Need a new idea? Start at the edge of what is known | Vittorio Loreto

翻译人员: Yu HAN 校对人员: Wei Wu

We have all probably wondered

我们可能都曾好奇过，

how great minds achieved what they achieved, right?

聪明人是怎样有所成就的，对吗？

And the more astonishing their achievements are,

并且他们的所作所为越令人惊叹，

the more we call them geniuses,

我们越习惯于叫他们天才，

perhaps aliens

或者是“外星人”，

来自另外的星球，

coming from a different planet,

definitely not someone like us.

反正绝对不像我们这样普通。

但是，真的是这样吗？

But is that true?

So let me start with an example.

让我来举个例子说明。

You all know the story of Newton's apple, right? OK.

我们都知道牛顿的苹果。

Is that true? Probably not.

那个故事真的发生过吗? 可能没有。

Still, it's difficult to think that no apple at all was there.

当然，我们很难想象传说中的 苹果其实并不存在。

I mean some stepping stone, some specific conditions

我的意思是，宇宙万有引力定律的发现

that made universal gravitation not impossible to conceive.

是基于特定环境或媒介的铺垫。

And definitely this was not impossible,

这种说法有一定道理，

at least for Newton.

至少对于牛顿来说是这样。

It was possible,

这是可能的，

and for some reason, it was also there,

因为一些原因，它就在那里，

available at some point, easy to pick as an apple.

像够到那个苹果一样容易，

Here is the apple.

触手可及。

And what about Einstein?

那么对于爱因斯坦呢？

Was relativity theory another big leap in the history of ideas

相对论是历史上又一大 新思想的飞跃。

no one else could even conceive?

除了爱因斯坦， 就没人可以提出了吗？

Or rather, was it again something adjacent and possible,

或者说，相对论当时 就在我们身边，

to Einstein of course,

对于爱因斯坦也是一样，

and he got there by small steps and his very peculiar scientific path?

他一步步走在自己的科学发现之路上， 最终发现了相对论。

Of course we cannot conceive this path,

当然我们无从知道 这是一条怎样的路，

but this doesn't mean that the path was not there.

但这不能否认那条路的存在。

So all of this seems very evocative,

这两个例子好像暗示了

but I would say hardly concrete

一些什么，却又不具象，

if we really want to grasp the origin of great ideas

尤其当我们真的希望 找到变得更优秀的源头，

and more generally the way in which the new enters our lives.

或通俗一点说，我们怎样 在生活中发现新鲜事物的时候。

As a physicist, as a scientist,

作为一个物理学家，科学家，

I have learned that posing the right questions

我知道，提出正确的问题，

is half of the solution.

问题就解决了一半。

But I think now we start having a great conceptual framework

而我想，我们现在已经拥有了 很棒的概念性的框架

to conceive and address the right questions.

来发现和解决问题。

So let me drive you to the edge of what is known,

那么现在，让我带大家 进入身边所熟悉的领域，

or at least, what I know,

或至少，是我熟悉的。

and let me show you that what is known

让我来说明一下，从熟悉的领域开始

could be a powerful and fascinating starting point

去感知新奇，创新，或者创造

to grasp the deep meaning of words like novelty, innovation,

这类词语更深层的含义，

creativity perhaps.

是一个多么好的起点。

So we are discussing the "new,"

我们在讨论“新”，

and of course, the science behind it.

同时还有它背后的科学。

The new can enter our lives in many different ways,

“新”可以由不同的方式 进入我们的生活，

can be very personal,

可以是很私人的，

like I meet a new person,

比如，我认识了一个新朋友，

I read a new book, or I listen to a new song.

读了一本新书或者听了一首新歌；

Or it could be global,

也可以是普遍化的，

I mean, something we call innovation.

比如，我们所说的创新，

It could be a new theory, a new technology,

可以是新理论，新技术，

but it could also be a new book if you're the writer,

同样也可以是一本新书， 前提是你是个作家，

or it could be a new song if you're the composer.

