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  • Chris Anderson: You were something of a mathematical phenom.

    (安德森) 你算是數學界的奇葩

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

    很早便在哈佛和麻省理工教書

  • And then the NSA came calling.

    之後NSA找上門

  • What was that about?

    這段故事是?

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

    (西蒙斯) 喔,NSA是美國國家安全局

  • they didn't exactly come calling.

    並沒有實際找我

  • They had an operation at Princeton, where they hired mathematicians

    它在普林斯頓有個機構 請了許多數學家

  • to attack secret codes and stuff like that.

    來破解密碼之類的

  • And I knew that existed.

    我知道這事

  • And they had a very good policy,

    它們的規定挺不錯

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

    你可以一半研究數學

  • and at least half your time working on their stuff.

    只要一半做它們的事

  • And they paid a lot.

    給薪很優渥

  • So that was an irresistible pull.

    這點很難抗拒

  • So, I went there.

    所以我就去了

  • CA: You were a code-cracker.

    (安) 你曾是密碼破解員

  • JS: I was.

    (西) 對,是的

  • CA: Until you got fired.

    (安) 直到被解雇

  • JS: Well, I did get fired. Yes.

    (西) 對,我被炒魷魚

  • CA: How come?

    (安) 怎會這樣?

  • JS: Well, how come?

    (西) 嗯,原因嘛

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

    被解雇因為...那時越戰爆發

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

    我單位的上司迷上越戰

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

    他替紐約時報寫了文章 成為封面故事

  • about how we would win in Vietnam.

    談如何打贏越戰

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

    我不喜歡越戰,覺得很愚蠢

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

    便寫信給《時代》雜誌,後來被登出來

  • saying not everyone who works for Maxwell Taylor,

    說並非麥克斯維爾·泰勒所有屬下

  • if anyone remembers that name, agrees with his views.

    都贊同他,如果還有人記得這個名字

  • And I gave my own views ...

    我提出我的看法

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

    (安) OK,我瞭解這會...

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

    (西) 與泰勒將軍不同

  • But in the end, nobody said anything.

    但最後也沒人說什麼

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

    那年我29歲,有個小子來找我

  • and said he was a stringer from Newsweek magazine

    自稱是《新聞週刊》特約記者

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

    想問我怎麼實踐自己的看法

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

    我說:「現在我幾乎都弄數學

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

    等戰爭結束,才會做他們的事」

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

    於是我便做了那天最明智的事

  • I told my local boss that I gave that interview.

    我把訪談一事告訴主管

  • And he said, "What'd you say?"

    他問我:「你說了什麼?」

  • And I told him what I said.

    我就照實說

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

    接著他說:「我要打電話給泰勒」

  • He called Taylor; that took 10 minutes.

    他打給泰勒,講了10分鐘

  • I was fired five minutes after that.

    再5分鐘我就被解雇了

  • CA: OK.

    (安) 這樣啊

  • JS: But it wasn't bad.

    (西) 不過這並非壞事

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

    (安) 這不糟,因為你去了 紐約州立大學石溪分校

  • and stepped up your mathematical career.

    數學生涯更上層樓

  • You started working with this man here.

    也開始跟這人合作

  • Who is this?

    他是誰?

  • JS: Oh, [Shiing-Shen] Chern.

    (西) 喔,陳省身

  • Chern was one of the great mathematicians of the century.

    陳是那世紀最厲害的數學家

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

    我在柏克萊念碩士時,就知道他

  • And I had some ideas,

    我有些想法

  • and I brought them to him and he liked them.

    告訴了他,他很喜歡

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

    我們便一起努力,就上面你看到的

  • There it is.

    就是這個

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

    (安) 你們共同發表了著名論文

  • Can you explain at all what that work was?

    可以談研究內容嗎?

  • JS: No.

    (西) 不行

  • (Laughter)

    (笑聲)

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

    (西) 我是說,可以講給別人聽

  • (Laughter)

    (笑聲)

  • CA: How about explaining this?

    (安) 如果說明這個呢?

  • JS: But not many. Not many people.

    (西) 可是, 不會向太多人

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

    (安) 你曾告訴我,這跟球體有關

  • so let's start here.

