今天推薦的演講者是：Albert Barabasi，發(fā)布于2019年的TED演講大會！

愛因斯坦曾經(jīng)說過，如果一個人到30歲時對科學(xué)都沒啥大貢獻，也就永遠不會有貢獻了。但本期TED演講者Albert，作為網(wǎng)絡(luò)科學(xué)的先驅(qū)者，他揭示了很多復(fù)雜系統(tǒng)背后隱藏的秩序。他認為，創(chuàng)意并無年齡限制，生產(chǎn)力才是關(guān)鍵！

The real relationship between your age and your chance of success

Albert BarabasiToday, actually, is a very special day for me, because it is my birthday. And so, thanks to all of you for joining the party. But every time you throw a party, there's someone there to spoil it. Right? And I'm a physicist, and this time I brought another physicist along to do so.

今天對我來說很特別，因為是我的生日。謝謝大家參與這個聚會?？墒牵看文闩e辦聚會的時候，總是有人搗蛋，對吧？我是個物理學(xué)家，這次我?guī)砹肆硪粋€物理學(xué)家。

His name is Albert Einstein -- also Albert -- and he's the one who said that the person who has not made his great contributions to science by the age of 30 will never do so. Now, you don't need to check Wikipedia that I'm beyond 30. So, effectively, what he is telling me, and us, is that when it comes to my science, I'm deadwood. Well, luckily, I had my share of luck within my career.

他的名字是阿爾伯特·愛因斯坦——也叫阿爾伯特——他是那個說過如果一個人到30歲時對科學(xué)都沒啥大貢獻，也就永遠不會有貢獻了。你不需要查維基百科去了解我是不是超過30歲。實際上他是想告訴我們，當(dāng)涉及到我在科學(xué)領(lǐng)域的作為時，我是朽木難雕了。幸運的是，我的事業(yè)運還算不錯。

Around age 28, I became very interested in networks, and a few years later, we managed to publish a few key papers that reported the discovery of scale-free networks and really gave birth to a new discipline that we call network science today. And if you really care about it, you can get a PhD now in network science in Budapest, in Boston, and you can study it all over the world.

在28歲時，我對網(wǎng)絡(luò)產(chǎn)生了興趣，幾年后，我成功發(fā)表了幾篇關(guān)于發(fā)現(xiàn)無標(biāo)度網(wǎng)絡(luò)的核心論文，并催生了一門我們今天稱為網(wǎng)絡(luò)科學(xué)的新學(xué)科。如果你對這個學(xué)科也很感興趣，可以在布達佩斯，在波士頓讀取網(wǎng)絡(luò)科學(xué)的博士學(xué)位，也可以在全球各地學(xué)習(xí)這門課程。

A few years later, when I moved to Harvard first as a sabbatical, I became interested in another type of network: that time, the networks within ourselves, how the genes and the proteins and the metabolites link to each other and how they connect to disease. And that interest led to a major explosion within medicine, including the Network Medicine Division at Harvard,that has more than 300 researchers who are using this perspective to treat patients and develop new cures.?

幾年后，當(dāng)我第一次在哈佛進行學(xué)術(shù)休假時，我對另一種形態(tài)的網(wǎng)絡(luò)產(chǎn)生了興趣：在我們自身的網(wǎng)絡(luò)中，基因、蛋白質(zhì)和代謝物如何相互聯(lián)系以及它們與疾病的關(guān)系。這個興趣引發(fā)了醫(yī)學(xué)領(lǐng)域的一陣轟動，包括哈佛大學(xué)的網(wǎng)絡(luò)醫(yī)學(xué)部，有300多名研究人員基于這個想法來治療病人，開發(fā)新的治療方法。

And a few years ago, I thought that I would take this idea of networks and the expertise we had in networks in a different area, that is, to understand success. And why did we do that?

?幾年以前，我覺得我應(yīng)該把網(wǎng)絡(luò)的概念和關(guān)于網(wǎng)絡(luò)的專業(yè)知識應(yīng)用于一個新的領(lǐng)域，用來理解成功。我們?yōu)槭裁匆@么做？

Well, we thought that, to some degree, our success is determined by the networks we're part of -- that our networks can push us forward, they can pull us back. And I was curious if we could use the knowledge and big data and expertise where we develop the networks to really quantify how these things happen. This is a result from that. What you see here is a network of galleries in museums that connect to each other.

