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Chris Anderson: You were something\nof a mathematical phenom.

You had already taught at Harvard\nand MIT at a young age.

Jim Simons: Well the NSA --\n

they didn't exactly come calling.

They had an operation at Princeton,\n

to attack secret codes\nand stuff like that.

And they had a very good policy

because you could do half your time\nat your own mathematics

and at least half your time\nworking on their stuff.

So that was an irresistible pull.

JS: Well, I did get fired. Yes.

I got fired because,\nwell, the Vietnam War was on

and the boss of bosses in my organization\n

and wrote a New York Times article,\n

about how we would win in Vietnam.

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

And I wrote a letter to the Times,\nwhich they published

saying not everyone\nwho works for Maxwell Taylor

if anyone remembers that name,\nagrees with his views.

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

JS: ... which were different\nfrom General Taylor's.

But in the end, nobody said anything.

But then, I was 29 years old at this time,\n

and said he was a stringer\nfrom Newsweek magazine

and he wanted to interview me\n

And I told him, "I\'m doing\nmostly mathematics now

and when the war is over,\nthen I\'ll do mostly their stuff.

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

I told my local boss\nthat I gave that interview.

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

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

He called Taylor; that took 10 minutes.

I was fired five minutes after that.

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

and stepped up your mathematical career.

You started working with this man here.

Chern was one of the great\nmathematicians of the century.

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

and I brought them to him\nand he liked them.

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

CA: It led to you publishing\na famous paper together.

Can you explain at all what that work was?

JS: I mean, I could\nexplain it to somebody.

CA: How about explaining this?

JS: But not many. Not many people.

CA: I think you told me\nit had something to do with spheres

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

it did have something to do with that,\n

that work was good mathematics.

I was very happy with it; so was Chern.

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

But, more interestingly,\nit happened to apply to physics

something we knew nothing about --\n

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

And about 10 years\nafter the paper came out

a guy named Ed Witten in Princeton\n

and people in Russia started applying it\n

Today, those things in there\ncalled Chern-Simons invariants

have spread through a lot of physics.

It never occurred to me\nthat it would be applied to physics.

But that's the thing about mathematics --\n

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

that may or may not perceive the truth.

Somehow, you come up\nwith a mathematical theory

discover two decades later\nthat it's being applied

to profoundly describe\nthe actual physical world.

But there's a famous physicist\nnamed [Eugene] Wigner

and he wrote an essay on the unreasonable\n

Somehow, this mathematics,\nwhich is rooted in the real world

in some sense -- we learn to count,\n

and then it flourishes on its own.

But so often it comes\nback to save the day.

General relativity is an example.

[Hermann] Minkowski had this geometry,\nand Einstein realized

Hey! It\'s the very thing\n

So, you never know. It is a mystery.

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

JS: Well, that's a ball -- it's a sphere,\n

What I'm going to show here was\n

the great mathematician, in the 1700s.

And it gradually grew to be\n

algebraic topology, geometry.

That paper up there had its roots in this.

it has eight vertices,\n12 edges, six faces.

And if you look at the difference --\n

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

Here's a different way of doing it --\n

this has 12 vertices and 30 edges

And vertices minus edges\nplus faces still equals two.

And in fact, you could do this\nany which way --

cover this thing with all kinds\nof polygons and triangles

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

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

covered by these rectangles,\n32 edges, 16 faces.

Vertices minus edges comes out to be zero.

It'll always come out to zero.

Every time you cover a torus\nwith squares or triangles

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

So, this is called\nthe Euler characteristic.

And it's what's called\na topological invariant.

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

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

into a subject which is now called\nalgebraic topology.

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

into higher-dimensional theory

higher-dimensional objects,\nand found new invariances?

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

Pontryagin classes --\nactually, there were Chern classes.

There were a bunch\nof these types of invariants.

I was struggling to work on one of them

and model it sort of combinatorially

instead of the way it was typically done

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

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

who wrote almost 70 volumes of mathematics

who he apparently would dandle on his knee\n

if it wasn't for Mr. Euler, there wouldn't\n

CA: OK, so that's at least given us\n

Let's talk about Renaissance.

Because you took that amazing mind\n

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

I think you probably didn't buy\nefficient market theory.

Somehow you found a way of creating\n

The way it's been explained to me

what's remarkable about what you did\n

it's that you took them\n

compared with other hedge funds.

So how on earth did you do this, Jim?

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

When I started doing trading, I had\n

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

I started trading and it went very well.

I made quite a lot of money\nwith pure luck.

I mean, I think it was pure luck.

It certainly wasn't mathematical modeling.

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

it looks like there's some structure here.

And I hired a few mathematicians,\n

just the kind of thing we did back\n

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

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

CA: Can we take a look at this?

Because here's a typical graph\nof some commodity.

I look at that, and I say,\n

maybe a slight upward trend\nover that whole period of time.

How on earth could you trade\nlooking at that

and see something that wasn't just random?

JS: In the old days -- this is\n

commodities or currencies\nhad a tendency to trend.

Not necessarily the very light trend\n

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

by the average move in the past 20 days --

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

And in fact, years ago,\nsuch a system would work --

not beautifully, but it would work.

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

But this is a year's worth of days

and you'd make a little money\nduring that period.

It's a very vestigial system.

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

and see whether, for example

a 10-day trend or a 15-day trend\n

JS: Sure, you would try all those things\n

Trend-following would\nhave been great in the '60s

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

CA: Because everyone could see that.

