WEBVTT

00:00:00.699 --> 00:00:02.757
Today actually is
a very special day for me,

00:00:02.757 --> 00:00:04.917
because it is my birthday.

NOTE Paragraph

00:00:04.917 --> 00:00:08.944
(Applause)

NOTE Paragraph

00:00:09.202 --> 00:00:12.596
And so thanks for all of you
for joining the party.

NOTE Paragraph

00:00:12.596 --> 00:00:13.787
(Laughter)

NOTE Paragraph

00:00:13.787 --> 00:00:18.431
But every time you throw a party,
there's someone there to spoil it. Right?

NOTE Paragraph

00:00:18.431 --> 00:00:19.601
(Laughter)

NOTE Paragraph

00:00:19.601 --> 00:00:21.076
And I'm a physicist,

00:00:21.076 --> 00:00:25.509
and this time I brought
another physicist along to do so.

00:00:25.509 --> 00:00:27.473
His name is Albert Einstein, also Albert,

00:00:27.473 --> 00:00:30.751
and he's the one who said that the person

00:00:30.751 --> 00:00:35.943
who has not made his main contributions
to science by the age of 30

00:00:35.943 --> 00:00:38.332
will never do so.

NOTE Paragraph

00:00:38.332 --> 00:00:40.644
Now you don't need to check Wikipedia

00:00:40.644 --> 00:00:42.695
that I'm being 30.

00:00:42.695 --> 00:00:44.135
(Laughter)

00:00:44.135 --> 00:00:47.262
So effectively what
he is telling me, and us,

00:00:47.262 --> 00:00:50.333
is that when it comes to my science,

00:00:50.333 --> 00:00:52.446
I'm a dead wood.

00:00:52.446 --> 00:00:58.324
Well, luckily, I had my share
of luck within my career.

00:00:58.324 --> 00:01:02.604
Around age 28, I became
very interested in networks,

00:01:02.969 --> 00:01:06.284
and a few years later we managed
to kind of publish a few key papers

00:01:06.284 --> 00:01:10.048
that reported the discovery
of scale-free networks

00:01:10.048 --> 00:01:12.551
and really gave birth to a new discipline
that we call network science today.

00:01:12.551 --> 00:01:18.464
And if you really care about it,
you can get a PhD now in network science

00:01:18.464 --> 00:01:20.799
in Budapest, in Boston,

00:01:20.799 --> 00:01:23.320
and you can study it all over the world.

NOTE Paragraph

00:01:23.546 --> 00:01:25.017
A few years later,

00:01:25.017 --> 00:01:28.149
when I moved to Harvard
first as a sabbatical,

00:01:28.149 --> 00:01:30.964
I became interested
in another type of networks,

00:01:30.964 --> 00:01:34.713
and that time the networks
within ourselves,

00:01:34.713 --> 00:01:38.632
how the genes and the proteins
and the metabolites link to each other,

00:01:38.632 --> 00:01:41.072
and how they connect to disease.

00:01:41.072 --> 00:01:46.291
And that also, that interest led
to a major explosion within medicine,

00:01:46.291 --> 00:01:50.153
including the Network Medicine
Division at Harvard

00:01:50.153 --> 00:01:53.577
that has more than 300 researchers
who are using this perspective

00:01:53.577 --> 00:01:56.777
to treat patients and develop new cures.

NOTE Paragraph

00:01:56.777 --> 00:02:01.926
And a few years ago, I thought that I
would take this idea of networks

00:02:01.926 --> 00:02:04.996
and expertise we had in networks
in a different area,

00:02:04.996 --> 00:02:07.841
that is to understand success.

00:02:07.841 --> 00:02:09.584
And why did we do that?

00:02:09.584 --> 00:02:12.956
Well, we thought that to some degree,

00:02:12.956 --> 00:02:14.904
our success is determined
by the networks we are part of,

00:02:14.904 --> 00:02:19.463
that our networks can push us forward,
they can pull us back,

00:02:19.463 --> 00:02:23.154
and I was curious if we could use
the knowledge in big data and expertise

00:02:23.154 --> 00:02:28.578
that we developed on networks to really
quantify how these things happen.