    從這說起吧

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

    (西) 我要講那研究-

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

    是有關球形, 但我想先說

  • that work was good mathematics.

    那是一流的數學研究

  • I was very happy with it; so was Chern.

    我非常高興,陳也是

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

    它甚至促成一個次領域,現在很興盛

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

    更棒的是它被用於物理

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

    一個未知領域,至少我不懂物理

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

    我想陳也只略知皮毛

  • And about 10 years after the paper came out,

    論文發表10年後

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

    普林斯頓的愛德華·維騰把它用在弦理論

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

    俄國人則用於所謂"凝聚體"研究

  • Today, those things in there called Chern-Simons invariants

    如今這些被稱為"陳-西蒙不變式"

  • have spread through a lot of physics.

    廣泛應用在物理界

  • And it was amazing.

    這太不可思議

  • We didn't know any physics.

    我們完全是物理門外漢

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

    從沒想過會被用於物理

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

    然而,這就是數學,你總猜不到它的去向

  • CA: This is so incredible.

    (安) 真難以置信

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

    我們談到演化如何形塑人類思想

  • that may or may not perceive the truth.

    無論思想是否關於真理

  • Somehow, you come up with a mathematical theory,

    你就這樣得出一個數學理論

  • not knowing any physics,

    完全不懂物理

  • discover two decades later that it's being applied

    這理論20年後被用來

  • to profoundly describe the actual physical world.

    深入描述實際物理世界

  • How can that happen?

    怎麼辦到的?

  • JS: God knows.

    (西) 天曉得

  • (Laughter)

    (笑聲)

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

    知名物理學家尤金·維格納

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

    曾撰文談到數學不合理的有效性

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

    不管怎樣, 數學本就源自真實世界

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

    例如學計算、測量,大家都這麼做

  • and then it flourishes on its own.

    這學門自己繁盛起來

  • But so often it comes back to save the day.

    常常一回到數學,困難就迎刃而解

  • General relativity is an example.

    廣義相對論就是一例

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

    愛因斯坦學了閔可夫斯基的幾何學後

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

    驚呼「就是它了! 幫我釐清廣義相對論」

  • So, you never know. It is a mystery.

    所以, 你搞不懂的,這太奧秘了

  • It is a mystery.

    超乎常理

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

    (安) 關於數學的獨創性

  • Tell us about this.

    講講這個

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

    (西) 這是顆球-球體,球面被格狀劃分

  • you know, those squares.

    就那些四方形

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

    我要講的是(萊昂納多)歐拉發現的

  • the great mathematician, in the 1700s.

    18世紀偉大的數學家

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

    這現象逐漸成為重要的數學領域

  • algebraic topology, geometry.

    代數拓樸學、幾何學

  • That paper up there had its roots in this.

    我的研究即從這來

  • So, here's this thing:

    是這樣的

  • it has eight vertices, 12 edges, six faces.

    這裡有8頂點、12邊和6面

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

    如果加以運算:頂點數-邊數+面數

  • you get two.

    得到2

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

    嗯,好一個2

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

    換方法做,佈滿三角形

  • this has 12 vertices and 30 edges

    有12個頂點,30個邊

  • and 20 faces, 20 tiles.

    和20個面

  • And vertices minus edges plus faces still equals two.

    此時點-邊+面仍是2

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

    事實上,你可用任何方法

  • cover this thing with all kinds of polygons and triangles

    球上蓋滿各種多邊形和三角形

  • and mix them up.

    混合在一起

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

    再把點-邊+面,得到2

  • Here's a different shape.

    這是另一種形狀

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

    這是環面,甜甜圈形表面16頂點

  • covered by these rectangles, 32 edges, 16 faces.

    覆蓋長方形,32邊,16面

  • Vertices minus edges comes out to be zero.

    點-邊+面得出0

  • It'll always come out to zero.

    答案永遠是0

  • Every time you cover a torus with squares or triangles

    只要用長方或三角形 覆蓋環面

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

    答案總是0

  • So, this is called the Euler characteristic.

    這稱為歐拉示性數

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

    也叫做拓樸不變量

  • It's pretty amazing.

