无限的开端，第一部分

数学领域也是如此。

So too in mathematics.

多伊奇解释说，数学是一个试图揭示必然真理的领域。

Deutsch explains that mathematics is a field where what we're trying to uncover is necessary truth.

数学的研究对象是必然真理，就像粒子物理学的研究对象是基本粒子一样。

The subject matter of mathematics is necessary truth in the same way that the subject matter of particle physics are the fundamental particles.

但仅仅因为基本粒子物理学的研究对象是基本粒子，并不意味着你真正找到了基本粒子。

But because the subject matter of fundamental particle physics are the fundamental particles, that doesn't mean you actually find the fundamental particles.

这仅仅意味着你们已经发现了现有最大粒子加速器所能解析的最小粒子。

All it means is that you have found the smallest particles that your biggest particle accelerator is able to resolve.

但如果拥有更大的加速器，你们可能会发现这些粒子内部还有更小的粒子。

But if you had an even bigger particle accelerator, you might find particles within those particles.

顺便说一句，这就是粒子物理学的发展历程。

This has been the history of particle physics, by the way.

我们曾认为原子是最基本的单位。

We used to think that atoms were fundamental.

后来当然发现原子由原子核和电子组成。

Then, of course, we found that they contained nuclei and electrons.

在原子核中，我们又发现了质子和中子。

In the nuclei, we found out there were protons and neutrons.

而在质子和中子内部，我们发现它们由夸克构成。

Inside the protons and neutrons, we found out they were made up of quarks.

这就是我们目前的认识阶段。

And that's where we're at right now.

现阶段我们认为夸克和电子是基本粒子。

We're at the point where we say that the quarks are fundamental and the electrons are fundamental.

但这并不意味着粒子物理学就此终结。

But that doesn't mean that we're going to end particle physics right now.

我们需要更多理论来探索这些极小微粒内部可能存在的结构。

What we need are further theories about what might be inside of those really small particles.

类比数学领域，如果说必然真理是数学的研究对象，那么数学家们从事的正是对这些必然真理的认知探索。

Comparing that to mathematics, if necessary truth is the subject matter of mathematics, our knowledge of that necessary truth is what mathematicians are engaged in.

他们致力于探索必然真理的知识。

They're engaged in creating knowledge about necessary truth.

由于数学家的大脑是物理实体，而所有物理实体都会因热力学第二定律或普通人常犯的思维错误而产生认知偏差，数学家同样可能犯错，最终证明的结论也可能存在谬误。

And because a mathematician has a brain, which is a physical object, and all physical objects are subject to making errors of degradation via the second law of thermodynamics or simply just the usual mental mistakes and errors that any human being makes, a mathematician is just as fallible as anyone else, then what they end up proving could be an error.

如果我理解正确，即便是数学也可能出错，因为数学本质上是一种创造性活动。

So if I understand this point, even mathematics is capable of error because mathematics is a creative act.

我们永远无法做到尽善尽美。

We're never quite done.

可能在某个公理设定上就存在错误。

There could have been a mistake in your axiom somewhere.

归根结底，数学也是创造性活动，其内部可能存在错误。

Ultimately, even mathematics is a creative act and can have error within it.

所有知识都具有推测性。

All knowledge is conjectural.

它始终处于被猜想的状态。

It's always being guessed.

这是我们在特定时期的最佳认知。

It's our best understanding at any given time.

你说得对，公理可能存在错误。

You're right to say that the axioms might be incorrect.

我们如何判断某个公理是错误的？

How do we know that an axiom is incorrect?

传统观点认为，当错误清晰明显时就能判定。

Traditionally, the answer has been because it's clearly and obviously the case.

你如何证明x加零必须等于x？

How can you prove that x plus zero must equal x?

嗯，你只能接受这是事实。

Well, you just have to accept that it's true.

但如果我们以欧几里得的《几何原本》为例，比如在纸上画两个点。

But if we consider something like Euclid's elements, for example, draw two points on a piece of paper.

现在通过这两个点，可以画出一条唯一的直线。

Now through those two points, a unique straight line can be drawn.

几个世纪以来这都被认为是真理，任何听众都可以亲自尝试这个实验。

This was accepted as true for centuries when anyone listening might wanna try the experiment for themselves.

