gotten a little tired of mathematics.

我开始经商的时候 已经有点厌倦数学了

I was in my late 30s, I had a little money.

人近四十 有些小钱

I started trading and it went very well.

我开始经商 而且进行得很顺利

I made quite a lot of money with pure luck.

光凭运气赚了相当多的钱

I mean, I think it was pure luck.

我的意思是 我觉得那完全是运气

It certainly wasn't mathematical modeling.

这当然不是数学建模

But in looking at the data, after a while I realized:

但过一阵子 当我看着那些数据 我意识到

it looks like there's some structure here.

那里面好像存在着某种结构

And I hired a few mathematicians, and we started making some models --

我招募了一些数学家 我们开始建立一些模型

just the kind of thing we did back at IDA [Institute for Defense Analyses].

和我们当初在IDA（国防分析研究所）做的事情差不多

You design an algorithm, you test it out on a computer.

你设计一个算法 在电脑上测试

Does it work? Doesn't it work? And so on.

管用？不管用？之类的

CA: Can we take a look at this?

我们可以看一下这个吗

Because here's a typical graph of some commodity.

这儿有一份 某个商品的典型图表

I look at that, and I say, "That's just a random, up-and-down walk --

我看着它 只能说 这只是一条随机的 上上下下的走势图

maybe a slight upward trend over that whole period of time."

大概整体上有轻微上升的趋势

How on earth could you trade looking at that,

你究竟就怎么看着这样的东西 来做交易的呢

and see something that wasn't just random?

还能看出点不随机的东西呢

JS: In the old days -- this is kind of a graph from the old days,

在过去 这是过时的一种图表

commodities or currencies had a tendency to trend.

可以通过趋势来追踪商品或货币

Not necessarily the very light trend you see here, but trending in periods.

并不必然是你这儿看到的轻微的趋势 可能是周期性的趋势

And if you decided, OK, I'm going to predict today,

如果你决定 好 我今天打算要做预测

by the average move in the past 20 days --

通过前20天的平均变化

maybe that would be a good prediction, and I'd make some money.

可能会有一个好的预测 还赚了点钱

And in fact, years ago, such a system would work --

事实上 几年前 这样子的系统是有用的

not beautifully, but it would work.

并不完美 但确实有用

You'd make money, you'd lose money, you'd make money.

你赚点钱 亏点钱 再赚点钱

But this is a year's worth of days,

但这是一年中的黄金几天

and you'd make a little money during that period.

你在那个阶段可以赚到点钱

It's a very vestigial system.

这是一个非常不健全的系统

CA: So you would test a bunch of lengths of trends in time

所以你会及时地测试大量的趋势区间

and see whether, for example,

看是否 举个例子

a 10-day trend or a 15-day trend was predictive of what happened next.

是否10天或15天的走向 可以对下一步做出较准确的预判

JS: Sure, you would try all those things and see what worked best.

当然 你要测试各种类型 来判断哪个最有效

Trend-following would have been great in the '60s,

跟踪趋势在60年代是很好的策略

and it was sort of OK in the '70s.

在70年代就一般了

By the '80s, it wasn't.

80年代 就没用了

CA: Because everyone could see that.

因为每个人都能看到

So, how did you stay ahead of the pack?

所以 你是如何保持领先地位呢

JS: We stayed ahead of the pack by finding other approaches --

我们保持领先是通过 寻找其他方法

shorter-term approaches to some extent.

某种程度上来说 更短期的方法

The real thing was to gather a tremendous amount of data --

具体来说是收集大量数据

and we had to get it by hand in the early days.

早期 我们不得不手动来收集数据

We went down to the Federal Reserve and copied interest rate histories

我们到美联储 拷贝历史利率之类的数据

and stuff like that, because it didn't exist on computers.

因为电脑上根本没有

We got a lot of data.

我们得到了很多数据

And very smart people -- that was the key.

和非常聪明的人——这是关键

I didn't really know how to hire people to do fundamental trading.