    這很神奇

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

    不論你怎麼劃,答案總是一樣

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

    這是18世紀中以來第一個刺激

  • into a subject which is now called algebraic topology.

    後來變成代數拓樸學

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

    (安) 你對此更深入研究

  • into higher-dimensional theory,

    到更高維度理論

  • higher-dimensional objects, and found new invariances?

    更高維度的物體,找新的不變量?

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

    是, 高維不變量已找到了

  • Pontryagin classes -- actually, there were Chern classes.

    龐特里亞金示性類,還有陳示性類

  • There were a bunch of these types of invariants.

    一大堆這類不變量

  • I was struggling to work on one of them

    那時我努力研究其中一個

  • and model it sort of combinatorially,

    發展成某種組合模型

  • instead of the way it was typically done,

    不用既有標準方法

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

    這變成我們的研究,也發現新東西

  • But if it wasn't for Mr. Euler --

    但如果沒有歐拉

  • who wrote almost 70 volumes of mathematics

    寫下70卷數學書

  • and had 13 children,

    養育13個子女

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

    想必是邊寫邊逗弄幼兒

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

    若非歐拉, 就沒有這些不變量

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

    (安) 恩, 我們瞭解了,奇特的心路歷程

  • Let's talk about Renaissance.

    現在讓我們談談文藝復興科技公司

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

    由於你曾任NSA解碼員的研究經歷

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

    你開始當金融界的解碼員

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

    我想你不相信效率市場理論

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

    20年來,你有辦法獲利驚人

  • The way it's been explained to me,

    對我來說你的方法

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

    驚人之處不在於獲利金額多寡

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

    而是大幅降低變動性與風險

  • compared with other hedge funds.

    相較其他對沖基金

  • So how on earth did you do this, Jim?

    你到底怎麼辦到的?

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

    (西) 我靠集合一群優秀的人

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

    我開始經商時,我對數學已有些厭煩

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

    年紀快40,手頭有點錢

  • I started trading and it went very well.

    便開始做買賣,結果非常成功

  • I made quite a lot of money with pure luck.

    純靠運氣賺了一大筆錢

  • I mean, I think it was pure luck.

    我說,我認為是好運

  • It certainly wasn't mathematical modeling.

    而肯定不是數學模型

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

    但我審視這些數字後

  • it looks like there's some structure here.

    發覺現似有固定模式

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

    我便請幾位數學家,弄了幾個模型

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

    類似我在防衛分析研究所做的

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

    設計一套演算法,用電腦測試

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

    能用?不能用? 之類的

  • CA: Can we take a look at this?

    (安) 可否看看這個?

  • Because here's a typical graph of some commodity.

    這是常見的商品銷售圖

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

    我想:「不過是隨機走高走低-

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

    整體趨勢緩升」

  • How on earth could you trade looking at that,

    你到底怎麼看這隨機圖

  • and see something that wasn't just random?

    就能做生意、發現東西?

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

    (西) 這圖很老套了

  • commodities or currencies had a tendency to trend.

    商品或貨幣有其趨勢

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

    不必然像這樣,但一段時間有其走向

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

    如果你決定,好,我要預測今天

  • by the average move in the past 20 days --

    靠前20日的平均變化

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

    也許可猜得準,也賺到錢

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

    事實上幾年前,這系統還可行

  • not beautifully, but it would work.

    不漂亮,但過得去

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

    賺了,賠了,又賺

  • But this is a year's worth of days,

    但這是一年內表現最好的幾天

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

    這期間賺得不多

  • It's a very vestigial system.

    這系統老掉牙了

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

    (安) 所以你用不同期間長短

  • and see whether, for example,

    的趨勢來檢視,例如

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

    是10天還是15天的走勢預測較準

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

    (西) 沒錯,都得試過才知道

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

    順勢投資法 在60年代或許非常好用

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

    70年代還可以

  • By the '80s, it wasn't.

    到80年代就玩不通了

  • CA: Because everyone could see that.

    (安) 因為任何人都看得出來

  • So, how did you stay ahead of the pack?

    你是怎麼持續領先的?