拿一张纸，拿一支笔，在纸上画两个点。

Take a piece of paper, take a pen, draw two dots on the piece of paper.

现在你能通过这两个点画出多少条唯一的直线？

Now how many unique straight lines can you draw through those two dots?

你应该很明显地看出只能画出一条这样的线。

It should be fairly obvious to you that only one such line can be drawn.

然而，我们现在知道这是错误的。

However, we now know that's false.

我只是想让你思考，当你盯着纸上唯一被画出的那条直线时，你会有确定无疑的感觉。

I just want you to reflect as you're staring at the piece of paper through which only one straight line is being drawn, you have the feeling of certainty.

你绝对确信自己没有错。

You are absolutely sure that you're not wrong.

对这种感觉，我们永远应该保持怀疑态度。

This feeling is something we should always be sceptical of.

因为当人们过于确信时，即便是在数学这样看似充满确定性的领域，他们也曾被证明是错误的。

Because when people have been absolutely certain, even in a domain as apparently full of certainty as mathematics, they've been shown to be wrong.

那么我们该如何证明它是错的呢？

So how can we show it wrong?

你可以这样做。

Here's what you do.

你可能会觉得我在作弊，但请回想一下，当我最初让你通过这两点画一条唯一直线时，你真的理解我的意思吗？

And you might think that I'm cheating, but then again, you have to reflect on, did you understand what I was saying when I first told you to draw a unique straight line through these two points?

我希望你这样做。

Here's what I want you to do.

把纸弯曲。

Bend the piece of paper.

用三维空间思考。

Think in three dimensions.

如果有篮球的话，把纸包裹在篮球上。

Wrap the piece of paper around a basketball if you have one.

现在考虑如何通过这两点画一条直线。

Now consider the ways in which you could draw a straight line through those two points.

你可以用笔穿透其中一个点，再从另一侧穿出另一个点。

You could punch a hole through one of those dots with your pen and push it out through the other side through the other hole.

这样你就得到了一条不同的直线。

And now you have a different straight line.

你既有用笔画出的直线，也有一条实际就是穿透这两个点的笔本身的直线。

You have the straight line that is drawn with your pen and you have a straight line that is literally your pen that has been pushed through these two dots.

所以你最初那种确信两点之间只能画一条直线的感觉是错误的。

So your initial feeling absolute certainty that only a unique line could be drawn through these two dots is false.

你可能觉得这不公平。

And you might be thinking that's unfair.

这是在作弊。

That's cheating.

你当时是在二维空间里思考。

You were thinking in two dimensions.

不。

No.

你当时是在二维空间里思考。

You were thinking in two dimensions.

我没有。

I wasn't.

我是在更高维度思考的。

I was thinking in more dimensions than that.

卡尔·波普尔有句名言：你永远无法用不被误解的方式说话。

Karl Popper has this wonderful saying, it is impossible to speak in such a way that you cannot be misunderstood.

这总是成立的。

This is always the case.

所以即使在力求精确的数学领域，人们仍可能犯错，对他们试图论证的前提产生误解。

So even in mathematics where we try and be as precise as possible, it's possible for people to make errors, to think false premises about what the argument is that they're trying to make.

顺便说一句，欧几里得几何的这个特例——因为传统几何总是在纸面的二维空间进行——被多位学者解决后发展出了曲面几何，最终促使爱因斯坦提出了广义相对论。

And by the way, this particular example of Euclidean geometry, because geometry was traditionally always done in two dimensions on a piece of paper, was resolved by various people and led to geometry in curved space, which led to Einstein coming up with general theory of relativity.

正是质疑这些我们认为绝不可能出错的最深层假设，才带来了真正的进步，带来了科学及其他领域根本性的变革。

So it is questioning these deepest assumptions that we have where we think there's no possible way we could be mistaken that leads to true progress, to genuine fundamental change in the sciences and everywhere else.

你说过，我们从民主时代的原子一路向下探索到原子核，再到质子和中子，最后到夸克。

You said that we went from atoms in the time of democratism down to nuclei and from there to protons and neutrons and then to quarks.

套用费曼的话说，这完全是粒子一路向下的过程。

It's particles all the way down, to paraphrase Feynman.

我们可以永远这样探索下去。

We can keep going forever.

但也不完全是永远。

But it's not quite forever.