我們認為，在某種程度上，我們的成功取決于我們所處的網(wǎng)絡(luò)——我們的網(wǎng)絡(luò)可以推動我們前進，也能拖我們后腿。我好奇我們能否使用在網(wǎng)絡(luò)中獲得的這些知識，結(jié)合大數(shù)據(jù)和專長來量化預(yù)測事情是如何發(fā)生的。這是一個結(jié)果。你在這里看到的是博物館里相互連接的畫廊網(wǎng)絡(luò)。

And through this map that we mapped out last year, we are able to predict very accurately the success of an artist if you give me the first five exhibits that he or she had in their career. Well, as we thought about success, we realized that success is not only about networks; there are so many other dimensions to that. And one of the things we need for success, obviously, is performance.

通過這張我們?nèi)ツ昀L制的圖，如果給我、他或她在開啟他們的職業(yè)生涯前舉辦五個展覽，我們就能夠非常準(zhǔn)確地預(yù)測 一個藝術(shù)家是否成功。當(dāng)我們思考成功時，我們意識到成功不僅跟網(wǎng)絡(luò)有關(guān)；還有很多其他的維度。其中一個成功的必要因素，很明顯就是業(yè)績。

So let's define what's the difference between performance and success. Well, performance is what you do: how fast you run, what kind of paintings you paint, what kind of papers you publish. However, in our working definition, success is about what the community notices from what you did, from your performance: How does it acknowledge it, and how does it reward you for it?

讓我們定義一下業(yè)績和成功的差別。業(yè)績是你做的事情：你跑得有多快，你畫的是什么畫，你發(fā)表的是什么論文。然而，在我們的工作定義中，成功是社會群體從你的業(yè)績中注意到你做的哪些事情，如何承認你的成就，如何獎勵你？

In other terms, your performance is about you, but your success is about all of us. And this was a very important shift for us, because the moment we defined success as being a collective measure that the community provides to us, it became measurable, because if it's in the community, there are multiple data points about that. So we go to school, we exercise, we practice, because we believe that performance leads to success.

換句話說，你的業(yè)績跟你有關(guān)，但你的成功跟大家都有關(guān)。這對我們來說是個非常重要的轉(zhuǎn)變，因為我們把成功定義為社會給予我們的集體評價。這樣一來成功就變得可衡量，因為在一個社會群體中，關(guān)于成功包含著很多數(shù)據(jù)點。我們上學(xué)，我們練習(xí)，我們實踐，因為我們相信業(yè)績會讓我們成功。

But the way we actually started to explore, we realized that performance and success are very, very different animals when it comes to the mathematics of the problem. And let me illustrate that. So what you see here is the fastest man on earth, Usain Bolt. And of course, he wins most of the competitions that he enters. And we know he's the fastest on earth because we have a chronometer to measure his speed.

但當(dāng)我們開始探索，我們開始意識到，以數(shù)學(xué)的方式看待這個問題時，業(yè)績和成功是非常、非常不同的概念，讓我來解釋一下。你在這里看到的是世界上最快的人，尤塞恩·博爾特。當(dāng)然，他贏得了大多數(shù)參與的比賽。我們知道是他是世界上最快的人，因為我們有精密的計時器去測量他的速度。

Well, what is interesting about him is that when he wins, he doesn't do so by really significantly outrunning his competition. He's running at most a percent faster than the one who loses the race. And not only does he run only one percent faster than the second one, but he doesn't run 10 times faster than I do -- and I'm not a good runner, trust me on that.

有趣之處在于當(dāng)他獲勝時，他并沒有明顯地超過競爭對手。他跑得比輸?shù)舯荣惖娜俗疃嗫彀俜种?。他不僅只比第二名快百分之一，他的速度也不超過我的10倍——并且我還不是個擅長跑步的人，這點請相信我。

And every time we are able to measure performance, we notice something very interesting; that is, performance is bounded. What it means is that there are no huge variations in human performance. It varies only in a narrow range, and we do need the chronometer to measure the differences. This is not to say that we cannot see the good from the best ones, but the best ones are very hard to distinguish.

每次我們能夠評估業(yè)績時，我們都會注意到一些有趣的事情：業(yè)績是有界限的。這意味著人類的業(yè)績并沒有巨大的差異。它變化的范圍非常小，我們確實需要精密的計時器來測量這個差異。不是說我們不能從最好的人身上看到好的一面，但最好的人非常難以識別。

And the problem with that is that most of us work in areas where we do not have a chronometer to gauge our performance. Alright, performance is bounded, there are no huge differences between us when it comes to our performance. How about success? Well, let's switch to a different topic, like books. One measure of success for writers is how many people read your work.