NOTE Paragraph

00:02:28.774 --> 00:02:30.220
This is a result from that.

00:02:30.220 --> 00:02:32.914
What you see here is a network
of galleries in museums

00:02:32.914 --> 00:02:34.570
that connect to each other,

00:02:34.570 --> 00:02:38.758
and through this map
that we mapped out last year,

00:02:38.758 --> 00:02:41.760
we are able to predict very accurately

00:02:41.760 --> 00:02:44.631
the success of an artist

00:02:44.631 --> 00:02:48.819
if you give me the first five exhibits
that he or she had in her career.

NOTE Paragraph

00:02:48.819 --> 00:02:51.261
Well, as we thought about success,

00:02:51.261 --> 00:02:55.482
we realized that success
is not only about networks.

00:02:55.482 --> 00:02:57.979
There are so many
other dimensions to that.

00:02:57.979 --> 00:03:01.245
And, you know, one of the things
we need for success obviously

00:03:01.245 --> 00:03:02.520
is performance.

00:03:02.520 --> 00:03:06.588
So let's define what's the difference
between performance and success.

00:03:06.588 --> 00:03:08.725
Well, performance is what you do,

00:03:08.725 --> 00:03:11.612
how fast you run,
what kind of paintings you paint,

00:03:11.612 --> 00:03:13.897
what kind of papers you publish.

00:03:13.897 --> 00:03:16.328
However, in our working definition,

00:03:16.328 --> 00:03:21.326
success is about what does the community
notices from what you did,

00:03:21.326 --> 00:03:22.641
from your performance,

00:03:22.641 --> 00:03:26.691
how does it acknowledge it,
and how does it reward you for it?

00:03:26.691 --> 00:03:27.715
In other terms,

00:03:27.715 --> 00:03:32.346
your performance is about you,
but your success is about all of us.

00:03:33.421 --> 00:03:37.422
And this was a very
important shift for us,

00:03:37.422 --> 00:03:41.248
because in the moment we defined success
as being a collective measure

00:03:41.248 --> 00:03:43.192
that the community provides to us,

00:03:43.192 --> 00:03:44.997
it became measurable,

00:03:44.997 --> 00:03:49.295
because if it's in the community,
there are multiple data points about that.

NOTE Paragraph

00:03:49.295 --> 00:03:52.020
So now we believe,
and we go to school, we exercise,

00:03:52.020 --> 00:03:56.968
we practice because we believe
that performance leads to success.

00:03:58.062 --> 00:04:00.123
But the way we actually
started to explore,

00:04:00.123 --> 00:04:03.792
we realized that performance and success
are very, very different animals

00:04:03.792 --> 00:04:06.690
when it comes to
the mathematics of the problem.

00:04:06.879 --> 00:04:08.599
And let me illustrate that.

NOTE Paragraph

00:04:08.599 --> 00:04:12.432
So what you see here is
the fastest man on Earth, Usain Bolt.

00:04:12.432 --> 00:04:17.657
And of course, he wins most of
the competitions that he enters.

00:04:17.657 --> 00:04:21.517
And we know he's the fastest on Earth
because we have a chronometer

00:04:21.517 --> 00:04:23.064
to measure his speed.

00:04:23.064 --> 00:04:27.190
Well, what is interesting about him
is that when he wins,

00:04:27.190 --> 00:04:32.226
he doesn't do so by really significantly
outrunning his competition.

00:04:32.667 --> 00:04:37.785
He's running at most a percent faster
than the one who loses the race.

00:04:37.785 --> 00:04:41.156
And not only does he run only
one percent faster than the second one,

00:04:41.156 --> 00:04:44.419
but he doesn't run
10 times faster than I do,

00:04:44.419 --> 00:04:46.542
and I'm not a good runner,
trust me on that.

