The real relationship between your age and your chance of success | Albert-László Barabási
285,456 views ・ 2019-09-03
请双击下面的英文字幕来播放视频。
翻译人员: psjmz mz
校对人员: Yolanda Zhang
00:12
Today, actually, is
a very special day for me,
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今天对我来说很特别,
00:14
because it is my birthday.
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因为是我的生日。
00:16
(Applause)
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(鼓掌)
00:20
And so, thanks to all of you
for joining the party.
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谢谢大家参与这个聚会。
00:24
(Laughter)
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(笑声)
00:25
But every time you throw a party,
there's someone there to spoil it. Right?
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可是,每次你举办聚会的时候,
总是有人捣蛋,对吧?
00:30
(Laughter)
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(笑声)
00:31
And I'm a physicist,
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我是个物理学家,
00:32
and this time I brought
another physicist along to do so.
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这次我带来了另一个物理学家。
00:36
His name is Albert Einstein --
also Albert -- and he's the one who said
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他的名字是阿尔伯特·爱因斯坦——
也叫阿尔伯特——他是那个说过
00:41
that the person who has not made
his great contributions to science
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如果一个人到30岁时对科学
00:46
by the age of 30
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都没啥大贡献,
00:47
will never do so.
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也就永远不会有贡献了。
00:49
(Laughter)
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(笑声)
00:50
Now, you don't need to check Wikipedia
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你不需要查维基百科
00:52
that I'm beyond 30.
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去了解我是不是超过30岁。
00:54
(Laughter)
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(笑声)
00:55
So, effectively, what
he is telling me, and us,
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实际上他是想告诉我们,
00:59
is that when it comes to my science,
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当涉及到我在科学领域的作为时,
01:01
I'm deadwood.
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我是朽木难雕了。
01:04
Well, luckily, I had my share
of luck within my career.
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幸运的是,我的事业运还算不错。
01:10
Around age 28, I became
very interested in networks,
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在28岁时,我对网络产生了兴趣,
01:13
and a few years later, we managed
to publish a few key papers
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几年后,我成功发表了几篇
01:18
that reported the discovery
of scale-free networks
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关于发现无标度网络的核心论文,
01:22
and really gave birth to a new discipline
that we call network science today.
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并催生了一门我们今天称为
网络科学的新学科。
01:26
And if you really care about it,
you can get a PhD now in network science
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如果你对这个学科也很感兴趣,
可以在布达佩斯,在波士顿
01:30
in Budapest, in Boston,
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读取网络科学的博士学位,
01:32
and you can study it all over the world.
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也可以在全球各地学习这门课程。
01:35
A few years later,
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几年后,
01:37
when I moved to Harvard
first as a sabbatical,
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当我第一次在哈佛进行学术休假时,
01:40
I became interested
in another type of network:
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我对另一种形态的网络产生了兴趣:
01:43
that time, the networks within ourselves,
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在我们自身的网络中,
01:46
how the genes and the proteins
and the metabolites link to each other
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基因、蛋白质和代谢物如何相互联系
01:50
and how they connect to disease.
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以及它们与疾病的关系。
01:53
And that interest led
to a major explosion within medicine,
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这个兴趣引发了
医学领域的一阵轰动,
01:57
including the Network Medicine
Division at Harvard,
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包括哈佛大学的网络医学部,
02:01
that has more than 300 researchers
who are using this perspective
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有300多名研究人员
基于这个想法来治疗病人,
02:05
to treat patients and develop new cures.
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开发新的治疗方法。
02:09
And a few years ago,
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几年以前,
02:11
I thought that I would take
this idea of networks
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我觉得我应该把网络的概念
02:13
and the expertise we had in networks
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和关于网络的专业知识
02:15
in a different area,
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应用于一个新的领域,
02:17
that is, to understand success.
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用来理解成功。
02:19
And why did we do that?
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我们为什么要这么做?