并且問題在于我們很多人的工作領(lǐng)域，并沒有精密的計時器來衡量我們的業(yè)績。好了，業(yè)績是有界限的，當(dāng)涉及我們的業(yè)績時，我們之間并沒有顯著的差異。那么成功呢？讓我們轉(zhuǎn)到另一個話題，比如書籍。評估作家成功的一個方法是有多少人閱讀了你的作品。

And so when my previous book came out in 2009, I was in Europe talking with my editor, and I was interested: Who is the competition? And I had some fabulous ones. That week -- Dan Brown came out with "The Lost Symbol," and "The Last Song" also came out, Nicholas Sparks. And when you just look at the list, you realize, you know, performance-wise, there's hardly any difference between these books or mine.

當(dāng)我早先在2009年出版那本書時，我在歐洲和編輯談話，我感興趣的是：誰是我的競爭對手？我有一些炙手可熱的對手。那周—— 丹·布朗出版了《失落的秘符》，并且尼古拉斯·斯帕克斯的《最后一首歌》也問世了。當(dāng)你看這個書單時，你意識到，就業(yè)績而言，這些書和我的之間并無多大差別。

Right? So maybe if Nicholas Sparks's team works a little harder, he could easily be number one, because it's almost by accident who ended up at the top. So I said, let's look at the numbers -- I'm a data person, right? So let's see what were the sales for Nicholas Sparks. And it turns out that that opening weekend, Nicholas Sparks sold more than a hundred thousand copies, which is an amazing number.

是吧？如果尼古拉斯·斯帕克斯的團隊再努力一點，他就可以輕松進入榜首，因為最終誰在暢銷榜頂端幾乎是隨機的。所以我說，讓我們看看數(shù)字吧——我就是干這行的，對吧？讓我們看看尼古拉斯·斯帕克斯的作品銷量。結(jié)果在新書發(fā)售的那個周末，尼古拉斯·斯帕克斯 賣出了10萬多本書，這是個驚人的數(shù)字。

You can actually get to the top of the "New York Times" best-seller list by selling 10,000 copies a week, so he tenfold overcame what he needed to be number one. Yet he wasn't number one. Why? Because there was Dan Brown, who sold 1.2 million copies that weekend. And the reason I like this number is because it shows that, really, when it comes to success, it's unbounded,

你可以看看紐約時報每周銷量在1萬冊以上的暢銷書榜單，所以他只憑借新書銷量的十分之一就能輕松登上榜首。然而他不是第一名。為什么？因為有丹·布朗，他在那個周末賣出了120萬冊。我喜歡這個數(shù)字的原因是因為它真正顯示了，當(dāng)涉及到成功時，它是沒有界限的，

that the best doesn't only get slightly more than the second best but gets orders of magnitude more, because success is a collective measure. We give it to them, rather than we earn it through our performance. So one of things we realized is that performance, what we do, is bounded, but success, which is collective, is unbounded, which makes you wonder:

最好的不止比第二名好一點點，而超越了好幾個數(shù)量級，因為成功是集體的衡量標(biāo)準(zhǔn)。我們給予他們成功，而不是通過我們的業(yè)績獲得它。我們意識到業(yè)績是有界限的，但成功，屬于集體衡量的，是無界的，這一定讓你心生疑惑：

How do you get these huge differences in success when you have such tiny differences in performance? And recently, I published a book that I devoted to that very question. And they didn't give me enough time to go over all of that, so I'm going to go back to the question of, alright, you have success; when should that appear?

當(dāng)人們的業(yè)績表現(xiàn)差異很小的時候，為何成功的差異如此之大？最近，我出版了一本關(guān)于這個問題的書。我沒有太多時間詳細介紹這本書，所以我打算回到這個問題，成功通常會在什么時候出現(xiàn)呢？

So let's go back to the party spoiler and ask ourselves: Why did Einstein make this ridiculous statement, that only before 30 you could actually be creative? Well, because he looked around himself and he saw all these fabulous physicists that created quantum mechanics and modern physics, and they were all in their 20s and early 30s when they did so. And it's not only him.