也可以是一首新歌， 如果你是个作曲家。

In all of these global cases, the new is for everyone,

这所有的例子里的“新”， 是每个人都有机会接触发现的。

but experiencing the new can be also frightening,

但体验“新”却也常常令人担忧，

so the new can also frighten us.

因为我们面对“新”，会有畏惧感。

But still, experiencing the new means exploring a very peculiar space,

同时，体验“新”意味着 我们在探索一段奇特的领域，

the space of what could be,

它具有任意性，

the space of the possible, the space of possibilities.

还有可能性。

It's a very weird space, so I'll try to get you through this space.

这是个很神奇的领域， 不过我会尝试带大家领略一下。

So it could be a physical space.

它可以是某个物理空间。

So in this case, for instance,

比如，

novelty could be climbing Machu Picchu for the first time,

我在2016年第一次爬上

as I did in 2016.

马丘比丘（古代印加城遗址， 在今秘鲁中南部)。

It could be a conceptual space,

也可以是理论上的空间，

so acquiring new information, making sense of it, in a word, learning.

如获取新的信息， 简而言之，就是学习。

It could be a biological space.

它还可以是生物层次的。

I mean, think about the never-ending fight of viruses and bacteria

想想我们的免疫系统 与病毒及细菌之间

永不停歇的对抗。

with our immune system.

And now comes the bad news.

但是先别忙着乐观，

We are very, very bad at grasping this space.

我们非常不擅于察觉到“新”的存在。

Think of it. Let's make an experiment.

想一想是不是这样， 我们来做个实验。

Try to think about all the possible things you could do in the next, say, 24 hours.

尝试思考在未来的24小时内， 你可以做的所有可能的事情。

Here the key word is "all."

记住，关键词是“所有”。

Of course you can conceive a few options, like having a drink, writing a letter,

下意识地，你会有几个选择， 比如喝一杯饮料，写封信，

also sleeping during this boring talk,

或者在我无聊的陈述中打个小盹，

if you can.

如果你们想的话。

But not all of them.

但这不是所有我们要做的事情。

So think about an alien invasion, now, here, in Milan,

想一想外星人入侵， 对，就是现在，在米兰，

or me -- I stopped thinking for 15 minutes.

或者是我，在接下来的 15分钟内停下来不去思考。

So it's very difficult to conceive this space,

所以，要察觉到 所有可能发生的事情并不容易。

but actually we have an excuse.

但这可以理解。

So it's not so easy to conceive this space

不容易实现的原因是

because we are trying to conceive the occurrence of something brand new,

我们都尝试着 去发现一些绝对的“新”，

so something that never occurred before,

一些以前从未发生的事情，

so we don't have clues.

所以我们找不到任何线索。

A typical solution could be

那么有什么解决办法吗？

looking at the future with the eyes of the past,

用目睹了过去的眼睛看未来，

so relying on all the time series of past events

就是凭借着在过去发生的事，

and hoping that this is enough to predict the future.

这些经历能支持我们预测未来。

But we know this is not working.

但实际上，这种方法的效果差强人意。

For instance, this was the first attempt for weather forecasts, and it failed.

就跟首次播报天气失败了一样。

And it failed because of the great complexity

因为事情多发生在表面，

of the underlying phenomenon.

而内部的复杂性却被忽略了。

So now we know that predictions had to be based on modeling,

所以，我们会通过建模来帮助预测，

which means creating a synthetic model of the system,

就是建立一个系统的综合模型，

simulating this model and then projecting the system

通过模型模拟，预测系统的

未来发展。

into the future through this model.

And now we can do this in a lot of cases

在很多情况下，基于大量数据，

with the help of a lot of data.

我们都可以建模。

Looking at the future with the eye of the past

但用过去的眼睛（数据） 预测未来（系统），

could be misleading also for machines.

也可能会出错， 对计算机来说也是一样。

Think about it.