02:20
Well, we thought that, to some degree,
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我们认为,在某种程度上,
02:23
our success is determined
by the networks we're part of --
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我们的成功取决于我们所处的网络——
02:26
that our networks can push us forward,
they can pull us back.
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我们的网络可以推动我们前进,
也能拖我们后腿。
02:30
And I was curious if we could use
the knowledge and big data and expertise
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我好奇我们能否使用
在网络中获得的这些知识,
02:35
where we develop the networks
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结合大数据和专长
02:36
to really quantify
how these things happen.
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来量化事情是如何发生的。
02:40
This is a result from that.
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这是一个结果。
02:41
What you see here is a network
of galleries in museums
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你在这里看到的是博物馆里
02:44
that connect to each other.
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相互连接的画廊网络。
02:46
And through this map
that we mapped out last year,
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通过这张我们去年绘制的图,
02:50
we are able to predict very accurately
the success of an artist
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如果给我他或她在他们的
职业生涯举办的前五个展览,
02:55
if you give me the first five exhibits
that he or she had in their career.
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我们就能够非常准确地预测
一个艺术家是否成功。
03:01
Well, as we thought about success,
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当我们思考成功时,
03:04
we realized that success
is not only about networks;
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我们意识到成功不仅跟网络有关;
03:07
there are so many
other dimensions to that.
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还有很多其他的维度。
03:10
And one of the things
we need for success, obviously,
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其中一个成功的必要因素,
03:13
is performance.
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很明显就是业绩。
03:14
So let's define what's the difference
between performance and success.
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让我们定义一下业绩和成功的差别。
03:18
Well, performance is what you do:
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业绩是你做的事情:
03:20
how fast you run,
what kind of paintings you paint,
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你跑得有多快,你画的是什么画,
03:23
what kind of papers you publish.
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你发表的是什么论文。
03:25
However, in our working definition,
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然而,在我们的工作定义中,
03:28
success is about what the community
notices from what you did,
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成功是社群从你的业绩中
03:32
from your performance:
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注意到你做的哪些事情,
03:34
How does it acknowledge it,
and how does it reward you for it?
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如何承认你的成就,如何奖励你?
03:38
In other terms,
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换句话说,
03:39
your performance is about you,
but your success is about all of us.
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你的业绩跟你有关,
但你的成功跟大家都有关。
03:45
And this was a very
important shift for us,
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这对我们来说是个非常重要的转变,
03:48
because the moment we defined success
as being a collective measure
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因为我们把成功定义为社群
03:52
that the community provides to us,
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给予我们的集体评价。
03:54
it became measurable,
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这样一来成功就变得可衡量,
03:56
because if it's in the community,
there are multiple data points about that.
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因为在一个社群中,
关于成功包含着很多数据点。
04:00
So we go to school,
we exercise, we practice,
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我们上学,我们练习,我们实践,
04:06
because we believe
that performance leads to success.
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因为我们相信业绩会让我们成功。
04:09
But the way we actually
started to explore,
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但当我们开始探索,
04:11
we realized that performance and success
are very, very different animals
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我们开始意识到
以数学的方式看待这个问题时,
04:15
when it comes to
the mathematics of the problem.
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业绩和成功是非常,
非常不同的概念,
04:18
And let me illustrate that.
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让我来解释一下。
04:20
So what you see here is
the fastest man on earth, Usain Bolt.
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你在这里看到的是世界上
最快的人,尤塞恩·博尔特。
04:25
And of course, he wins most of
the competitions that he enters.
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当然,他赢得了大多数参与的比赛。
04:30
And we know he's the fastest on earth
because we have a chronometer
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我们知道是他是世界上最快的人,
因为我们有精密的计时器
04:33
to measure his speed.
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去测量他的速度。
04:34
Well, what is interesting about him
is that when he wins,
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有趣之处在于当他获胜时,
04:38
he doesn't do so by really significantly
outrunning his competition.