那么讓我們回到派對搗亂者的話題，問問我們自己：為什么愛因斯坦要發(fā)表這樣荒謬的言論，人的創(chuàng)造力止步于30歲？因為他發(fā)現(xiàn)周圍所有這些創(chuàng)造量子力學(xué)和現(xiàn)代物理學(xué)的偉大物理學(xué)家，他們的偉大成就都是誕生在20多歲和30歲出頭。并不是只有他這樣想。

It's not only observational bias, because there's actually a whole field of genius research that has documented the fact that, if we look at the people we admire from the past and then look at what age they made their biggest contribution, whether that's music, whether that's science, whether that's engineering, most of them tend to do so in their 20s, 30s, early 40s at most.

這不僅是觀察偏差，因為事實上有一整個領(lǐng)域的天才研究都證明了這一點，如果回顧一下我們崇拜的先人，然后再看他們做出最大貢獻的年紀，不管在音樂，在科學(xué)，還是在工程領(lǐng)域，大部分人都是在他們20歲，30歲，最多40歲出頭時做出了這些成績。

But there's a problem with this genius research. Well, first of all, it created the impression to us that creativity equals youth, which is painful, right? And it also has an observational bias, because it only looks at geniuses and doesn't look at ordinary scientists and doesn't look at all of us and ask, is it really true that creativity vanishes as we age?

但這個天才研究有個問題。首先，它為大眾制造了一種印象，即創(chuàng)造力等于年輕，真讓人傷心，不是嗎？并且它也存在觀察偏差，因為它只觀察了天才，并沒研究普通科學(xué)家，并沒有看著我們這些人問，隨著年齡的增長，創(chuàng)造力真的會消失嗎？

So that's exactly what we tried to do, and this is important for that to actually have references. So let's look at an ordinary scientist like myself, and let's look at my career. So what you see here is all the papers that I've published from my very first paper, in 1989; I was still in Romania when I did so, till kind of this year. And vertically, you see the impact of the paper, that is, how many citations, how many other papers have been written that cited that work.

所以這正是我們嘗試做的，并且有參照對象很重要。那么讓我們看看像我這樣平凡科學(xué)家的職業(yè)生涯。這里是我發(fā)表的全部論文，從1989年發(fā)表的最早一篇論文；當(dāng)時我還在羅馬尼亞，直到今年這個時候?？v坐標(biāo)，你可以看到論文的影響，也就是被引用的次數(shù)，有多少其他人發(fā)表的論文引用了我的文章。

And when you look at that, you see that my career has roughly three different stages. I had the first 10 years where I had to work a lot and I don't achieve much. No one seems to care about what I do, right? There's hardly any impact. That time, I was doing material science, and then I kind of discovered for myself networks and then started publishing in networks.

當(dāng)你看這個數(shù)據(jù)時，可以看到我的職業(yè)生涯有三個階段。我第一個10年，工作很多，但卻并沒有多少成就。似乎沒人關(guān)注我做的事情，對吧？沒有一點影響力。當(dāng)時，我在做材料科學(xué)，然后我注冊了自己的網(wǎng)絡(luò)賬號，開始發(fā)表網(wǎng)絡(luò)文章，

And that led from one high-impact paper to the other one. And it really felt good. That was that stage of my career. So the question is, what happens right now? And we don't know, because there hasn't been enough time passed yet to actually figure out how much impact those papers will get; it takes time to acquire.

從那以后，高影響力的文章我發(fā)表了一篇又一篇。那時感覺真是很好，那是我職業(yè)生涯的高光時刻。那么問題是，現(xiàn)在發(fā)生了什么？我們不知道，現(xiàn)在就去計算出這些論文會產(chǎn)生怎樣的影響還為時尚早，我們需要時間來獲取這些信息。

Well, when you look at the data, it seems to be that Einstein, the genius research, is right, and I'm at that stage of my career. So we said, OK, let's figure out how does this really happen, first in science. And in order not to have the selection bias, to look only at geniuses, we ended up reconstructing the career of every single scientist from 1900 till today and finding for all scientists what was their personal best,

當(dāng)你看這個數(shù)據(jù)時，會覺得愛因斯坦和天才研究的結(jié)論是對的，我正在我職業(yè)生涯的高光階段。那么讓我們看看這究竟是如何發(fā)生的，首先看看科學(xué)領(lǐng)域。為了不產(chǎn)生選擇偏差，只看天才，我們最終重建了1900年至今每一位科學(xué)家的職業(yè)生涯，并找到了所有科學(xué)家的個人最高成就，

whether they got the Nobel Prize or they never did, or no one knows what they did, even their personal best. And that's what you see in this slide. Each line is a career, and when you have a light blue dot on the top of that career, it says that was their personal best. And the question is, when did they actually make their biggest discovery?