对吧？

Right?

在某个时刻，会遇到普朗克长度。

At some point, run into the Planck length.

还有普朗克时间。

There's the Planck time.

还有普朗克长度。

There's the Planck length.

甚至还有普朗克质量，这实际上是个相当大的质量。

There's even the Planck mass, which is actually quite a large mass.

这些东西并不具有任何物理意义。

These things don't have any physical significance.

普朗克时间并非最短可能时间，普朗克长度也并非最短可能长度。

It's not like the Planck time is the shortest possible time, and it's not like the Planck length is the shortest possible length.

原因在于这些普朗克量是量子理论的一部分。

The reason for that is because these Planck things are part of quantum theory.

但长度并非由量子理论描述。

But length is not described by quantum theory.

它是由广义相对论描述的。

It's described by the general theory of relativity.

而在该理论中，空间是无限可分的。

And in that theory, space is infinitely divisible.

不存在最小的可能长度或时间。

There is no smallest possible length or time.

这揭示了离散与连续之间古老的张力，因为量子理论似乎暗示事物是离散的。

This illuminates an ancient tension between the discrete and the continuous because quantum theory seems to suggest that things are discrete.

例如，存在最小的金粒子——金原子。

For example, there's a smallest possible particle of gold, the gold atom.

存在最小的电粒子——电子。

There's a smallest possible particle of electricity, the electron.

存在最小的光粒子——光子。

There's a smallest possible particle of light, the photon.

在量子理论中，我们有这种离散性的概念，即存在构成万物的最小基本单元。

In quantum theory, we have this idea of discreteness, that there is a smallest possible thing from which everything else is built.

但在广义相对论中，理念恰恰相反。

But in general relativity, the idea is the opposite.

它认为事物可以连续变化。

It says things can continuously vary.

如果数学要求事物必须连续可变以便进行微分等运算，其核心思想在于空间和时间可以被无限分割。

And if the mathematics requires that things be continuously variable so they can be differentiated and so on, the idea there is that you can keep on dividing up space and you can keep on dividing up time.

因此物理学家们认识到，在我们物理学最基础的阐释层面存在着这样的矛盾。

So physicists understand that there is this contradiction at the deepest level of our most foundational explanations in physics.

这也是为何人们不断尝试统一量子理论和广义相对论的原因之一。

And it's one of the reasons why there are these attempts to try and unify quantum theory and general relativity.

因为现实的本质究竟是什么？

Because what is the fundamental nature of reality?

事物是可以无限分割的，还是必须在某个节点停止分割？

Is it that things can be infinitely divisible or is it that we must stop somewhere or other?

因为如果可无限分割，量子理论或许就得从属于广义相对论，但我们目前无从得知。

Because if it's infinitely divisible, then quantum theory might have to be subservient to general relativity, but we just don't know.

这下我解决芝诺悖论的方法行不通了——在到达终点前，你必须先完成一半路程。

There goes my solution for Zeno's paradox, which is before you can get all the way somewhere, you have to get halfway there.

而在完成一半路程前，又得先完成四分之一路程，如此你将永远无法抵达终点。

And before you can get halfway there, you have to get a quarter of the way there, and therefore you'll never get there.

突破这个悖论的一种方法是：即便是无限序列也可能具有有限总和。

One way to get past that is to say, even a series of infinite things can have a finite sum.

你只需运行这个无限序列并求和。

You know, just run the infinite series and sum it.

我们很早就学过这个级数是收敛的。

And we learned pretty early on that converges.

但我另一个想法是：你必须跨越最小距离（普朗克长度），因此终将到达目的地。

But another thought I had was that you have to cover a minimum distance, a Planck length, and therefore you will get there.

这是一个有限的步骤序列，但你说我们就是不知道。

It's a finite series of steps, but you're saying we just don't know.

是的。

Yes.

所以如果物理定律说我们可以在特定时间内移动一米，那我们就这么做。

So if the laws of physics say that we can cover one meter in a certain time period, then that's exactly what we'll do.

而我们目前对物理定律的理解恰恰说明了这一点。

And our current understanding of the laws of physics say precisely that.

因此芝诺悖论只需说明我们可以在特定时间内穿越这段空间就能解决。

So Zeno's paradox is resolved simply by saying that we can cover this space in this amount of time.