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他并没有明显地超过竞争对手。
04:44
He's running at most a percent faster
than the one who loses the race.
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他跑得比输掉比赛的人
最多快百分之一。
04:49
And not only does he run only
one percent faster than the second one,
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他不仅只比第二名快百分之一,
04:53
but he doesn't run
10 times faster than I do --
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他的速度也不超过我的10倍——
04:56
and I'm not a good runner,
trust me on that.
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并且我还不是个擅长跑步的人,
这点请相信我。
04:58
(Laughter)
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(笑声)
04:59
And every time we are able
to measure performance,
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每次我们能够评估业绩时,
05:03
we notice something very interesting;
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我们都会注意到一些有趣的事情:
05:05
that is, performance is bounded.
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业绩是有界限的。
05:07
What it means is that there are
no huge variations in human performance.
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这意味着人类的业绩
并没有巨大的差异。
05:11
It varies only in a narrow range,
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它变化的范围非常小,
05:14
and we do need the chronometer
to measure the differences.
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我们确实需要精密的计时器
来测量这个差异。
05:18
This is not to say that we cannot
see the good from the best ones,
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不是说我们不能从
最好的人身上看到好的一面,
05:21
but the best ones
are very hard to distinguish.
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但最好的人非常难以识别。
05:24
And the problem with that
is that most of us work in areas
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并且问题在于我们很多人的工作领域
05:27
where we do not have a chronometer
to gauge our performance.
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并没有精密的计时器
来衡量我们的业绩。
05:31
Alright, performance is bounded,
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好了,业绩是有界限的,
05:32
there are no huge differences between us
when it comes to our performance.
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当涉及我们的业绩时,
我们之间并没有显著的差异。
05:36
How about success?
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那么成功呢?
05:37
Well, let's switch to
a different topic, like books.
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让我们转到另一个话题,比如书籍。
05:40
One measure of success for writers is
how many people read your work.
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评估作家成功的一个方法是
有多少人阅读了你的作品。
05:46
And so when my previous book
came out in 2009,
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当我早先那本书
在2009年出版时,
05:51
I was in Europe talking with my editor,
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我在欧洲和编辑谈话,
05:53
and I was interested:
Who is the competition?
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我感兴趣的是:谁是我的竞争对手?
05:56
And I had some fabulous ones.
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我有一些炙手可热的对手。
05:59
That week --
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那周——
06:00
(Laughter)
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(笑声)
06:01
Dan Brown came out with "The Lost Symbol,"
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丹·布朗出版了《失落的秘符》,
06:04
and "The Last Song" also came out,
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并且尼古拉斯·斯帕克斯
06:07
Nicholas Sparks.
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的《最后一首歌》也问世了。
06:09
And when you just look at the list,
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当你看这个书单时,
06:12
you realize, you know, performance-wise,
there's hardly any difference
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你意识到,就业绩而言,这些书
06:15
between these books or mine.
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和我的之间并无多大差别。
06:17
Right?
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是吧?
06:18
So maybe if Nicholas Sparks's team
works a little harder,
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如果尼古拉斯·斯帕克斯
的团队再努力一点,
06:23
he could easily be number one,
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他就可以轻松进入榜首,
06:25
because it's almost by accident
who ended up at the top.
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因为最终谁在畅销榜顶端
几乎是随机的。
06:28
So I said, let's look at the numbers --
I'm a data person, right?
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所以我说,让我们看看数字吧——
我就是干这行的,对吧?
06:31
So let's see what were
the sales for Nicholas Sparks.
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让我们看看尼古拉斯·斯帕克斯
的作品销量。
06:36
And it turns out that
that opening weekend,
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结果在新书发售的那个周末,
06:38
Nicholas Sparks sold more than
a hundred thousand copies,
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尼古拉斯·斯帕克斯
卖出了10万多本书,
06:41
which is an amazing number.