我不太知道要怎么去雇佣做基本贸易的人

I had hired a few -- some made money, some didn't make money.

我请了些 有的赚钱了 有的没有

I couldn't make a business out of that.

因为这样 我没有成功地打开局面

But I did know how to hire scientists,

但我知道怎么请科学家

because I have some taste in that department.

因为在那个领域 我还是有点眼光的

So, that's what we did.

所以我们这么做了

And gradually these models got better and better,

渐渐地 这些模型越来越好

and better and better.

越来越好

CA: You're credited with doing something remarkable at Renaissance,

您在文艺复兴科技公司所做的最为人称道的事

which is building this culture, this group of people,

就是建立起了这样的文化 组建这样的团队

who weren't just hired guns who could be lured away by money.

他们不是会被简单地 被金钱诱惑的雇佣兵

Their motivation was doing exciting mathematics and science.

他们的动力在于令人激动的数学和科学

JS: Well, I'd hoped that might be true.

噢我挺希望这是真的

But some of it was money.

但有些原因也是钱

CA: They made a lot of money.

他们金钵满盈

JS: I can't say that no one came because of the money.

我不能断言 没有人是冲着钱来的

I think a lot of them came because of the money.

我觉得他们中大多数都是为了钱

But they also came because it would be fun.

但也是因为 这会很好玩

CA: What role did machine learning play in all this?

机器学习在这里扮演了怎样一个角色？

JS: In a certain sense, what we did was machine learning.

某种意义上 我们做的就是机器学习

You look at a lot of data, and you try to simulate different predictive schemes,

你观察一大堆数据 模拟不同的预测方案

until you get better and better at it.

直到你越来越擅长于此

It doesn't necessarily feed back on itself the way we did things.

我们所做之事 不见得一定有自我反馈

But it worked.

但确实有效

CA: So these different predictive schemes can be really quite wild and unexpected.

所以这些不同的预测方案 很有可能相当不受控制 且无法预料

I mean, you looked at everything, right?

我的意思是 你着眼于万事万物 不是吗

You looked at the weather, length of dresses, political opinion.

你要看天气 裙长 政见

JS: Yes, length of dresses we didn't try.

嗯 我们可没试过裙长

CA: What sort of things?

那是什么样的事物呢？

JS: Well, everything.

嗯 各种东西

Everything is grist for the mill -- except hem lengths.

各种对工作有价值的东西 衣服下摆长度不算在内

Weather, annual reports,

天气 年报

quarterly reports, historic data itself, volumes, you name it.

季报 历史数据 成交量

Whatever there is.

应有尽有

We take in terabytes of data a day.

我们一天内接收兆兆字节的数据

And store it away and massage it and get it ready for analysis.

储存 处理 准备用于分析

You're looking for anomalies.

你寻找的是异常现象

You're looking for -- like you said,

你找的是 就像你说的

the efficient market hypothesis is not correct.

有效市场假说（Efficient Markets Hypothesis，EMH。有效市场假说认为市场价格波动是随机的，交易者不可能持续从市场中获利。）是不正确的

CA: But any one anomaly might be just a random thing.

但任何一个异常现象 都有可能只是一个随机事件

So, is the secret here to just look at multiple strange anomalies,

所以 这儿的秘诀是 只看那些 重复出现的奇特异常现象

and see when they align?

并观察他们是否一致

JS: Any one anomaly might be a random thing;

任何一个异常现象可能是随机事件

however, if you have enough data you can tell that it's not.

然而 只要你有足够的数据 可以看出来它其实不是

You can see an anomaly that's persistent for a sufficiently long time --

你可以在足够长的时间段里 看到这些异常现象是长期存在的

the probability of it being random is not high.

它是随机事件的可能性不高

But these things fade after a while; anomalies can get washed out.

但有一些异常现象不久后就消逝了 会淡出市场

So you have to keep on top of the business.