NOTE Paragraph

00:04:46.542 --> 00:04:47.907
(Laughter)

NOTE Paragraph

00:04:47.907 --> 00:04:51.767
And every time we are able
to measure performance,

00:04:51.767 --> 00:04:53.405
we notice something very interesting.

00:04:53.405 --> 00:04:56.101
That is, performance is bounded.

00:04:56.101 --> 00:04:59.834
What it means is that there are
no huge variations in human performance.

00:04:59.834 --> 00:05:03.449
It varies only in a narrow range,

00:05:03.449 --> 00:05:06.577
and we do need the chronometer
to measure the differences.

00:05:06.577 --> 00:05:09.557
This is not to say that we cannot
see the good from the best ones,

00:05:09.557 --> 00:05:12.264
but the best ones
are very hard to distinguish,

00:05:12.264 --> 00:05:15.400
and the problem with that
is that most of us work in areas

00:05:15.400 --> 00:05:19.105
where we do not have a chronometer
to gauge our performance.

NOTE Paragraph

00:05:19.401 --> 00:05:21.446
Alright, performance is bounded,

00:05:21.446 --> 00:05:24.429
there are no huge differences between us
when it comes to our performance.

00:05:24.429 --> 00:05:25.991
How about success?

00:05:25.991 --> 00:05:29.082
Well, let's switch to
a different topic like books, right?

00:05:29.082 --> 00:05:32.518
One measure of success for writers
is how many people read your work?

00:05:32.518 --> 00:05:39.391
And so when my previous book
came out in 2009,

00:05:39.391 --> 00:05:42.263
I was in Europe talking with my editor,
and I was interested,

00:05:42.263 --> 00:05:44.269
who is the competition?

00:05:44.269 --> 00:05:47.136
And I had some fabulous one.

00:05:47.136 --> 00:05:49.144
That week (Laughter)

00:05:49.144 --> 00:05:52.354
Dan Brown came out with "The Lost Symbol"

00:05:52.354 --> 00:05:55.011
and "The Last Song" also came out,

00:05:55.011 --> 00:05:57.271
Nicholas Sparks.

00:05:57.271 --> 00:06:01.189
And when you just look at the list,

00:06:01.189 --> 00:06:02.651
you realize, you know, performance-wise

00:06:02.651 --> 00:06:05.550
there is hardly any difference
between these books or mine.

00:06:05.550 --> 00:06:06.510
Right?

00:06:06.510 --> 00:06:13.348
So maybe if Nicholas Sparks' team
works a little harder,

00:06:13.348 --> 00:06:14.186
he could easily be number one,

00:06:14.186 --> 00:06:16.732
because it's almost by accident
who ended up at the top.

00:06:16.936 --> 00:06:19.539
So I said, let's look at the numbers.
I am a data person, right?

00:06:19.539 --> 00:06:24.315
So let's see what were
the sales for Nicholas Sparks.

00:06:24.315 --> 00:06:26.157
And it turns out that
that opening weekend,

00:06:26.157 --> 00:06:28.908
Nicholas Sparks sold more than
a hundred thousand copies,

00:06:28.908 --> 00:06:30.468
which is an amazing number.

00:06:30.468 --> 00:06:33.587
You can actually get to the top
of the New York Times Bestseller List

00:06:33.587 --> 00:06:36.501
by selling 10,000 copies a week,

00:06:36.501 --> 00:06:40.423
so he tenfold overcame
what he needed to be number one.

00:06:40.423 --> 00:06:42.523
Yet he wasn't number one. Why?

00:06:42.523 --> 00:06:46.721
Because there was Dan Brown,
who sold 1.2 million copies that week.

NOTE Paragraph

00:06:46.721 --> 00:06:48.839
(Laughter)

NOTE Paragraph

00:06:48.839 --> 00:06:53.435
And the reason I like this number
is because it shows that really,

00:06:53.435 --> 00:06:57.241
when it comes to success, it's unbounded,

00:06:57.241 --> 00:07:02.887
that the best doesn't only get
slightly more than the second best,

00:07:02.887 --> 00:07:05.718
but gets orders of magnitude more,

00:07:05.718 --> 00:07:08.605
because success is a collective measure.