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这是个惊人的数字。
06:42
You can actually get to the top
of the "New York Times" best-seller list
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你可以看看纽约时报
每周销量在1万册以上的
06:46
by selling 10,000 copies a week,
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畅销书榜单,
06:48
so he tenfold overcame
what he needed to be number one.
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所以他只凭借新书销量的
十分之一就能轻松登上榜首。
06:52
Yet he wasn't number one.
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然而他不是第一名。
06:53
Why?
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为什么?
06:54
Because there was Dan Brown,
who sold 1.2 million copies that weekend.
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因为有丹·布朗,他在
那个周末卖出了120万册。
06:59
(Laughter)
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(笑声)
07:01
And the reason I like this number
is because it shows that, really,
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我喜欢这个数字的原因
是因为它真正显示了,
07:05
when it comes to success, it's unbounded,
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当涉及到成功时,它是没有界限的,
07:08
that the best doesn't only get
slightly more than the second best
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最好的不止比第二名好一点点,
07:14
but gets orders of magnitude more,
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而超越了好几个数量级,
07:17
because success is a collective measure.
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因为成功是集体的衡量标准。
07:20
We give it to them, rather than
we earn it through our performance.
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我们给予他们成功,而不是
通过我们的业绩获得它。
07:24
So one of things we realized is that
performance, what we do, is bounded,
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我们意识到业绩是有界限的,
07:30
but success, which is
collective, is unbounded,
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但成功,属于集体衡量的,是无界的,
07:32
which makes you wonder:
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这一定让你心生疑惑:
07:34
How do you get these
huge differences in success
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当人们的业绩表现差异很小的时候,
07:37
when you have such tiny
differences in performance?
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为何成功的差异如此之大?
07:40
And recently, I published a book
that I devoted to that very question.
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最近,我出版了一本
关于这个问题的书。
07:44
And they didn't give me enough time
to go over all of that,
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我没有太多时间详细介绍这本书,
07:47
so I'm going to go back
to the question of,
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所以我打算回到这个问题,
07:49
alright, you have success;
when should that appear?
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成功通常会在什么时候出现呢?
07:52
So let's go back to the party spoiler
and ask ourselves:
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那么让我们回到派对捣乱者
的话题,问问我们自己:
07:57
Why did Einstein make
this ridiculous statement,
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为什么爱因斯坦要发表
这样荒谬的言论,
08:00
that only before 30
you could actually be creative?
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人的创造力止步于30岁?
08:03
Well, because he looked around himself
and he saw all these fabulous physicists
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因为他发现周围
所有这些创造量子力学
08:08
that created quantum mechanics
and modern physics,
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和现代物理学的伟大物理学家,
08:11
and they were all in their 20s
and early 30s when they did so.
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他们的伟大成就都是诞生在
20多岁和30岁出头。
08:15
And it's not only him.
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并不是只有他这样想。
08:16
It's not only observational bias,
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这不仅是观察偏差,
08:18
because there's actually
a whole field of genius research
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因为事实上有一整个
领域的天才研究
08:22
that has documented the fact that,
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都证明了这一点,
08:24
if we look at the people
we admire from the past
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如果回顾一下我们崇拜的先人,
08:28
and then look at what age
they made their biggest contribution,
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然后再看他们做出
最大贡献的年纪,
08:31
whether that's music,
whether that's science,
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不管在音乐,在科学,
08:33
whether that's engineering,
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还是在工程领域,
08:35
most of them tend to do so
in their 20s, 30s, early 40s at most.
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大部分人都是在他们20岁,30岁,
最多40岁出头时做出了这些成绩。
08:41
But there's a problem
with this genius research.
166
521914
2791
但这个天才研究有个问题。
08:45
Well, first of all, it created
the impression to us
167
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3280
首先,它为大众制造了一种印象,
08:48
that creativity equals youth,
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3479
即创造力等于年轻,
08:52
which is painful, right?
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真让人伤心,不是吗?