设想一个画面，

Now picture yourself for a second in the middle of the Australian Outback.

你在澳大利亚内陆地区，

You stand there under the sun.

站在太阳底下，

So you see something weird happening.

看到了一些奇怪的事情。

The car suddenly stops

远远地，一辆车突然停住了，

very, very far from a kangaroo crossing the street.

在它前面很远处 有一只袋鼠在过马路。

You look closer

你仔细一看，

and you realize that the car has no driver.

发现车里竟没有司机。

It is not restarting, even after the kangaroo is not there anymore.

袋鼠过完马路后， 汽车也没有重新启动。

So for some reasons,

因为一些原因，

the algorithms driving the car cannot make sense

这辆无人驾驶汽车内置的算法 并不能理解这种现象，

of this strange beast jumping here and there on the street.

一只奇怪的庞然大物 在街上蹦来蹦去。

So it just stops.

于是它就停下了。

Now, I should tell you, this is a true story.

这是个真实的故事。

It happened a few months ago to Volvo's self-driving cars

几个月前，沃尔沃的 无人驾驶汽车就这样

停在了澳洲内陆中部地区。

in the middle of the Australian Outback.

(Laughter)

（笑声）

It is a general problem,

这个问题很普遍，

and I guess this will affect more and more in the near future

我想在不久的将来， 人工智能和机器学习

artificial intelligence and machine learning.

会在方方面面产生影响。

It's also a very old problem, I would say 17th century,

这个问题存在很久了， 17世纪就出现了。

but I guess now we have new tools and new clues to start solving it.

但我相信，现在的我们拥有 更多的新工具和方法去解决它。

So let me take a step back,

让我们暂时回到过去，

five years back.

五年前，

Italy. Rome. Winter.

意大利，罗马，冬天。

So the winter of 2012 was very special in Rome.

2012的冬天， 对罗马来说是很特别的，

Rome witnessed one of the greatest snowfalls of its history.

因为一场史无前例， 美不胜收的飘雪。

That winter was special also for me and my colleagues,

这个冬天对我和我的同事们 来说也有着特殊的意义，

because we had an insight about the possible mathematical scheme --

因为我们理解了一种 近乎合理的数学模型——

again, possible, possible mathematical scheme,

强调一下，只是可能，

to conceive the occurrence of the new.

用来帮助发现“新”。

I remember that day because it was snowing,

我记得那天在下雪，

so due to the snowfall, we were blocked, stuck in my department,

也正是因为这场雪， 我们被困在了办公室，

and we couldn't go home,

无法回家，

so we got another coffee, we relaxed

所以我们决定喝杯咖啡，放松一下，

and we kept discussing.

同时继续讨论我们的研究，

But at some point -- maybe not that date, precisely --

忽然之间——准确地说， 可能并不在那段小憩的时间——

at some point we made the connection

在某个时间点，我们在

between the problem of the new

发现“新”，与斯图亚特 · 考夫曼

and a beautiful concept proposed years before

曾经提出的一个美妙的

by Stuart Kauffman,

理论之间建立起了一种联系，

the adjacent possible.

即临界的可能性。

So the adjacent possible consists of all those things.

临界的可能性可以包含很多东西，

It could be ideas, it could be molecules, it could be technological products

比如新点子，新分子， 或者新科技产品。

that are one step away

我们距离这些实际存在的“新”，

from what actually exists,

只有一步之遥。

and you can achieve them through incremental modifications

我们可以通过改变身边存在的事物，

and recombinations of the existing material.

或对其加以重组来发现“新”。

So for instance, if I speak about the space of my friends,

举个例子，比如我身边有一群朋友，

my adjacent possible would be the set of all friends of my friends

那么身边可能的“新”， 可以是一群我朋友的朋友，

not already my friends.

他们目前还不是我的朋友。

I hope that's clear.