所以你必须在商业上保持优势

CA: A lot of people look at the hedge fund industry now

如今很多人关注对冲基金产业

and are sort of ... shocked by it,

有点被它

by how much wealth is created there,

产生了那么多的财富

and how much talent is going into it.

那么多的天才投身其中 所惊吓到

Do you have any worries about that industry,

你对这个产业有什么担忧吗

and perhaps the financial industry in general?

可能宽泛来说 整个金融产业？

Kind of being on a runaway train that's --

有点像在一辆 停不下来的火车上

I don't know -- helping increase inequality?

它助长了不平等

How would you champion what's happening in the hedge fund industry?

你会怎样在目前的对冲基金产业获胜呢？

JS: I think in the last three or four years,

我认为 在过去三四年里

hedge funds have not done especially well.

对冲基金没有表现得特别好

We've done dandy,

我们做的看似繁荣

but the hedge fund industry as a whole has not done so wonderfully.

但对冲基金产业整体上 没有表现太过如意

The stock market has been on a roll, going up as everybody knows,

众所周知 证券市场一路顺风地向上发展

and price-earnings ratios have grown.

市价盈利率增长了

So an awful lot of the wealth that's been created in the last --

过去五到六年创造了大量财富，

let's say, five or six years -- has not been created by hedge funds.

而不是对冲基金创造了极大量财富

People would ask me, "What's a hedge fund?"

人们会问我 “什么是对冲基金”

And I'd say, "One and 20."

我会说 “一和二十”

Which means -- now it's two and 20 --

现在是二和二十了 意思是

it's two percent fixed fee and 20 percent of profits.

2%的管理费 和20%的收益

Hedge funds are all different kinds of creatures.

对冲基金有各种各样的

CA: Rumor has it you charge slightly higher fees than that.

有传言说您（公司）比那个收费稍微高一点？

JS: We charged the highest fees in the world at one time.

我们一度是全世界收费最高的

Five and 44, that's what we charge.

5和44 我们是这么收的

CA: Five and 44.

5和44

So five percent flat, 44 percent of upside.

所以抽取了固定5% 收益部分44% (抽取5％的资产管理费和44％的投资收益分成)

You still made your investors spectacular amounts of money.

你仍然让你的投资者们获得了可观的收益

JS: We made good returns, yes.

我们有很好的回报率 没错

People got very mad: "How can you charge such high fees?"

人们都要疯了 “你怎么能收这么高呢”

I said, "OK, you can withdraw."

我说 “好啊 你可以撤资嘛”

But "How can I get more?" was what people were --

但 “我怎么赚更多” 是人们所（关注的）

(Laughter)

（笑）

But at a certain point, as I think I told you,

但某种程度上 正如我说过的

we bought out all the investors because there's a capacity to the fund.

我们买下了所有的投资者 因为对于基金 我们有能力

CA: But should we worry about the hedge fund industry

但我们应该担心对冲基金产业

attracting too much of the world's great mathematical and other talent

吸引了太多世界上厉害的数学家和其他天才

to work on that, as opposed to the many other problems in the world?

而对世界上很多其他问题视而不见吗

JS: Well, it's not just mathematical.

嗯 不只是数学

We hire astronomers and physicists and things like that.

我们还雇了天文学家和物理学家 之类的

I don't think we should worry about it too much.

我不觉得我们应该对此 太过担忧

It's still a pretty small industry.

这仍然是相当小的一个产业

And in fact, bringing science into the investing world

事实上 将科学引进投资世界

has improved that world.

令它得到了改善

It's reduced volatility. It's increased liquidity.

减少了波动性 增加了流动性

Spreads are narrower because people are trading that kind of stuff.

因为人们在交易这样子的东西 传播变得有限

So I'm not too worried about Einstein going off and starting a hedge fund.

所以我不太担心爱因斯坦会跑去开始玩对冲基金

CA: You're at a phase in your life now where you're actually investing, though,

您现在的人生阶段 尽管实际上

at the other end of the supply chain --

你在投资另外一个产业链

you're actually boosting mathematics across America.