08:53
(Laughter)
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1951
(笑声)
08:55
And it also has an observational bias,
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4088
并且它也存在观察偏差,
08:59
because it only looks at geniuses
and doesn't look at ordinary scientists
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因为它只观察了天才,
并没研究普通科学家,
09:04
and doesn't look at all of us and ask,
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1965
并没有看着我们这些人问,
09:06
is it really true that creativity
vanishes as we age?
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3185
随着年龄的增长,
创造力真的会消失吗?
09:10
So that's exactly what we tried to do,
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1877
所以这正是我们尝试做的,
09:12
and this is important for that
to actually have references.
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3803
并且有参照对象很重要。
09:16
So let's look at an ordinary
scientist like myself,
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2643
那么让我们看看像我
这样平凡科学家
09:18
and let's look at my career.
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的职业生涯。
09:20
So what you see here is all the papers
that I've published
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3202
这里是我发表的全部论文,
09:23
from my very first paper, in 1989;
I was still in Romania when I did so,
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5115
从1989年发表的最早一篇论文;
当时我还在罗马尼亚,
09:28
till kind of this year.
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568688
1593
直到今年这个时候。
09:30
And vertically, you see
the impact of the paper,
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2518
纵坐标,你可以看到论文的影响,
09:33
that is, how many citations,
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1403
也就是被引用的次数,
09:34
how many other papers
have been written that cited that work.
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3988
有多少其他人发表的论文
引用了我的工作。
09:39
And when you look at that,
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1300
当你看这个数据时,
09:40
you see that my career
has roughly three different stages.
186
580721
2813
可以看到我的职业生涯有三个阶段。
09:43
I had the first 10 years
where I had to work a lot
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2435
我第一个10年,工作很多,
但却并没有多少成就。
09:46
and I don't achieve much.
188
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1276
09:47
No one seems to care
about what I do, right?
189
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2118
似乎没人关注我做的事情,对吧?
09:49
There's hardly any impact.
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1681
没有一点影响力。
09:51
(Laughter)
191
591164
1404
(笑声)
09:52
That time, I was doing material science,
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2887
当时,我在做材料科学,
09:55
and then I kind of discovered
for myself networks
193
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3691
然后我自己发现了网络,
09:59
and then started publishing in networks.
194
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1947
然后开始发表网络的文章,
10:01
And that led from one high-impact
paper to the other one.
195
601189
3073
从那以后,高影响力的文章
我发表了一篇又一篇。
10:04
And it really felt good.
That was that stage of my career.
196
604286
3104
那时感觉真是很好,那是
我职业生涯的高光时刻。
10:07
(Laughter)
197
607414
1282
(笑声)
10:08
So the question is,
what happens right now?
198
608720
3208
那么问题是,现在发生了什么?
10:12
And we don't know, because there
hasn't been enough time passed yet
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3239
我们不知道,现在就去
计算出这些论文
10:15
to actually figure out how much impact
those papers will get;
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615850
2987
会产生怎样的影响还为时尚早,
需要时间来获取这些信息。
10:18
it takes time to acquire.
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618861
1227
当你看这个数据时,
10:20
Well, when you look at the data,
202
620112
1569
10:21
it seems to be that Einstein,
the genius research, is right,
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621705
2854
会觉得爱因斯坦和
天才研究的结论是对的,
10:24
and I'm at that stage of my career.
204
624583
1811
我在我职业生涯的高光阶段。
10:26
(Laughter)
205
626418
2308
(笑声)
10:28
So we said, OK, let's figure out
how does this really happen,
206
628750
5974
那么让我们看看
这究竟是如何发生的,
10:34
first in science.