它并未说明空间是否无限可分。

It's silent on whether or not space is infinitely divisible.

当有人问你，空间是否无限可分？

When someone asks you, is space infinitely divisible?

那我会回答，是的，它是。

Then I would say, yes, it is.

他们可能会反问，你怎么知道？

And they might turn around and say, how do you know?

我会说，广义相对论。

And I would say, general relativity.

我怎么知道这是真的？

How do I know that's true?

其实，我并不确定它是否真实。

Well, I don't know that it's true.

然而，这是目前我们对时空的最佳解释。

However, it is the best explanation that we presently have of space time.

然后他们可能会讨论，如果空间是无限可分的，那么芝诺悖论就会再次出现。

And then they might get into a discussion about, well, if it's infinitely divisible, then you're presented with Zeno's paradox all over again.

而我会说，不是这样的。

And I would say, no.

你可以通过简单的实验来反驳这一点。

You refute that by simple experiment.

所以我们不知道如何穿越这些无限的点，如果这些点确实是无限的话。

So we don't know how it is that we can travel through all of these infinite points, if in fact there are infinite points.

芝诺悖论属于纯数学领域，但我们并不生活在纯数学的世界里。

Zeno's paradox is about the domain of pure mathematics, But we don't live in a world of pure mathematics.

我们生活在物理世界中。

We live in a world of physics.

如果物理学告诉我们可以在有限时间内穿越无限多个点，那么不管数学怎么说，我们都能做到。

And if the physics says that we can transverse an infinite number of points in a finite amount of time, then that's what we'll do regardless of what the mathematics says.

每个数学理论都存在于大脑或计算机的物理基质中。

Every mathematical theory is held inside a physical substrate of a brain or a computer.

你始终受到物理定律的约束，这些纯粹的抽象领域可能与现实毫无对应关系。

You're always bound by the laws of physics, and these pure abstract domains may have no mapping to reality.

数学中绝大多数定理都是我们无法证明的。

The overwhelming majority of theorems in mathematics are theorems that we cannot possibly prove.

这就是哥德尔定理。

This is Godel's theorem.

这也源于图灵关于什么是可计算与不可计算的证明。

And it also comes out of Turing's proof of what is and is not computable.

不可计算的事物数量远超可计算的事物。

These things that are not computable vastly outnumber the things that are computable.

而什么是可计算的，完全取决于我们在这个物理宇宙中能制造出什么样的计算机。

And what is computable depends entirely upon what computers we can make in this physical universe.

我们能制造的计算机必须遵守我们的物理定律。

The computers that we can make must obey our laws of physics.

如果物理定律不同，我们就能证明不同类型的数学。

If the laws of physics were different, then we'd be able to prove different sorts of mathematics.

这是数学家误解的另一部分。

And this is another part of the mathematician's misconception.

他们认为可以超越物理定律。

They think they can get outside of the laws of physics.

然而，他们的大脑只是一台物理计算机。

However, their brain is just a physical computer.

他们的大脑必须遵守物理定律。

Their brain must obey the laws of physics.

如果他们存在于物理定律不同的宇宙中，他们就能证明不同的定理。

If they existed in a universe with different laws of physics, then they could prove different theorems.

但我们存在于当前的宇宙中，因此受到诸多限制，尤其是光速的有限性。

But we exist in the universe that we're in, and so we're bound by a whole bunch of things, not least of which is the finite speed of light.

因此，在抽象空间中可能存在某些事物，如果我们能摆脱此处物理定律的限制，就能对其有更全面的理解。

So there could be certain things out there in abstract space which we would be able to come to a more full understanding of if we could get outside of the restrictions of the laws of physics here.

幸运的是，目前我们无法证明的那些定理本质上都不有趣。

Happily, none of those theorems that we cannot prove at the moment are inherently interesting.

有些事物可能天生就乏味，比如所有这些我们无法证明其真伪的定理。

Some things can be inherently boring, namely all of these theorems which we cannot possibly prove as true or false.

这些定理对我们的物理宇宙没有任何影响。

Those theorems can't have any bearing in our physical universe.

它们与我们的物理宇宙毫无关联。

They have nothing to do with our physical universe.

这就是为什么我们说它们本质上无趣。

And this is why we say they're inherently uninteresting.