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

    (西) 我們靠開發其他方法保持領先-

  • shorter-term approaches to some extent.

    像是期間更短的方法

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

    實際上是蒐集無數資料

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

    早期都一筆筆抄回來

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

    我們到聯準會影印歷史利率

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

    之類的,那時還沒有電腦

  • We got a lot of data.

    我們取得大批資料

  • And very smart people -- that was the key.

    和絕頂聰明的人——這是關鍵

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

    我不太會找人做實際買賣

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

    我請過幾個——有人能賺,有的不行

  • I couldn't make a business out of that.

    我不能這樣做生意

  • But I did know how to hire scientists,

    但我知道怎麼請科學家

  • because I have some taste in that department.

    這方面我比較有品味

  • So, that's what we did.

    所以就這麼做了

  • And gradually these models got better and better,

    模型表現越來越好

  • and better and better.

    越來越順

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

    (安) 你帶領文藝復興公司的成果驚艷

  • which is building this culture, this group of people,

    塑造了一種文化、一群人

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

    他們不是老想錢的傭兵

  • Their motivation was doing exciting mathematics and science.

    而一心想玩數學和科學

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

    (西) 我希望這是真的

  • But some of it was money.

    但有些動機真的是錢

  • CA: They made a lot of money.

    (安) 他們賺了好多

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

    (西) 我不信沒人在乎錢

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

    我想許多人來都想賺錢

  • But they also came because it would be fun.

    但他們也想樂在其中

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

    (安) 當中機器學習的角色是?

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

    (西) 某些情況下,我們就是做機器學習

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

    你面對成堆資料,試著模擬各種預測系統

  • until you get better and better at it.

    直到越發熟練

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

    它不一定會跟人一樣主動回饋資料

  • But it worked.

    但仍滿好用的

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

    (安) 所以不同預測系統很難駕馭與掌握

  • I mean, you looked at everything, right?

    意思是,你什麼都算,是嗎?

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

    天氣、裙長、政治評論

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

    (西) 是的,裙長倒沒試過

  • CA: What sort of things?

    (安) 哪類東西?

  • JS: Well, everything.

    (西) 所有東西

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

    什麼都可用-除了衣擺長度

  • Weather, annual reports,

    天氣、年報

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

    季報、歷史資料、冊數,只要你叫得出來

  • Whatever there is.

    管他是什麼

  • We take in terabytes of data a day.

    我們每天取得1T的資料

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

    接著儲存、處理、準備分析

  • You're looking for anomalies.

    尋找突出的現象

  • You're looking for -- like you said,

    在找——就像你說的

  • the efficient market hypothesis is not correct.

    效率市場假說並不正確

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

    (安) 但任何奇特現象都可能只是隨機現象

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

    所以秘訣是在與注意多次出現的異狀,

  • and see when they align?

    並觀察何時接連出現嗎?

  • JS: Any one anomaly might be a random thing;

    (西) 任何異常狀可能只是恰巧

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

    不過看夠多資料後 就知並非如此

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

    會發現異常持續很久

  • the probability of it being random is not high.

    隨機出現的機率反而不高

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

    一陣子它會不見,異常會消失

  • So you have to keep on top of the business.

    所以我們得保持領先

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

    (安) 目前人們看對沖基金產業

  • and are sort of ... shocked by it,

    都感到震驚

  • by how much wealth is created there,

    竟創造這麼多財富

  • and how much talent is going into it.

    又得投入大量腦力

  • Do you have any worries about that industry,

    你擔心這產業嗎?

  • and perhaps the financial industry in general?

    或對整個金融業?

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

    好似脫韁野馬

  • I don't know -- helping increase inequality?

    我不曉得——助長社會不平等?

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

    你為何支持對沖基金的近來發展?

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

    (西) 我想近3、4年

  • hedge funds have not done especially well.

    對沖基金表現平平

  • We've done dandy,

    我們曾風光一時

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

    但這產業走得不太順

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

    眾所周知,股市向來平步青雲

  • and price-earnings ratios have grown.

    本益比增加了

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

    過去5、6年錢賺到嚇死人

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

    但對沖基金就較差

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

    人們問我:「什麼是對沖基金?」

  • And I'd say, "One and 20."