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634748
1778
首先看看科学领域。
10:36
And in order not to have
the selection bias,
208
636550
3632
为了不产生选择偏差,
10:40
to look only at geniuses,
209
640206
1337
只看天才,
10:41
we ended up reconstructing the career
of every single scientist
210
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3716
我们最终重建了1900年至今每一位
10:45
from 1900 till today
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2502
科学家的职业生涯,
10:47
and finding for all scientists
what was their personal best,
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3712
并找到了所有科学家
的个人最高成就,
10:51
whether they got the Nobel Prize
or they never did,
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2812
不管他获得了诺贝尔奖还是没有,
10:54
or no one knows what they did,
even their personal best.
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3407
或是没人问津,即便是他最好的成就。
10:57
And that's what you see in this slide.
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657836
1915
这就是你们在这张幻灯片上看到的。
10:59
Each line is a career,
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659775
1573
每条线是个职业生涯,
11:01
and when you have a light blue dot
on the top of that career,
217
661372
3003
在职业生涯的顶端
有一个浅蓝色的点,
11:04
it says that was their personal best.
218
664399
2040
代表着他们个人的最好成就。
11:06
And the question is,
219
666463
1155
问题是,
11:07
when did they actually make
their biggest discovery?
220
667642
3568
他们最重大的发现
发生在什么时候?
11:11
To quantify that,
221
671234
1165
要量化这点,
11:12
we look at what's the probability
that you make your biggest discovery,
222
672423
3376
我们看的是你获得
最大发现的概率是多少,
11:15
let's say, one, two, three
or 10 years into your career?
223
675823
2672
比如你职业生涯的
的第1,2,3或者10年。
11:18
We're not looking at real age.
224
678519
1480
我们真正要看的并不是年纪。
我们看的是所谓的“学术年龄。”
11:20
We're looking at
what we call "academic age."
225
680023
2134
你的学术年龄始于
你发表第一篇论文的时候。
11:22
Your academic age starts
when you publish your first papers.
226
682181
3250
11:25
I know some of you are still babies.
227
685455
1779
我知道你们有些人还是婴儿。
11:27
(Laughter)
228
687258
1397
(笑声)
11:28
So let's look at the probability
229
688679
2706
那么让我们来看看
11:31
that you publish
your highest-impact paper.
230
691409
2066
你发表最高影响力论文的概率。
11:33
And what you see is, indeed,
the genius research is right.
231
693499
3071
你看到的是,的确,
天才研究的结论是正确的。
11:36
Most scientists tend to publish
their highest-impact paper
232
696594
3024
很多科学家发表的
影响力最高的论文倾向于
11:39
in the first 10, 15 years in their career,
233
699642
2899
发表在他们职业生涯的
前10到15年,
11:42
and it tanks after that.
234
702565
3133
在那之后就会直线下降。
11:45
It tanks so fast that I'm about --
I'm exactly 30 years into my career,
235
705722
5107
它下降得如此之快——我如今
正处在我职业的第30个年头,
11:50
and the chance that I will publish a paper
that would have a higher impact
236
710853
3540
我发表一篇比过往有
更高影响力的论文
11:54
than anything that I did before
237
714417
1940
的概率
11:56
is less than one percent.
238
716381
1353
不到1%。
11:57
I am in that stage of my career,
according to this data.
239
717758
3049
根据这个数据,我正处在
职业生涯的这个阶段。
12:01
But there's a problem with that.
240
721648
1843
但这里有个问题。
12:03
We're not doing controls properly.
241
723515
3675
我们的对照数据有问题。
12:07
So the control would be,
242
727214
1417
对照数据就是,
12:08
what would a scientist look like
who makes random contribution to science?
243
728655
4607
对科学做出随机贡献的
科学家会是什么样子?
12:13
Or what is the productivity
of the scientist?
244
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2995
或者科学家的生产力怎样?
12:16
When do they write papers?
245
736305
2006
他们什么时候写的论文?
12:18
So we measured the productivity,
246
738335
2444
所以我们评估了生产力,
12:20
and amazingly, the productivity,
247
740803
2052
令人惊讶的是,生产力,
12:22
your likelihood of writing a paper
in year one, 10 or 20 in your career,
248
742879
4131
你在职业生涯的第1年、第10年
或第20年写论文的概率,
12:27
is indistinguishable from the likelihood
of having the impact
249
747034
3606
与论文产生影响的概率
12:30
in that part of your career.