00:07:08.605 --> 00:07:12.931
We give it to them, rather than
we earn it through our performance.

NOTE Paragraph

00:07:12.931 --> 00:07:17.267
So one of things we realized
is that performance,

00:07:17.267 --> 00:07:21.104
what we do is bounded but success,
which is collective, is unbounded,

00:07:21.104 --> 00:07:24.534
which makes you wonder,

00:07:24.534 --> 00:07:25.589
how do you get these
huge differences in success

00:07:25.589 --> 00:07:28.829
when you have so tiny
differences in performance?

00:07:28.829 --> 00:07:32.527
And recently I published a book
that I devoted to that very question,

00:07:32.527 --> 00:07:35.337
and they didn't give enough time
to go over all of that,

00:07:35.337 --> 00:07:38.259
so I'm going to go back
to the question of alright,

00:07:38.259 --> 00:07:40.844
you have success, when should that appear?

NOTE Paragraph

00:07:40.844 --> 00:07:43.259
So let's go back to the party spoiler,

00:07:43.259 --> 00:07:45.028
and ask ourselves,

00:07:45.028 --> 00:07:48.805
why did Einstein make
this ridiculous statement

00:07:48.805 --> 00:07:52.078
that only before 30
you could actually be creative?

00:07:52.078 --> 00:07:56.732
Well, because he looked around himself
and he saw all these fabulous physicists

00:07:56.732 --> 00:07:59.361
that created quantum mechanics
and modern physics,

00:07:59.361 --> 00:08:03.825
and they were all in their 20s
and early 30s when they did so.

00:08:03.825 --> 00:08:07.140
And it's not only him.

00:08:07.140 --> 00:08:08.818
It's not only observational bias,

00:08:08.818 --> 00:08:11.007
because there's actually
a whole field of genius research

00:08:11.007 --> 00:08:15.778
that has documented the fact
that if we look at the people

00:08:15.778 --> 00:08:16.975
we admire from the past

00:08:16.975 --> 00:08:19.938
and then we look at what age
did they make their biggest contribution,

00:08:19.938 --> 00:08:21.802
whether that's music,
whether that's science,

00:08:21.802 --> 00:08:23.461
whether that's engineering,

00:08:23.461 --> 00:08:27.462
most of them tend to do so
in their 20s, 30s, early 40s at most.

00:08:27.462 --> 00:08:33.521
But there's a problem
with this genius research.

00:08:33.521 --> 00:08:36.799
Well, first of all, it created
the impression to us

00:08:36.799 --> 00:08:40.315
that creativity equals youth,

00:08:40.315 --> 00:08:43.413
which is painful, right?

NOTE Paragraph

00:08:43.413 --> 00:08:44.484
(Laughter)

NOTE Paragraph

00:08:44.484 --> 00:08:47.863
And it also has an observational bias,

00:08:47.863 --> 00:08:50.827
because it only looks at geniuses

00:08:50.827 --> 00:08:52.811
and doesn't look at ordinary scientists,

00:08:52.811 --> 00:08:55.787
and doesn't look at all of us and asking,

00:08:55.787 --> 00:08:58.478
is it really true that creativity
vanishes as we age?

00:08:58.478 --> 00:09:01.776
So that's exactly what we tried to do,
and this is important for that

00:09:01.776 --> 00:09:04.434
to actually have references.

NOTE Paragraph

00:09:04.434 --> 00:09:07.119
So let's look at an ordinary
scientist like myself,

00:09:07.119 --> 00:09:08.753
and let's look at my career.

00:09:08.753 --> 00:09:13.177
So what you see here is all the papers
that I published from my first paper,

00:09:13.177 --> 00:09:16.821
it's in 1989 that I was still
in Romania when I did so,

00:09:16.821 --> 00:09:19.208
til kind of this year.