    我說:「1和20」

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

    意思是——現在是2和20

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

    2%的固定手續費,20%的獲利抽成

  • Hedge funds are all different kinds of creatures.

    各家對沖基金差異很大

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

    (安) 有流言說,你收的高些

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

    (西) 我們的手續費一度是世界最高

  • Five and 44, that's what we charge.

    5和44,就這個價格

  • CA: Five and 44.

    (安) 5和44

  • So five percent flat, 44 percent of upside.

    5%固定費用,44%獲利抽成

  • You still made your investors spectacular amounts of money.

    你仍幫客戶賺進大把鈔票

  • JS: We made good returns, yes.

    (西) 是的,收益很不錯

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

    人們氣我:「這太貴了」

  • I said, "OK, you can withdraw."

    我說:「OK,你可退出」

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

    但「如何賺更多」就是人們...

  • (Laughter)

    (笑聲)

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

    但重點是,我跟你提過

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

    我們收購了所有投資者,因為這基金能賺

  • CA: But should we worry about the hedge fund industry

    (安) 但該替對沖基金業擔心嗎?

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

    它吸走太多全球優秀的數學等人才

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

    只做這事,而無視世界其他問題

  • JS: Well, it's not just mathematical.

    (西) 這個嘛,不單數學家

  • We hire astronomers and physicists and things like that.

    我們也聘請天文學家和物理學家等

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

    我不覺得我們應當過於擔心

  • It's still a pretty small industry.

    這產業規模仍小

  • And in fact, bringing science into the investing world

    事實上,把科學引入投資界

  • has improved that world.

    對世界有益

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

    可降低變動性,提高流動性

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

    因人們交易這東西,擴散範圍變更小

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

    我不擔心愛因斯坦出走搞對沖基金

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

    (安) 你現在的人生階段是,一方面進出市場

  • at the other end of the supply chain --

    但在供應鏈另一端

  • you're actually boosting mathematics across America.

    也正促進全美數學發展

  • This is your wife, Marilyn.

    這是您的夫人,瑪麗蓮

  • You're working on philanthropic issues together.

    您倆攜手從事慈善工作

  • Tell me about that.

    說說這個

  • JS: Well, Marilyn started --

    (西) 嗯,瑪麗蓮-

  • there she is up there, my beautiful wife --

    這就是她,我美麗的老婆

  • she started the foundation about 20 years ago.

    20年前她創立一基金會

  • I think '94.

    我想是1994年

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

    我說1993, 她說1994

  • but it was one of those two years.

    就這兩年間

  • (Laughter)

    (笑聲)

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

    我們創立基金會以便做慈善工作

  • She kept the books, and so on.

    她負責管帳等事

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

    那時我們沒太多想法,後來逐漸找到方向——

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

    投入數學、科學和基礎研究

  • And that's what we've done.

    這就是我們在做的

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

    6年前我離開文藝復興公司,改在基金會工作

  • So that's what we do.

    我們在做這個

  • CA: And so Math for America is basically investing

    (安) Math for America計畫,基本上是投資

  • in math teachers around the country,

    全國數學教師

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

    提供額外收入並給予支持和指導

  • And really trying to make that more effective

    讓計畫更有效運作

  • and make that a calling to which teachers can aspire.

    號召有理想的老師

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

    (西) 是的——與其懲罰不適任者

  • which has created morale problems all through the educational community,

    會拖累教育士氣的人

  • in particular in math and science,

    特別在數理科

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

    我們著重鼓勵好老師,給他們地位

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

    是的,我們每年給他們1萬5千美元額外收入

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

    目前紐約市有800名公立學校數理教師

  • as part of a core.

    是核心成員

  • There's a great morale among them.

    他們士氣高昂

  • They're staying in the field.

    專注在這領域

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

    明年將增至1千人

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

    即紐約公立學校10%的數理教師

  • (Applause)

    (掌聲)

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

    (安) 你還資助另一計畫

  • Research into origins of life, I guess.

    研究生命的起源, 是吧

  • What are we looking at here?

    這是什麼?