希望我说的够清楚。

But now if I meet a new person,

如果我现在认识一个新朋友，

say Briar,

比如布莱尔，

all her friends would immediately enter my adjacent possible,

那么她的朋友们就会 立即成为我的“新”朋友的备选人，

pushing its boundaries further.

这样我的人脉就会越来越多。

So if you really want to look from the mathematical point of view --

如果你们想用数学角度 来看待这件事——

I'm sure you want --

我确信你们有这个想法——

you can actually look at this picture.

我们可以来看一眼这张图。

So suppose now this is your universe.

这就是你的世界。

I know I'm asking a lot.

我知道我要求有点多。

I mean, this is your universe. Now you are the red spot.

麻烦大家把自己置身于这张图，这个 红点，就是我们现在所处的位置。

And the green spot is the adjacent possible for you,

绿点便是我们身边可能的“新”，

so something you've never touched before.

即我们从未踏入的领域。

So you do your normal life.

我们过着正常的生活，

You move. You move in the space.

在自己的世界中一步一步走，

You have a drink. You meet friends. You read a book.

喝杯水，见个朋友，读本书，

At some point, you end up on the green spot,

在某个时间点， 我们就走到了这个绿点，

so you meet Briar for the first time.

比如，我们在这里 第一次见到了布莱尔，

And what happens?

然后呢？

So what happens is there is a new part,

在这个特殊时刻，

我们会涉足一个崭新的领域，

a brand new part of the space,

becoming possible for you in this very moment,

我们从未投身的领域，

even without any possibility for you to foresee this

即使我们从未预想能走到

before touching that point.

这片未知的领域。

And behind this there will be a huge set of points

在踏入这片新区域后， 会有更多新领域，

that could become possible at some later stages.

在未来的某个时段可能被我们开启。

So you see the space of the possible is very peculiar,

所以我们看到了， 身边可能的未知领域是很神奇的，

because it's not predefined.

因为它的不可预知。

It's not something we can predefine.

我们没有办法提前得知，

It's something that gets continuously shaped and reshaped

这片区域是随着我们的行动和选择

by our actions and our choices.

被随时塑造的。

So we were so fascinated by these connections we made --

当时发现这一点联系时， 我们非常高兴——

scientists are like this.

科学家就是这样。

And based on this,

基于这一点，

we conceived our mathematical formulation for the adjacent possible,

我们发现了可以计算 临界可能性的数学公式，

20 years after the original Kauffman proposals.

在考夫曼理论提出的20年后。

In our theory -- this is a key point --

在我们的理论中，有一个关键点。

I mean, it's crucially based on a complex interplay

这个公式依赖于“新”区域的拓展

between the way in which this space of possibilities expands

及其重建之间复杂的相互影响，

and gets restructured,

以及我们自身探索

and the way in which we explore it.

“新”的方式。

After the epiphany of 2012,

在2012年的顿悟后，

we got back to work, real work,

我们回到工作中，进行实地考察，

because we had to work out this theory,

因为要将理论应用于实践。

and we came up with a certain number of predictions

我们提出了几个需要用实际生活

来检验的预测。

to be tested in real life.

Of course, we need a testable framework

当然，我们需要一个测试体系，

to study innovation.

来研究这个新方法。

So let me drive you across a few predictions we made.

让我简单介绍一下 我们所做的预测。

The first one concerns the pace of innovation,

第一个是创新的步调，

so the rate at which you observe novelties in very different systems.

即不同的体系中 发现“新”的速度。

So our theory predicts that the rate of innovation

我们的理论预测出这种速度

should follow a universal curve,

应该遵循通用曲线，

like this one.

比如这张图。

This is the rate of innovation versus time in very different conditions.

这是不同条件下新方法的 速率与时间的比值。

And somehow, we predict that the rate of innovation

通常，我们预测发现“新”的速率

should decrease steadily over time.

随着时间变长稳定降低，

So somehow, innovation is predicted to become more difficult

由于某些限制，随着我们行动的增加

as your progress over time.