而且世界上存在大量本质上无趣的事物。

And there's a lot of inherently uninteresting things.

概率是否真实存在于物理宇宙中，还是只是我们无知的产物？

Does probability actually exist in the physical universe, or is it a function of our ignorance?

当我掷骰子时，我不知道它会如何落地，因此我引入了概率概念。

If I'm rolling a dice, I don't know which way it's gonna land, so therefore I put in a probability.

但这是否意味着宇宙中确实存在不可知的概率性事物？

But does that mean that there's an actual probabilistic unknowable thing in the universe?

宇宙是在某处抛硬币吗，还是说它始终是确定性的？

Is the universe flipping a coin somewhere, or is it always deterministic?

所有的概率实际上都是主观的。

All probability is actually subjective.

不确定性和随机性都是主观的。

Uncertainty and randomness are subjective.

如果你不知道结果会如何，于是掷骰子，那是因为你个人不知道。

If you don't know what the outcome's going to be, so you roll a dice, that's because you individually do not know.

并非因为宇宙深处存在不确定性。

It's not because there is uncertainty there deeply in the universe.

我们对量子理论的理解是，所有物理上可能的事情都会发生。

What we know about quantum theory is that all physically possible things occur.

这引出了多重宇宙的概念。

This leads to the concept of the multiverse.

与其驳斥所有理解量子理论的失败尝试，我们不如认真对待量子理论方程所表达的内容。

And rather than refute all of the failed ways of trying to understand quantum theory, we're just gonna take seriously what the equations of quantum theory say.

根据实验，我们不得不认为量子理论表明：每一个可能发生的事情都会发生。

What we are compelled to think about quantum theory given the experiments, is that every single possible thing that can happen does happen.

这意味着宇宙中不存在固有的不确定性，因为所有可能发生的事情实际上都会发生。

This means that there is no inherent uncertainty in the universe because everything that can happen actually will happen.

并不是有些事情会发生而有些事情不会发生。

It's not like some things will happen and won't happen.

所有事情都会发生。

Everything happens.

现在你身处一个单一的宇宙中。

Now you occupy a single universe.

在那个宇宙里，当你掷骰子时，结果是两点。

And in that universe, when you roll the dice, it comes up a two.

但我们知道在物理现实的其他地方，会出现一点、三点、四点、五点或六点。

But we know somewhere else in physical reality, it comes up a one, somewhere else three, a four, a five, and a six.

如果我掷两个骰子，那么它们总和为二的宇宙数量会少于总和为七的宇宙数量，因为七可以是三加四、五加二等等组合。

If I'm rolling two dice, then the universe in which they sum up to two is less than the number of universes in which we roll a seven because that can be a three or four or five and a two and so on.

因此，宇宙的数量仍然与我们计算的概率相对应。

So the number of universes still does correspond to what we calculate as the probability.

是的。

Yes.

这导致了 Deutsch 所说的在量子理论中理解概率的决策理论方法。

This leads to what Deutsch calls the decision theoretic way of understanding probability within quantum theory.

决策理论意味着你假设宇宙以这种方式分裂的比例关系。

Decision theoretic means you assume this proportionality between the universe as this way of splitting things up.

所以如果你掷两个不同的骰子，宇宙就会按比例分裂成不同的测量结果。

So if you're rolling two different dice, then the universe's proportion themselves into measures.

而测量的本质是一种讨论无限性的方式。

And what a measure is is it's a way of talking about infinities.

YouTube上有个视频，Deutsch在其中解释了著名的量子双缝实验，该实验涉及粒子波二象性。

There is a video on YouTube which has Deutsch explained the famous quantum double slit experiment, which is about particle wave duality.

光是粒子还是波？

Is light a particle or a wave?

你让它通过狭缝，取决于是否存在观察者干扰。

You pass it through a slit depending on whether there's observer interference or not.

最终它会呈现波状图案，或以单个光子的形式出现。

It ends up in a wave pattern, ends up as individual photons.

这个著名的实验长期困扰着人们，并促使他们修正世界观，正是这个实验让爱因斯坦说出'上帝不会掷骰子'这句话。

And this is the famous experiment which has baffled people for a long time and caused them to revise their worldview, the one that led Einstein to say, god does not play dice with the universe.

正确。

Correct.