250
750664
1775
几乎无法区分。
12:33
And to make a long story short,
251
753026
1783
长话短说,
12:34
after lots of statistical tests,
there's only one explanation for that,
252
754833
4228
在很多的数据检验后,
只有一个解释,
12:39
that really, the way we scientists work
253
759085
2894
真相是,我们科学家的工作,
12:42
is that every single paper we write,
every project we do,
254
762003
3633
我们写的每篇论文,做的每个项目
12:45
has exactly the same chance
of being our personal best.
255
765660
4160
都有同样的概率成为
我们个人的最佳成果。
12:49
That is, discovery is like
a lottery ticket.
256
769844
4953
那就是,发现就像中彩票。
12:54
And the more lottery tickets we buy,
257
774821
2351
我们买了越多的彩票,
12:57
the higher our chances.
258
777196
1507
我们中奖的几率就越高。
12:58
And it happens to be so
259
778727
1559
碰巧的是,
13:00
that most scientists buy
most of their lottery tickets
260
780310
2719
很多科学家在他们
职业生涯的头10年,
13:03
in the first 10, 15 years of their career,
261
783053
2460
15年买了大部分的彩票,
13:05
and after that,
their productivity decreases.
262
785537
3413
在那之后,他们的生产力就下降了。
13:09
They're not buying
any more lottery tickets.
263
789411
2084
他们不再买更多的彩票。
13:11
So it looks as if
they would not be creative.
264
791519
3444
所以看起来他们没有创造力了。
13:14
In reality, they stopped trying.
265
794987
1999
现实中,他们停止了尝试。
13:17
So when we actually put the data together,
the conclusion is very simple:
266
797509
3915
所以当我们把数据放在一起时,
结论非常简单:
13:21
success can come at any time.
267
801448
2331
成功可能随时会来。
13:23
It could be your very first
or very last paper of your career.
268
803803
3735
它可能是你职业生涯中
最早或最后的论文。
13:27
It's totally random
in the space of the projects.
269
807562
4288
它在项目的空间中完全是随机的。
13:31
It is the productivity that changes.
270
811874
1931
改变的是你的生产力。
13:33
Let me illustrate that.
271
813829
1252
让我解释一下。
13:35
Here is Frank Wilczek,
who got the Nobel Prize in Physics
272
815105
3269
这是获得诺贝尔物理学奖
的弗兰克·威尔切克,
13:38
for the very first paper he ever wrote
in his career as a graduate student.
273
818398
4101
他得奖要归功于研究生时
写的第一篇论文。
13:42
(Laughter)
274
822523
1007
(笑声)
13:43
More interesting is John Fenn,
275
823554
3218
更有趣的是约翰·芬,
13:46
who, at age 70, was forcefully retired
by Yale University.
276
826796
4598
他在70岁时,被耶鲁大学强制退休,
13:51
They shut his lab down,
277
831418
2056
他们关闭了他的实验室,
13:53
and at that moment, he moved
to Virginia Commonwealth University,
278
833498
3666
那时,他搬到了弗吉尼亚联邦大学,
13:57
opened another lab,
279
837188
1786
开了另一个实验室,
13:58
and it is there, at age 72,
that he published a paper
280
838998
3033
就在那里,在年纪72岁时,
他发表了一篇论文,
14:02
for which, 15 years later, he got
the Nobel Prize for Chemistry.
281
842055
3845
这篇论文在15年后
获得了诺贝尔化学奖。
14:06
And you think, OK,
well, science is special,
282
846940
3042
你会想,科学领域比较特殊,
14:10
but what about other areas
where we need to be creative?
283
850006
3463
但其他需要我们有创造力的领域呢?
14:13
So let me take another
typical example: entrepreneurship.