发现“新”会变得更加困难。

It's neat. It's interesting. It's beautiful. We were happy.

这个系统很巧妙， 有趣且迷人，我们都很高兴。

But the question is, is that true?

但问题是，这是真的吗？

Of course we should check with reality.

当然我们会根据现实情况校准。

So we went back to reality

所以我们回到现实中来，

and we collected a lot of data, terabytes of data,

收集了很多数据，多达万亿字节。

tracking innovation in Wikipedia, Twitter,

从维基百科，到推特记录，

the way in which we write free software,

记录我们写新程序的方式，

even the way we listen to music.

甚至听音乐的方式。

I cannot tell you, we were so amazed and pleased and thrilled

我绝对不会跟你们说， 我们是多么激动，雀跃地发现，

to discover that the same predictions we made in the theory

在许多不同实际的体系中，

were actually satisfied in real systems,

我们的预测与真实情况

many different real systems.

几乎没有差别。

We were so excited.

我们太激动了。

Of course, apparently, we were on the right track,

很明显，我们走在一条正确的路上，

but of course, we couldn't stop,

当然，我们不愿意就此停下，

so we didn't stop.

也没有停下。

So we kept going on,

我们一直努力着，

and at some point we made another discovery

直到某个时候， 我们发现了另外的新理论，

that we dubbed "correlated novelties."

我们把它叫做“关联性创新”。

It's very simple.

很简单，

So I guess we all experience this.

我想我们都经历过。

So you listen to "Suzanne" by Leonard Cohen,

当我们听到莱昂纳德 · 科恩的 《苏珊》（歌曲）时，

and this experience triggers your passion for Cohen

这会激起你对科恩的热情，

so that you start frantically listening to his whole production.

然后你就会迫不及待地 去听他所有的作品，

And then you realize that Fabrizio De André here

然后你会看到一个名字， 法布里奇奥 · 德 · 安德雷，

recorded an Italian version of "Suzanne,"

翻唱了苏珊的意大利语版本，

and so on and so forth.

等等类似的例子。

So somehow for some reason,

不知怎么的，

the very notion of adjacent possible is already encoding the common belief

这个临界可能性的概念就会 根植于我们的信念中，

that one thing leads to another

即在很多不同的体系中，

in many different systems.

“新”的发现具有连续性。

But the reason why we were thrilled

那么我们为什么那么高兴呢，

is because actually we could give, for the first time,

因为第一次，我们可以把这种直觉

a scientific substance to this intuition

科学地实体化，

and start making predictions

并且开始对

about the way in which we experience the new.

体验“新”的方式进行预测。

So novelties are correlated.

创新是互相联系的，

They are not occurring randomly.

并不会随意地发生。

And this is good news,

这是一个好消息，

because it implies that impossible missions

这意味着，有些看起来 不可能的任务

might not be so impossible after all,

其实是可行的，

if we are guided by our intuition,

只要我们跟着直觉走，

somehow leading us to trigger a positive chain reaction.

它会带领我们走上一条 积极正面的连锁反应链。

But there is a third consequence of the existence of the adjacent possible

但是，关于临界可能性， 还存在第三种结果，

that we named "waves of novelties."

我们叫它创新的浪潮。

So just to make this simple, so in music,

简单来说，在音乐中，

without waves of novelties,

如果没有创新的浪潮，

we would still be listening all the time to Mozart or Beethoven,

我们可能还在继续听着 莫扎特或贝多芬。

which is great,

好像听起来还行，

but we don't do this all the time.

但是我们不能一直这样下去。

We also listen to the Pet Shop Boys or Justin Bieber -- well, some of us do.

我们同样会听宠物店男孩（乐队） 或贾斯汀 · 比伯——起码部分人会听。

(Laughter)

（笑声）

So we could see very clearly all of these patterns

所以我们可以从收集和 分析的庞大的数据中

in the huge amounts of data we collected and analyzed.