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

    (西) 先擱一邊

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

    等會再說這圖

  • Origins of life is a fascinating question.

    生命源起令人著迷

  • How did we get here?

    如何找到答案?

  • Well, there are two questions:

    這要處理兩個問題

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

    一是,從地質學往生物學

  • how did we get here?

    路在哪裡?

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

    二是,從哪下手?

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

    一路上需哪些材料?

  • Those are two very, very interesting questions.

    這兩問題非常有趣

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

    問題一是條曲折路,從地質學到RNA

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

    之類的——這如何可能?

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

    問題二是需要什麼東西

  • Well, more than we think.

    這超乎我們想像

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

    所以,這是張星體形成圖

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

    在千億星體組成的銀河系裡

  • about two new stars are created.

    每年都誕生兩顆星星

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

    別問過程,反正就誕生了

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

    接著要百萬年才穩定下來

  • So, in steady state,

    型態固定了

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

    宇宙形成中的星星隨時都有兩百萬顆

  • That one is somewhere along this settling-down period.

    那顆星正逐漸穩定

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

    周遭圍繞著廢棄物

  • dust and stuff.

    塵埃和其他東西

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

    它可能形成太陽系,或者其他什麼

  • But here's the thing --

    但關鍵是——

  • in this dust that surrounds a forming star

    形成中星體周遭的塵土裡

  • have been found, now, significant organic molecules.

    現在研究發現重要的有機分子

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

    不只有甲烷,還有甲醛、氰化物

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

    這種基礎物質——或者生命的種子

  • So, that may be typical.

    這可能是典型過程

  • And it may be typical that planets around the universe

    宇宙星體也可能經此典型過程

  • start off with some of these basic building blocks.

    由基礎組成物建立起來

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

    這代表到處都存在生命?

  • Maybe.

    也許

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

    但問題在於這過程多麼迂迴曲折

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

    從渺小的起頭, 種子演變成生命

  • And most of those seeds will fall on fallow planets.

    這類種子絕大多數落在休眠星體上

  • CA: So for you, personally,

    (安) 那麼對你個人來說

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

    尋找答案,關於你我的起源

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

    和源起過程是你想知道的

  • JS: Would love to see.

    (西) 我很期待

  • And like to know --

    也想知道——

  • if that path is tortuous enough, and so improbable,

    如果這路如此艱辛、渺茫

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

    那不論源頭是什麼,你我都可能是個奇點

  • But on the other hand,

    但另方面

  • given all this organic dust that's floating around,

    由於懸浮在外的有機塵埃

  • we could have lots of friends out there.

    遠方我們也許有很多朋友

  • It'd be great to know.

    知道這個感覺很好

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

    (安) 幾年前,我有機會和伊隆·馬斯克對談

  • and I asked him the secret of his success,

    我請教他成功的秘訣

  • and he said taking physics seriously was it.

    他說好好把物理當回事

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

    而你所說的,我覺得是把數學當回事

  • that has infused your whole life.

    它飽滿了你的人生

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

    它給你帶來可觀的收入,可以投資

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

    全美、甚至其他地方數千位孩童的未來

  • Could it be that science actually works?

    真是這學科的功勞嗎?

  • That math actually works?

    數學真起作用了?

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

    (西) 數學本身一定是確實有效的

  • But this has been fun.

    但有趣的是

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

    和瑪麗蓮同心捐助也真是人生至樂

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

    (安) 我發現——這啟發了我

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

    認真做好一門學問,更多好事由此而來

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

    感謝你來 TED 分享不凡的人生

  • Thank you.

    謝謝你

  • Jim Simons!

    詹姆士‧西蒙斯

  • (Applause)

    (掌聲)

Chris Anderson: You were something of a mathematical phenom.

(安德森) 你算是數學界的奇葩

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A2 TED 數學 數學家 研究 物理 資料

【TED】吉姆-西蒙斯:破解華爾街的數學家 (The mathematician who cracked Wall Street | Jim Simons) (【TED】Jim Simons: The mathematician who cracked Wall Street (The mathematician who cracked Wall Street | Jim Simons))

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    Mark Hsu posted on 2021/01/14
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