在量子理论的奠基者们试图为这些实验现象寻找合理解释时，爱因斯坦是个现实主义者。

Einstein was a realist at the time when the founders of quantum theory were trying to develop a good explanation of what precisely was going on with these experiments in quantum theory.

爱因斯坦否定了所有那些理论，因为它们都不够现实。

Einstein rejected all of them on the basis that they weren't realistic.

他这么做是对的，因为那些理论都毫无道理可言。

And he was right to do so because none of them made any sense.

直到今天，其他替代理论也都同样说不通。

And to this day, none of the other alternatives make any sense.

当时爱因斯坦并不知道多重宇宙的存在。

Now Einstein didn't know about the multiverse.

我们不得不等到1950年代，休·埃弗雷特才提出了一个简单而现实的理解量子理论的方法。

We had to wait until Hugh Everett in the 1950s was able to devise a simple, realistic way of understanding quantum theory.

如果回到双缝实验这个概念，人们常说粒子具有二象性。

But if I go back to this idea of the double slit experiment, it is often claimed that particles have a duality to them.

有时它们表现为粒子，有时又表现为波。

Sometimes they're particles and sometimes they're waves.

以电子为例，在某些实验中它会表现出粒子特性。

The electron, for example, given certain experiments will behave like a particle.

而在其他实验中，它又表现得像波。

And in other experiments, it behaves like a wave.

听到这个解释的人会觉得：好吧，这似乎能说明问题。

People who hear this think, well, okay, that kind of explains what's going on.

例如，在光电效应中，你将光照射到电子上，这实际上意味着你向一个电子发射了一个光子——光的粒子，从而可以将电子从原子中击出。

For example, in the photoelectric effect, you shine a light at electrons, which literally means you're firing a photon, a particle of light at an electron, and you can knock the electron out of the atom.

这被认为是确凿证据，表明以光子形式存在的光和以电子形式存在的电都是粒子，因为它们会相互反弹。

This is supposed to be proof positive that light in the form of photons and electricity in the form of electrons are both particles because they're bouncing off one another.

而这正是粒子的行为特征。

And this is what particles do.

波不会这样。

Waves don't do that.

你在海滩观察水波时，会看到它们相互穿过。

You watch water waves at the beach, you'll see they pass through each other.

它们不会相互反弹。

They don't bounce off one another.

波会从粒子反弹，但波与波之间不会相互反弹。

Waves will bounce off particles, but they won't bounce off each other.

在杨氏双缝实验之前，我们实际上依赖牛顿关于光的理论。

Prior to Young's twin slit experiment, we actually relied upon Newton's ideas of light.

牛顿的观点是光具有微粒性，如他所说，这意味着光由粒子组成。

And Newton's idea was that light was corpuscular, as he said, which means made of particles.

后来杨氏出现，他将光照射到一张纸上切割出的两条狭缝。

And then Young came along and he shone a light through two slits cut into a piece of paper.

当你将这道光投射到另一张纸上时，会发现不仅仅是两束光。

And what you find when you project that light onto another sheet of paper is not just two beams of light.

你会看到所谓的干涉图案，即光与自身发生了干涉。

You find what's called an interference pattern where the light has interfered with itself.

正如当波穿过小孔或自然地质缝隙时，它们会相互干涉。

In the same way that when waves pass through small apertures, the natural geological gaps, they will interfere with one another.

它们在某些地方形成波峰，在另一些地方形成波谷。

They produce crests in some places and troughs in others.

它们可以相互抵消。

They can cancel each other out.

这曾被早期物理学家视为光实际上是波的证据。

This was supposed to be proof to some of the early physicists that light in fact was a wave.

现在我们进入量子理论领域，发现像电子这样曾被确信是粒子的物质，在进行相同实验时也会相互干涉。

And now we get to quantum theory and we find that things we thought were certainly particles like electrons, when we do the same experiment with them, they interfere with one another.

因此看起来我们既有像波一样行为的粒子，也有像粒子一样行为的波。

So it appears as though we've got particles acting like waves and waves acting like particles.

解决这个矛盾不是要接受荒谬的说法。

The resolution to this is not to admit nonsense.