00:09:19.208 --> 00:09:21.932
And vertically you see
the impact of the paper,

00:09:21.932 --> 00:09:24.401
that is, how many citations,

00:09:24.401 --> 00:09:27.612
how many other papers
have been written that cited that work?

00:09:27.612 --> 00:09:31.644
And when you look at that,
you see that my career

00:09:31.644 --> 00:09:32.810
has three roughly different stages.

00:09:32.810 --> 00:09:35.556
I had the first 10 years
where I work a lot

00:09:35.556 --> 00:09:36.508
and I don't achieve much.

00:09:36.508 --> 00:09:37.754
No one seems to care
about what I do, right?

00:09:37.754 --> 00:09:40.926
There's hardly any impact.

00:09:40.926 --> 00:09:44.012
That time, I was doing material science,

00:09:44.012 --> 00:09:47.457
and then I kind of discovered
for myself networks,

00:09:47.457 --> 00:09:49.338
and then started publishing in network,

00:09:49.338 --> 00:09:52.736
and that led one high-impact paper
to the other one.

00:09:52.736 --> 00:09:55.159
And it really felt good.
That was that stage of my career.

NOTE Paragraph

00:09:55.159 --> 00:09:57.426
(Laughter)

NOTE Paragraph

00:09:57.426 --> 00:10:00.766
So the question is,
what happens right now?

00:10:00.766 --> 00:10:08.088
And we don't know, because there
hasn't been enough time passed yet

00:10:08.088 --> 00:10:09.182
to actually figure out how much impact
those papers will get.

00:10:09.182 --> 00:10:09.924
It takes time to acquire.

00:10:09.924 --> 00:10:10.924
Well, when you look at the data,

00:10:10.924 --> 00:10:12.779
it seems to be that Einstein,
the genius research, is right,

00:10:12.779 --> 00:10:14.716
and I'm at that stage of my career.

NOTE Paragraph

00:10:14.716 --> 00:10:16.551
(Laughter)

NOTE Paragraph

00:10:17.010 --> 00:10:24.535
So we said, OK, let's figure out
how does this really happen

00:10:24.535 --> 00:10:28.729
first in science, right?

00:10:28.729 --> 00:10:30.528
And in order not to have
the selection bias,

00:10:30.528 --> 00:10:31.368
to look only at geniuses,

00:10:31.368 --> 00:10:33.410
we ended up reconstructing the career
of every single scientist

00:10:33.410 --> 00:10:36.057
from 1900 til today

00:10:36.057 --> 00:10:38.395
and finding for all scientists
what was their personal best,

00:10:38.395 --> 00:10:42.322
whether they got the Nobel Prize
or they never did,

00:10:42.322 --> 00:10:45.720
or no one knows what they did,
even their personal best.

00:10:46.071 --> 00:10:48.100
And that's what you see
actually in this slide.

00:10:48.100 --> 00:10:50.172
Each line is a career,

00:10:50.172 --> 00:10:52.804
and when you have a light blue dot
on the top of that career,

00:10:52.804 --> 00:10:55.425
it says that was their personal best.

00:10:55.425 --> 00:10:56.437
And the question is,

00:10:56.437 --> 00:10:59.451
when did they actually make
their biggest discovery?

00:10:59.451 --> 00:11:02.118
And to quantify that, we look at
what's the probability

00:11:02.118 --> 00:11:05.018
that you make your biggest discovery
let's say, one, two, three,

00:11:05.018 --> 00:11:06.821
or 10 years into your career?

00:11:06.821 --> 00:11:09.945
We're not looking at real age.

00:11:09.945 --> 00:11:12.099
We're looking at
what we call academic age.

00:11:12.099 --> 00:11:14.632
Your academic age starts
when you publish your first papers.

00:11:14.632 --> 00:11:15.935
I know some of you are still babies.