284
853493
4936
那么让我们再看看
另一个典型的例子:创业。
14:18
Silicon Valley,
285
858834
1579
硅谷。
14:20
the land of the youth, right?
286
860437
2066
年轻人的领地,对吧?
14:22
And indeed, when you look at it,
287
862527
1595
确实,当你看这个领域时,
你发现最大的奖励,
TechCrunch Awards或其他奖励,
14:24
you realize that the biggest awards,
the TechCrunch Awards and other awards,
288
864146
4642
14:28
are all going to people
289
868812
2173
全都给了平均年纪
14:31
whose average age
is late 20s, very early 30s.
290
871009
5015
在30岁左右的人。
14:36
You look at who the VCs give the money to,
some of the biggest VC firms --
291
876465
5602
再看看VC的钱都给了谁,
一些最大的VC企业——
14:42
all people in their early 30s.
292
882091
2241
几乎所有的人都在30岁出头。
14:44
Which, of course, we know;
293
884951
1265
当然,我们知道;
14:46
there is this ethos in Silicon Valley
that youth equals success.
294
886240
4453
硅谷有这样一种风气:
年轻等于成功。
14:51
Not when you look at the data,
295
891653
2183
不过,当你看数据的时候
就不会这样认为了。
14:53
because it's not only
about forming a company --
296
893860
2304
看看这些人当中有谁真正
14:56
forming a company is like productivity,
trying, trying, trying --
297
896188
3140
成立了一家成功的公司——
14:59
when you look at which
of these individuals actually put out
298
899352
3484
成立一个公司就像生产力,
尝试,尝试,再尝试。
15:02
a successful company, a successful exit.
299
902860
2782
因为这不仅关于成立一个公司。
15:05
And recently, some of our colleagues
looked at exactly that question.
300
905666
3720
最近,我们的几位同事
正好研究了这个问题。
15:09
And it turns out that yes,
those in the 20s and 30s
301
909410
3156
果不期然,这些年纪
在20多岁和30多岁的人
15:12
put out a huge number of companies,
form lots of companies,
302
912590
3348
创立了大量的公司,很多公司,
15:15
but most of them go bust.
303
915962
1531
但大部分都破产了。
15:18
And when you look at the successful exits,
what you see in this particular plot,
304
918089
4195
再看看那些成功的退出,
你在这个图中可以看到,
15:22
the older you are, the more likely that
you will actually hit the stock market
305
922308
3695
你年纪越大,就越有可能
轰动股票市场
15:26
or the sell the company successfully.
306
926027
2312
或者成功出售公司。
15:28
This is so strong, actually,
that if you are in the 50s,
307
928847
3113
数据很显著,事实上,
如果你50多岁,
15:31
you are twice as likely
to actually have a successful exit
308
931984
3588
你成功退出的机会是
15:35
than if you are in your 30s.
309
935596
1890
你30岁时的两倍。
15:38
(Applause)
310
938613
4325
(鼓掌)
15:43
So in the end, what is it
that we see, actually?
311
943645
3009
所以最后,我们看到了什么?
15:46
What we see is that creativity has no age.
312
946678
4083
我们看到的是创意并无年龄限制。
15:50
Productivity does, right?
313
950785
2202
生产力才是关键,对吧?
15:53
Which is telling me that
at the end of the day,
314
953424
4135
这就告诉我们,
15:57
if you keep trying --
315
957583
2000
如果你不断尝试——
15:59
(Laughter)
316
959607
2403
(笑声)
16:02
you could still succeed
and succeed over and over.
317
962034
3572
你仍然可以不断取得成功。
16:05
So my conclusion is very simple:
318
965630
2391
所以我的结论很简单:
16:08
I am off the stage, back in my lab.
319
968045
2093
演讲结束后,我得回到实验干活儿了。
16:10
Thank you.
320
970162
1171
谢谢。
16:11
(Applause)
321
971357
3309
(鼓掌)
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