So, how did you stay ahead of the pack?

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

shorter-term approaches to some extent.

The real thing was to gather\na tremendous amount of data --

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

We went down to the Federal Reserve\n

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

And very smart people -- that was the key.

I didn't really know how to hire\n

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

I couldn't make a business out of that.

But I did know how to hire scientists

because I have some taste\nin that department.

And gradually these models\ngot better and better

CA: You're credited with doing\n

which is building this culture,\nthis group of people

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

Their motivation was doing\nexciting mathematics and science.

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

CA: They made a lot of money.

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

I think a lot of them\ncame because of the money.

But they also came\nbecause it would be fun.

CA: What role did machine learning\nplay in all this?

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

You look at a lot of data, and you try\n

until you get better and better at it.

It doesn't necessarily feed back on itself\n

CA: So these different predictive schemes\n

I mean, you looked at everything, right?

You looked at the weather,\nlength of dresses, political opinion.

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

Everything is grist for the mill --\nexcept hem lengths.

quarterly reports, historic data itself,\nvolumes, you name it.

We take in terabytes of data a day.

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

You're looking for anomalies.

You're looking for -- like you said

the efficient market\nhypothesis is not correct.

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

So, is the secret here to just look\n

JS: Any one anomaly\nmight be a random thing;

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

You can see an anomaly that's persistent\n

the probability of it being\nrandom is not high.

But these things fade after a while;\n

So you have to keep on top\nof the business.

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

and are sort of ... shocked by it

by how much wealth is created there

and how much talent is going into it.

Do you have any worries\nabout that industry

and perhaps the financial\nindustry in general?

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

I don't know --\nhelping increase inequality?

How would you champion what's happening\n

JS: I think in the last\nthree or four years

hedge funds have not done especially well.

but the hedge fund industry as a whole\n

The stock market has been on a roll,\n

and price-earnings ratios have grown.

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

let's say, five or six years --\n

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

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

it's two percent fixed fee\nand 20 percent of profits.

Hedge funds are all\ndifferent kinds of creatures.

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

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

Five and 44, that's what we charge.

So five percent flat,\n44 percent of upside.

You still made your investors\nspectacular amounts of money.

JS: We made good returns, yes.

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

I said, "OK, you can withdraw.

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

But at a certain point,\nas I think I told you

we bought out all the investors\n

CA: But should we worry\nabout the hedge fund industry

attracting too much of the world's\n

to work on that, as opposed\n

JS: Well, it's not just mathematical.

We hire astronomers and physicists\nand things like that.

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

It's still a pretty small industry.

And in fact, bringing science\ninto the investing world

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

Spreads are narrower because\n

So I'm not too worried about Einstein\n

CA: You're at a phase in your life now\n

at the other end of the supply chain --

you're actually boosting\nmathematics across America.

You're working on\nphilanthropic issues together.

JS: Well, Marilyn started --

there she is up there,\nmy beautiful wife --

she started the foundation\nabout 20 years ago.

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

but it was one of those two years.

We started the foundation,\n

She kept the books, and so on.

We did not have a vision at that time,\n

which was to focus on math and science,\n

Six years ago or so, I left Renaissance\n

CA: And so Math for America\nis basically investing

in math teachers around the country

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

And really trying\nto make that more effective

and make that a calling\nto which teachers can aspire.

JS: Yeah -- instead of beating up\nthe bad teachers

which has created morale problems\n

in particular in math and science

we focus on celebrating the good ones\nand giving them status.

Yeah, we give them extra money,\n15,000 dollars a year.

We have 800 math and science teachers\n

There's a great morale among them.

They're staying in the field.

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

of the math and science teachers\n

CA: Jim, here's another project\n

Research into origins of life, I guess.

What are we looking at here?

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

And then I'll tell you\nwhat you're looking at.

Origins of life is a fascinating question.

Well, there are two questions:

One is, what is the route\nfrom geology to biology --

And the other question is,\nwhat did we start with?

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

Those are two very,\nvery interesting questions.

The first question is a tortuous path\nfrom geology up to RNA

or something like that --\nhow did that all work?

And the other,\nwhat do we have to work with?

So what's pictured there\nis a star in formation.

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

about two new stars are created.

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

And it takes them about a million\nyears to settle out.

there are about two million stars\nin formation at any time.

That one is somewhere\nalong this settling-down period.

And there's all this crap\nsort of circling around it

And it'll form probably a solar system,\nor whatever it forms.

in this dust that surrounds a forming star

have been found, now,\nsignificant organic molecules.

Molecules not just like methane,\nbut formaldehyde and cyanide --

things that are the building blocks --\n

And it may be typical\nthat planets around the universe

start off with some of these\nbasic building blocks.

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

But it's a question\nof how tortuous this path is

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

And most of those seeds\nwill fall on fallow planets.

finding an answer to this question\nof where we came from

of how did this thing happen,\n

if that path is tortuous enough,\nand so improbable

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

given all this organic dust\nthat's floating around

we could have lots of friends out there.

CA: Jim, a couple of years ago,\n

and I asked him the secret of his success

and he said taking\nphysics seriously was it.

Listening to you, what I hear you saying\n

that has infused your whole life.

It's made you an absolute fortune,\n

in the futures of thousands and thousands\n

Could it be that science actually works?

JS: Well, math certainly works.\nMath certainly works.

Working with Marilyn and giving it away\nhas been very enjoyable.

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

that by taking knowledge seriously,\n

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