NOTE Paragraph

00:11:15.935 --> 00:11:16.797
(Laughter)

NOTE Paragraph

00:11:16.797 --> 00:11:21.704
So let's look at the probability
that you publish your highest impact paper

00:11:21.704 --> 00:11:24.898
and what you see is indeed
the genius research is right.

00:11:24.898 --> 00:11:28.188
Most scientists tend to publish
their highest impact paper

00:11:28.188 --> 00:11:30.666
in the first 10, 15 years in their career,

00:11:30.666 --> 00:11:33.973
and it tanks after that.

00:11:33.973 --> 00:11:38.986
It tanks so fast that I'm about,
I'm exactly 30 years into my career,

00:11:38.986 --> 00:11:42.629
and the chance that I will publish a paper
that would have higher impact

00:11:42.629 --> 00:11:44.553
than anything that I did before

00:11:44.553 --> 00:11:46.083
is less than one percent.

00:11:46.083 --> 00:11:49.939
I am in that stage of my career,
according to this data.

00:11:49.939 --> 00:11:52.054
But there's a problem with that.

00:11:52.054 --> 00:11:55.614
We're not doing controls properly.

00:11:55.614 --> 00:11:57.163
So the control would be,

00:11:57.163 --> 00:12:01.549
how would a scientist look like
who makes random contribution to science?

00:12:01.549 --> 00:12:04.966
Or what is the productivity
of the scientist?

00:12:04.966 --> 00:12:06.591
When do they write papers?

00:12:06.591 --> 00:12:09.097
So we measured the productivity,

00:12:09.097 --> 00:12:11.717
and amazingly, the productivity,

00:12:11.717 --> 00:12:15.186
your likelihood of writing a paper
in year one, 10, or 20 in your career

00:12:15.186 --> 00:12:18.876
is indistinguishable from the likelihood
of having the impact

00:12:18.876 --> 00:12:20.582
in that part of your career.

NOTE Paragraph

00:12:21.178 --> 00:12:23.429
And to make a long story short,

00:12:23.429 --> 00:12:27.445
after lots of statistical tests,
there's only one explanation for that,

00:12:27.445 --> 00:12:30.331
that really the way we scientists work

00:12:30.331 --> 00:12:34.110
is that every single paper we write,
every project we do,

00:12:34.110 --> 00:12:37.901
has exactly the same chance
of being our personal best.

00:12:37.901 --> 00:12:40.768
That is, discovery is like a lottery,

00:12:40.768 --> 00:12:42.689
and like a lottery ticket,

00:12:42.689 --> 00:12:47.040
and then the more lottery tickets we buy,
the higher is the chance,

00:12:47.040 --> 00:12:49.567
and it happens to be so
that most scientists

00:12:49.567 --> 00:12:53.848
buy most of their lottery tickets
in the first 10, 15 years of their career,

00:12:53.848 --> 00:12:57.762
and after that,
their productivity decreases.

00:12:57.762 --> 00:12:59.741
They're not buying
any more lottery tickets.

00:12:59.741 --> 00:13:03.323
So it looks as if
they would not be creative.

00:13:03.323 --> 00:13:05.877
In reality, they stopped trying.

00:13:05.877 --> 00:13:08.153
So when we actually put the data together,
the conclusion is very simple:

00:13:08.153 --> 00:13:09.805
success can come at any time.

00:13:09.805 --> 00:13:15.597
It could be your very first
or very last paper of your career.

00:13:15.597 --> 00:13:20.139
It's totally random
in the space of the projects.

00:13:20.139 --> 00:13:22.147
It is the productivity that changes.

NOTE Paragraph

00:13:22.147 --> 00:13:23.555
And let me illustrate that.

00:13:23.555 --> 00:13:25.021
Here is Frank Wilczek,

00:13:25.021 --> 00:13:28.423
who get the Nobel Prize in Physics
for the very first paper

00:13:28.423 --> 00:13:31.902
he ever wrote in his career
as a graduate student.

00:13:31.902 --> 00:13:35.052
More interesting is John Fenn,

00:13:35.052 --> 00:13:39.752
who at age 70 was forcefully retired
by Yale university.