不管他獲得了諾貝爾獎還是沒有，或是沒人問津，即便是他最好的成就。這就是你們在這張幻燈片上看到的。每條線是個職業(yè)生涯，在職業(yè)生涯的頂端有一個淺藍色的點，代表著他們個人的最好成就。問題是，他們最重大的發(fā)現(xiàn)發(fā)生在什么時候？

To quantify that, we look at what's the probability that you make your biggest discovery, let's say, one, two, three or 10 years into your career? We're not looking at real age. We're looking at what we call "academic age." Your academic age starts when you publish your first papers. I know some of you are still babies. So let's look at the probability that you publish your highest-impact paper.

要量化這點，我們看的是你獲得最大發(fā)現(xiàn)的概率是多少，比如你職業(yè)生涯的的第1，2，3或者10年。我們真正要看的并不是年紀。我們看的是所謂的“學(xué)術(shù)年齡”。你的學(xué)術(shù)年齡始于你發(fā)表第一篇論文的時候。我知道你們有些人還沒開始自己的學(xué)術(shù)生涯。那么讓我們來看看你發(fā)表最高影響力論文的概率。

And what you see is, indeed, the genius research is right. Most scientists tend to publish their highest-impact paper in the first 10, 15 years in their career, and it tanks after that. It tanks so fast that I'm about -- I'm exactly 30 years into my career, and the chance that I will publish a paper that would have a higher impact than anything that I did before is less than one percent.

你看到的是，的確，天才研究的結(jié)論是正確的。很多科學(xué)家發(fā)表的影響力最高的論文傾向于發(fā)表在他們職業(yè)生涯的前10到15年，在那之后就會直線下降。它下降得如此之快——我如今正處在我職業(yè)的第30個年頭，我發(fā)表一篇比過往有更高影響力的論文的概率不到1%。

I am in that stage of my career, according to this data. But there's a problem with that. We're not doing controls properly. So the control would be, what would a scientist look like who makes random contribution to science? Or what is the productivity of the scientist? When do they write papers?

根據(jù)這個數(shù)據(jù)，我正處在職業(yè)生涯的這個階段。但這里有個問題。我們的對照數(shù)據(jù)有問題。對照數(shù)據(jù)就是，對科學(xué)做出隨機貢獻的科學(xué)家會是什么樣子？或者科學(xué)家的生產(chǎn)力怎樣？他們什么時候?qū)懙恼撐模?/p>

So we measured the productivity, and amazingly, the productivity, your likelihood of writing a paper in year one, 10 or 20 in your career, is indistinguishable from the likelihood of having the impact in that part of your career. And to make a long story short, after lots of statistical tests, there's only one explanation for that, that really,

所以我們評估了生產(chǎn)力，令人驚訝的是，生產(chǎn)力，你在職業(yè)生涯的第1年、第10年或第20年寫論文的概率，與論文產(chǎn)生影響的概率幾乎無法區(qū)分。長話短說，在很多的數(shù)據(jù)檢驗后，只有一個解釋，真相是，

the way we scientists work is that every single paper we write, every project we do, has exactly the same chance of being our personal best. That is, discovery is like a lottery ticket. And the more lottery tickets we buy, the higher our chances. And it happens to be so that most scientists buy most of their lottery tickets in the first 10, 15 years of their career, and after that, their productivity decreases.

我們科學(xué)家的工作，我們寫的每篇論文，做的每個項目都有同樣的概率成為我們個人的最佳成果。那就是，發(fā)現(xiàn)就像中彩票。我們買了越多的彩票，我們中獎的幾率就越高。碰巧的是，很多科學(xué)家在他們職業(yè)生涯的頭10年，15年買了大部分的彩票，在那之后，他們的生產(chǎn)力就下降了。

They're not buying any more lottery tickets. So it looks as if they would not be creative. In reality, they stopped trying. So when we actually put the data together, the conclusion is very simple: success can come at any time. It could be your very first or very last paper of your career. It's totally random in the space of the projects. It is the productivity that changes.