但实际推动了整个美国的数学

This is your wife, Marilyn.

这是您妻子 Marilyn

You're working on philanthropic issues together.

你们一起致力于慈善事业

Tell me about that.

和我说说这个吧

JS: Well, Marilyn started --

好 Marilyn开创了

there she is up there, my beautiful wife --

这就是她 我美丽的老婆

she started the foundation about 20 years ago.

她在大约20年前创建了一个基金会

I think '94.

我想是1994年

I claim it was '93, she says it was '94,

我觉得是1993年 但她说是1994年

but it was one of those two years.

反正是这两年当中一个

(Laughter)

（笑）

We started the foundation, just as a convenient way to give charity.

我们创建这个基金 作为更方便做慈善的一个途径

She kept the books, and so on.

她管账 处理相关事务

We did not have a vision at that time, but gradually a vision emerged --

那时我们没什么愿景 但渐渐地浮现出一个想法

which was to focus on math and science, to focus on basic research.

就是致力于数学和科学 致力于基础研究

And that's what we've done.

这就是我们所做的

Six years ago or so, I left Renaissance and went to work at the foundation.

大概六年前 我离开文艺复兴科技公司 开始在基金会做事

So that's what we do.

所以这就是我们做的

CA: And so Math for America is basically investing

所以美国数学协会（Math for America）主要投资

in math teachers around the country,

全国范围的数学教师

giving them some extra income, giving them support and coaching.

提供他们额外收入 给予他们支持和辅导

And really trying to make that more effective

而且确实努力地变得更有效率

and make that a calling to which teachers can aspire.

使它成为老师们可以立志追求的渴望

JS: Yeah -- instead of beating up the bad teachers,

是啊 不去管打击了教育界士气的

which has created morale problems all through the educational community,

那些坏老师

in particular in math and science,

特别是数学和科学方面的

we focus on celebrating the good ones and giving them status.

我们致力于赞美好的老师 给予他们重要的地位

Yeah, we give them extra money, 15,000 dollars a year.

对了 我们每年提供给他们15000美元的额外资金

We have 800 math and science teachers in New York City in public schools today,

如今我们在纽约的公立学校里有800位数学和科学老师

as part of a core.

作为核心部分

There's a great morale among them.

他们都很有斗志

They're staying in the field.

坚守于他们的领域

Next year, it'll be 1,000 and that'll be 10 percent

明年将会有1000个

of the math and science teachers in New York [City] public schools.

会有10%纽约公立学校的数学、科学教师

(Applause)

（鼓掌）

CA: Jim, here's another project that you've supported philanthropically:

Jim 这是你所慈善事业的另外一个项目

Research into origins of life, I guess.

我猜是 探究生命起源

What are we looking at here?

我们看到的这是什么？

JS: Well, I'll save that for a second.

这个我一会儿来讲

And then I'll tell you what you're looking at.

我会告诉你看到的什么

Origins of life is a fascinating question.

生命的起源是一个迷人的问题

How did we get here?

我们来自何处

Well, there are two questions:

有两个问题

One is, what is the route from geology to biology --

一个是 从地质学到生物学 发展路线是什么

how did we get here?

我们是怎样发展到现在的

And the other question is, what did we start with?

另一个问题是 我们是怎么开始的

What material, if any, did we have to work with on this route?

什么物质 如果有的话 是这条线路上必须参与的

Those are two very, very interesting questions.

这是两个非常非常有趣的问题

The first question is a tortuous path from geology up to RNA

第一个是从地质学发展到RNA 其间曲折的道路

or something like that -- how did that all work?

或者类似的 那是怎么发展的

And the other, what do we have to work with?

另外一个 是什么东西是我们必不可少的

Well, more than we think.

超乎我们的想象

So what's pictured there is a star in formation.

所以那张图是形成中的一颗恒星

Now, every year in our Milky Way, which has 100 billion stars,

现在 每年 在我们拥有一千亿恒星的银河系中

about two new stars are created.