在本科阶段的量子理论课程中常这样解释：你必须接受光子作为粒子诞生，以波的形式存在，又以粒子形式消亡——这完全是胡说。

So this is what often is explained in quantum theory lectures in undergraduate level, is that you have to accept that something like a photon is born as a particle, it lives as a wave, and then it dies again as a particle, which is nonsense.

之所以说是胡说，是因为光子并不知道自己是活着还是死了。

And the reason that it's nonsense is because the photon doesn't know that it's alive and it's dead.

它不知道自己参与的是什么实验。

It doesn't know what experiment it's participating in.

因此我们必须更深入地理解如何解释这个双缝实验中发生的现象。

So we have to come to a deeper understanding of how to explain what is going on in this double experiment.

因为如果我们向双缝装置发射光子或电子，并在任一狭缝处放置探测器，我们就会检测到粒子。

Because if we fire either a photon or an electron at that double slit apparatus and we put a detector at either of those slits, then we will detect a particle.

因此我们能检测到发射了一个粒子。

So we can detect that we fired a particle.

我们可以检测到有粒子穿过那些狭缝。

We can detect that a particle is going through those slits.

我们也能在投影屏上检测到粒子。

And we can detect a particle at the projection screen as well.

当你在实验室用电子做这个实验时，你能看到电子撞击屏幕产生的光点，但不会得到你预期的简单图案。

When you do this experiment in the laboratory using electrons, you can see the dots where the electrons strike hitting the screen, but you don't get a simple pattern that you would expect.

如果你向一堵有两个洞的墙发射炮弹，你会预期所有炮弹都会穿过那两个洞，落在墙后的两个位置之一。

If you're firing cannonballs at a wall where there are two holes in the wall through which the cannonballs can go, you would expect that all the cannonballs are going to go through those two holes and land in one of two positions behind the wall.

但在量子层面的粒子中，情况并非如此。

But with particles at the quantum level, that's not what happens.

这里发生了某些现象。

Something is going on.

唯一能解释的是：当我们发射一个光子时，除了我们宇宙中可见的光子外，还有其他平行宇宙中我们看不见的光子也在穿过装置。

And the only explanation is that when we fire a photon, there's the photon that we can see in our universe, but there's also photons in other universes passing through the apparatus that we cannot see.

这些光子能够与我们可检测到的光子产生相互作用。

And these photons are able to interact with the photon that we are able to detect.

这就是干涉概念的由来。

This is where the concept of interference comes in.

干涉是物理学中的古老概念。

Interference is an old concept in physics.

这要追溯到波动现象。

It goes back to waves.

波确实会相互干涉。

Waves certainly interfere.

但我们需要理解粒子之间相互干涉的方式。

But we need to understand the way in which particles can interfere one with another.

这些粒子既包括我们能观测到的，也包括通过这些实验我们只能假设存在的。

Particles that we can observe and particles that we can only assume to observe given these experiments.

这就是为什么我们不得不承认这些其他粒子的存在。

And this is why we are forced into acknowledging the existence of these other particles.

不仅是这些粒子，还包括它们存在的其他宇宙。

And not only these other particles, but other universes in which these particles exist.

此时人们可能会反对说：你怎么敢在科学中引入那些看不见、无法观测的东西？

Now, people might object at this point and go, how dare you invoke in science things that cannot be seen, things that cannot be observed?

这显然完全违背了科学方法。

This is completely antagonistic towards the scientific method surely.

我要对持这种想法的人说：你所知道的几乎所有有趣的科学知识，都是关于未被观测到的事物。

And I will say to anyone who's thinking that right now, almost everything of interest that you know about science is about the unobserved.

让我们以恐龙为例。

Let's consider dinosaurs.

恐龙是未被观测到的。

Dinosaurs are unobserved.

你会说：哦，等等。

You say, Oh, hold on.

我去过博物馆。

I've been to the museum.

我见过恐龙。

I've seen a dinosaur.

不，你看到的是化石。

No, you have seen a fossil.

而化石甚至不是骨头。

And a fossil isn't even a bone.

它是骨头的石化形态。

It's an ossified bone.

它已经变质成了岩石。

It has been metamorphized into rock.

所以没人真正见过恐龙。

So no one has ever seen a dinosaur.