很清楚地看到这些例子。

For instance, we discovered that popular hits in music

比如，我们发现流行撞上音乐，

are continuously born, you know that,

产生的是什么，你们知道的。

and then they disappear, still leaving room for evergreens.

然后这些会消失，依然留有空间 给“常青树”（指经典音乐）。

So somehow waves of novelties ebb and flow

创新经历着潮起潮落，

while the tides always hold the classics.

而经典却永不消逝。

There is this coexistence between evergreens and new hits.

经典音乐和新流行可以共存。

Not only our theory predicts these waves of novelties.

不仅仅是我们的理论预测到了 创新浪潮的存在，

This would be trivial.

这不重要。

But it also explains why they are there,

重要的是，为什它们在那里，

and they are there for a specific reason,

基于某种特殊的原因，

因为我们是人类， 会在充满可能性空间中

because we as humans display different strategies

in the space of the possible.

展现不同的策略。

So some of us tend to retrace already known paths.

我们中的有些人倾向 去走已经走过的路，

So we say they exploit.

我们称之为开拓。

Some of us always launch into new adventures.

有的人愿意去做新的探险，

We say they explore.

这是探索。

And what we discovered is all the systems we investigated

我们发现的自己探究的东西，

are right at the edge between these two strategies,

就在开拓和探索的边缘，

something like 80 percent exploiting, 20 percent exploring,

就像80%是开发，20%是探索。

something like blade runners of innovation.

像是叶片式螺旋的创新。

So it seems that the wise balance, you could also say a conservative balance,

看上去，保持在过去和未来之间， 开发与探索之间的

between past and future, between exploitation and exploration,

智慧的平衡， 或称为保守的平衡，

is already in place and perhaps needed in our system.

已经就位，并且被 我们的自身所需要。

But again the good news is now we have scientific tools

好消息是，现在我们有科学工具

to investigate this equilibrium,

来研究这种均衡，

perhaps pushing it further in the near future.

或许在不久的将来 可以推广这种平衡。

So as you can imagine,

你们能想象到，

I was really fascinated by all this.

我是多么的深陷其中。

Our mathematical scheme is already providing cues and hints

我们的数学模型已经 提供了线索和暗示，

to investigate the space of possibilities

去寻找可能行的空间，

and the way in which all of us create it and explore it.

以及我们所有人创造并探索的方式。

But there is more.

不仅如此，

This, I guess, is a starting point of something that has the potential

这是一段关于“新”的

to become a wonderful journey for a scientific investigation of the new,

奇妙科学探索之路的起点，

but also I would say a personal investigation of the new.

同样也是个人自我发现的起点。

And I guess this can have a lot of consequences

我猜这个过程会卓有成效，

and a huge impact in key activities

并对主要活动产生巨大影响，

like learning, education, research, business.

比如学习，教育，研究，商务。

So for instance, if you think about artificial intelligence,

比如，想一下人工智能，

I am sure -- I mean, artificial intelligence,

我确信——在不久的将来，

we need to rely in the near future

我们会越来越依附

more and more on the structure of the adjacent possible,

发现临界可能性的这样一种结构，

to restructure it, to change it,

人工智能会去帮助重建这个结构，

but also to cope with the unknowns of the future.

去改变，去应对未知。

In parallel, we have a lot of tools,

同时，我们也有很多工具，

new tools now, to investigate how creativity works

崭新的现代工具， 去探究创新力是怎样产生，

and what triggers innovation.

是什么使创新应运而生。

And the aim of all this is to raise a generation of people

这所有一切的目的 便是去扶持一代人，

able to come up with new ideas to face the challenges in front of us.

一代能有新想法， 有能力面对挑战的人

We all know.

我们都知道。

I think it's a long way to go,

还有很长的路要走，

but the questions, and the tools,

但现在已有的问题，工具，

are now there, adjacent and possible.

就在身边，甚至唾手可得。

Thank you.

谢谢大家！

(Applause)

（掌声）