他們不再買更多的彩票。所以看起來他們沒有創(chuàng)造力了?，F(xiàn)實中，他們停止了嘗試。所以當(dāng)我們把數(shù)據(jù)放在一起時， 結(jié)論非常簡單：成功可能隨時會來。它可能是你職業(yè)生涯中最早或最后的論文。它在項目的空間中完全是隨機的。改變的是你的生產(chǎn)力。

Let me illustrate that. Here is Frank Wilczek, who got the Nobel Prize in Physics for the very first paper he ever wrote in his career as a graduate student. More interesting is John Fenn, who, at age 70, was forcefully retired by Yale University. They shut his lab down, and at that moment, he moved to Virginia Commonwealth University, opened another lab,

讓我解釋一下。這是獲得諾貝爾物理學(xué)獎的弗蘭克·威爾切克，他得獎要歸功于研究生時寫的第一篇論文。更有趣的是約翰·芬，他在70歲時，被耶魯大學(xué)強制退休，他們關(guān)閉了他的實驗室，那時，他搬到了弗吉尼亞聯(lián)邦大學(xué)，開了另一個實驗室，

and it is there, at age 72, that he published a paper for which, 15 years later, he got the Nobel Prize for Chemistry. And you think, OK, well, science is special, but what about other areas where we need to be creative? So let me take another typical example: entrepreneurship. Silicon Valley, the land of the youth, right?

就在那里，在年紀72歲時，他發(fā)表了一篇論文，這篇論文在15年后獲得了諾貝爾化學(xué)獎。你會想，科學(xué)領(lǐng)域比較特殊，但其他需要我們有創(chuàng)造力的領(lǐng)域呢？那么讓我們再看看另一個典型的例子：創(chuàng)業(yè)。硅谷。年輕人的領(lǐng)地，對吧？

And indeed, when you look at it, you realize that the biggest awards, the TechCrunch Awards and other awards, are all going to people whose average age is late 20s, very early 30s. You look at who the VCs give the money to, some of the biggest VC firms -- all people in their early 30s. Which, of course, we know; there is this ethos in Silicon Valley that youth equals success.

確實，當(dāng)你看這個領(lǐng)域時，你發(fā)現(xiàn)最大的獎勵，TechCrunch Awards或其他獎勵，全都給了平均年紀在30歲左右的人。再看看VC的錢都給了誰，一些最大的VC企業(yè)——幾乎所有的人都在30歲出頭。當(dāng)然，我們知道；硅谷有這樣一種風(fēng)氣：年輕等于成功。

Not when you look at the data, because it's not only about forming a company -- forming a company is like productivity, trying, trying, trying -- when you look at which of these individuals actually put out a successful company, a successful exit. And recently, some of our colleagues looked at exactly that question.

不過，當(dāng)你看數(shù)據(jù)的時候就不會這樣認為了?？纯催@些人當(dāng)中有誰真正成立了一家成功的公司——成立一個公司就像生產(chǎn)力，嘗試、嘗試、再嘗試。因為這不僅關(guān)于成立一個公司。最近，我們的幾位同事正好研究了這個問題。

And it turns out that yes, those in the 20s and 30s put out a huge number of companies, form lots of companies, but most of them go bust. And when you look at the successful exits, what you see in this particular plot, the older you are, the more likely that you will actually hit the stock market or the sell the company successfully.

果不期然，這些年紀 在20多歲和30多歲的人創(chuàng)立了大量的公司，很多公司，但大部分都破產(chǎn)了。再看看那些成功的例子，你在這個圖中可以看到，你年紀越大，就越有可能轟動股票市場或者成功出售公司。

This is so strong, actually, that if you are in the 50s, you are twice as likely to actually have a successful exit than if you are in your 30s. So in the end, what is it that we see, actually? What we see is that creativity has no age. Productivity does, right? Which is telling me that at the end of the day, if you keep trying -- you could still succeed and succeed over and over. So my conclusion is very simple: I am off the stage, back in my lab. Thank you.

數(shù)據(jù)很顯著，事實上，如果你50多歲，你成功的機會是你30歲時的兩倍。所以最后，我們看到了什么？我們看到的是創(chuàng)意并無年齡限制。生產(chǎn)力才是關(guān)鍵，對吧？這就告訴我們，如果你不斷嘗試—— 你仍然可以不斷取得成功。所以我的結(jié)論很簡單：演講結(jié)束后，我得回到實驗干活兒了。謝謝。