00:13:39.752 --> 00:13:41.611
They shut his lab down,

00:13:41.611 --> 00:13:45.428
and at that moment, he moved
to Virginia Commonwealth University,

00:13:45.428 --> 00:13:47.321
opened another lab,

00:13:47.321 --> 00:13:49.943
and it is there at age 72
that he published a paper

00:13:49.943 --> 00:13:55.035
for which 15 years later he got
the Nobel Prize for Chemistry.

NOTE Paragraph

00:13:55.255 --> 00:13:58.276
And you think, OK,
well science is special, right?

00:13:58.276 --> 00:14:00.623
But what about other areas
where we need to be creative?

00:14:00.623 --> 00:14:06.757
So let me take another
typical example: entrepreneurship.

00:14:06.757 --> 00:14:08.415
Silicon Valley,

00:14:08.415 --> 00:14:11.349
the land of the youth, right?

00:14:11.349 --> 00:14:13.485
And indeed, when you look at it,
you realize that the biggest awards,

00:14:13.485 --> 00:14:17.016
the TechCrunch Awards and other awards,

00:14:17.016 --> 00:14:21.169
are all going to people,

00:14:21.169 --> 00:14:24.766
an average age for them
is late 20s, very early 30s.

00:14:24.766 --> 00:14:30.416
You look at who the VCs give the money to,
some of the biggest VC firms,

00:14:30.416 --> 00:14:33.087
all people in their early 30s.

00:14:33.087 --> 00:14:36.824
Which, of course, we know:

00:14:36.824 --> 00:14:39.013
there is this ethos in Silicon Valley
that youth equals success.

00:14:39.013 --> 00:14:42.201
Not when you look at the data,

00:14:42.201 --> 00:14:44.671
because it's not only
about forming a company.

00:14:44.671 --> 00:14:47.447
Forming a company is like productivity:
trying, trying, trying.

00:14:47.447 --> 00:14:50.134
When you look at which
of these individuals actually put out

00:14:50.134 --> 00:14:53.961
a successful company, a successful exit,

00:14:53.961 --> 00:14:57.752
and recently some of our colleagues
looked at exactly that question,

00:14:57.752 --> 00:15:00.788
and it turns out that yes,
those in the 20s and 30s

00:15:00.788 --> 00:15:02.992
put out a huge number of companies,
form lots of companies,

00:15:02.992 --> 00:15:04.428
but most of them go bust,

00:15:04.428 --> 00:15:09.157
and when you look at the successful exits,
what you see in this particular plot,

00:15:09.157 --> 00:15:14.879
the older you are, the more likely that
you will actually hit the stock market

00:15:14.879 --> 00:15:17.140
or the sell the company successfully.

00:15:17.140 --> 00:15:20.434
This is so strong, actually,
that if you are in the 50s,

00:15:20.434 --> 00:15:23.946
you are twice as likely
to actually have a successful exit

00:15:23.946 --> 00:15:26.574
than if you are in your 30s.

NOTE Paragraph

00:15:26.857 --> 00:15:30.481
(Applause)

NOTE Paragraph

00:15:31.921 --> 00:15:35.257
So at the end, what it is
that see, actually?

00:15:35.257 --> 00:15:39.067
What we see is that creativity has no age.

00:15:39.067 --> 00:15:41.693
Productivity does, right?

00:15:41.693 --> 00:15:45.176
Which is telling me that
at the end of the day,

00:15:45.176 --> 00:15:48.386
if you keep trying

00:15:48.386 --> 00:15:50.366
(Laughter)

00:15:50.366 --> 00:15:53.861
you could still succeed
and succeed over and over,

00:15:53.861 --> 00:15:55.908
so my conclusion is very simple.

00:15:55.908 --> 00:15:58.772
I am of this age, back in my lab.

NOTE Paragraph

00:15:58.772 --> 00:16:01.161
Thank you.

NOTE Paragraph

00:16:01.161 --> 00:16:02.898
(Applause)