大约有两个正在形成的恒星

Don't ask me how, but they're created.

不要问我怎么做到的 但它们正在形成中

And it takes them about a million years to settle out.

它们耗去了一百万年慢慢沉积

So, in steady state,

进入稳定状态

there are about two million stars in formation at any time.

随时随刻 都有两百万的恒星处于生成状态

That one is somewhere along this settling-down period.

那一个是处于稳定状态的某处

And there's all this crap sort of circling around it,

这些宇宙垃圾围绕着它转动

dust and stuff.

灰尘 和其他东西

And it'll form probably a solar system, or whatever it forms.

它可能会形成一个太阳系 或随便什么

But here's the thing --

重点是

in this dust that surrounds a forming star

在围绕着这个形成恒星的尘埃中

have been found, now, significant organic molecules.

现在被发现存在 有着重大意义的 有机分子

Molecules not just like methane, but formaldehyde and cyanide --

不只是像甲烷那样的分子 还有甲醛和氰化物

things that are the building blocks -- the seeds, if you will -- of life.

像是生命结构基础（building blocks） 生命的种子的物质

So, that may be typical.

所以那可能很有典型意义

And it may be typical that planets around the universe

可能宇宙中的行星 起源于这些基础的结构基石

start off with some of these basic building blocks.

是具有典型意义的

Now does that mean there's going to be life all around?

这是否意味着周围会产生生命体呢

Maybe.

有可能

But it's a question of how tortuous this path is

但问题是 从那些脆弱的开端 那些种子

from those frail beginnings, those seeds, all the way to life.

一路演变为生命的道路 是如何曲折

And most of those seeds will fall on fallow planets.

那些种子大部分会掉落到荒芜的行星

CA: So for you, personally,

对您个人而言

finding an answer to this question of where we came from,

找到这些问题的答案

of how did this thing happen, that is something you would love to see.

我们从哪里来 又是怎么发生的 是您乐于看到的

JS: Would love to see.

乐于看到

And like to know --

而且想要知道

if that path is tortuous enough, and so improbable,

如果那条道路足够曲折 难以实现

that no matter what you start with, we could be a singularity.

无论起源是什么 我们可能是个特例

But on the other hand,

另一方面

given all this organic dust that's floating around,

考虑到所有这些漂浮在周围的有机灰尘

we could have lots of friends out there.

宇宙中我们可能有很多朋友

It'd be great to know.

很高兴知道

CA: Jim, a couple of years ago, I got the chance to speak with Elon Musk,

几年前 我有机会和伊隆·马斯克（南非企业家）谈话

and I asked him the secret of his success,

我问到他成功的秘诀

and he said taking physics seriously was it.

他说 秘诀就是 严肃地对待物理

Listening to you, what I hear you saying is taking math seriously,

听了你的言论 我听到你说的就是 严肃地对待数学

that has infused your whole life.

这个理念贯彻了你整个生命

It's made you an absolute fortune, and now it's allowing you to invest

它使你拥有了可观的财富 如今又引领你

in the futures of thousands and thousands of kids across America and elsewhere.

投资美国和其他地方成千上万孩子们的未来

Could it be that science actually works?

有没有可能 科学确实起作用了

That math actually works?

数学确实起作用了呢

JS: Well, math certainly works. Math certainly works.

数学当然起作用了

But this has been fun.

这很有趣

Working with Marilyn and giving it away has been very enjoyable.

和Marilyn在一起工作 施予别人 让我感到非常愉快

CA: I just find it -- it's an inspirational thought to me,

我刚发现 有个想法让我醍醐灌顶

that by taking knowledge seriously, so much more can come from it.

就是严肃地对待知识 你可以从中得到很多很多

So thank you for your amazing life, and for coming here to TED.

感谢您精彩的人生 感谢您来到TED

Thank you.

谢谢

Jim Simons!

詹姆斯 西蒙斯！

(Applause)