我们看到的只是类似恐龙的物体，并将其解读为巨大的类鸟爬行动物——当我们组装它们的骨骼时，就编造出关于这种生物数千万或数亿年前在地球上行走的故事。

We have seen things that look like dinosaurs and interpreted them to be huge reptilian bird like creatures that when we assemble their skeletons, we make up a story about what this thing was that walked the earth tens or hundreds of millions of years ago.

同理，没人见过太阳核心，也永远不会观测到太阳核心。

In the same way, no one has ever seen the core of the sun and no one will ever observe the core of the sun.

但我们了解恒星核聚变。

But we know about stellar fusion.

我们知道氢原子核在那里碰撞形成氦，并在此过程中产生热量。

We know that hydrogen nuclei being crashed together there to form helium and in the process producing heat.

我们没看见过大爆炸。

We don't see the big bang.

我们看不见大陆的移动。

We don't see the movement of continents.

科学中几乎所有有趣的事物，我们都无法直接观测到。

Almost everything of interest in science, we do not observe.

甚至我们声称见过的许多事物，实际上只是通过仪器检测到的。

Even many of the things that we say we have seen, we've actually just seen instruments detect those things.

所以我们通过仪器观察效应，进而推测存在其他宇宙，那里的光子与我们可见的光子相互作用。

So we're watching the effects through instruments and then theorizing that there are other universes out there where the photons are interacting with the photons that we can see.

许多科学家和哲学家都讨论过多重宇宙的概念，但这是对多重宇宙最严谨、最清醒的理解。

There are many scientists, philosophers who've talked about this concept of a multiverse, but this is a very strict, very sober understanding of what a multiverse is.

这个多重宇宙中的所有宇宙都遵循相同的物理定律。

All of these universes in this multiverse obey the same laws of physics.

我们讨论的不是存在不同物理定律的宇宙。

We're not talking about universes where there are other laws of physics.

这并不比历史上人们曾认为宇宙仅由地球构成、其他天体都围绕地球运转更令人惊讶——行星、恒星、太阳、月亮都围绕我们运转，存在于这颗渺小的星球上。

This should be no more surprising than historically when it used to be thought that the universe consisted of our planet and around our planet orbited everything else, other planets, stars, the sun, the moon orbited around us, existed on this tiny planet.

随后我们对现实的认知稍微扩展了一些。

Then our vision of reality got expanded a little bit.

我们意识到，事实上我们并非宇宙的中心。

We realized, in fact, we were not at the center of the universe.

太阳才是中心，而其他行星在某些情况下——比如木星、土星等气态巨行星——实际上比我们的地球还要大。

The sun was at the center and these other planets were in fact bigger in some cases, in the case of Jupiter and Saturn and the gas giants, bigger than what our planet Earth is.

太阳也比我们大得多，因此我们的宇宙变得更为广阔。

And the sun was a lot bigger than what we are, so our universe became larger.

后来我们认识到，我们只是数百亿恒星组成的巨大星系中众多恒星系统之一。

Then we realized that we were just one star system among many in a huge galaxy of hundreds of billions of stars.

后来我们意识到，这个星系只是数千亿星系中的一个。

Then later we realized that this galaxy is one of hundreds of billions of galaxies.

因此，思想史和科学史就是我们不断拓宽对物理现实规模认知的历史。

So the history of ideas and the history of science is a history of us broadening our vision of exactly how large physical reality is.

这是这一总体趋势中的又一步。

And this is another step in that general trend.

我们应该期待它继续发展。

And we should expect it to continue.

人们接受这种理解事物的方式应该不会太难。

It shouldn't be that hard for people to accept that this is the way to understand things.

我们是否已经了解量子理论以及这个多元宇宙运作的全部？

Do we know everything about quantum theory and how this multiverse works?

不。

No.

我们尚未将这个多元宇宙与广义相对论统一起来。

We haven't united this multiverse with general relativity.

我们需要多元宇宙的时空或几何结构，但目前尚未掌握。

We needed space time or a geometry of the multiverse, which we don't have yet.

那么回到好的解释，这些解释从何而来？

So getting back to good explanations, where do these explanations come from?

目前存在对归纳法的痴迷。

There's currently an obsession with induction.

归纳法指的是通过过去预测未来的理念。

Induction being the idea that you can predict the future from the past.

你可以说，看到一，然后二，然后三，然后四，然后五，所以接下来必定是六、七、八、九。

You can say, saw one, then two, then three, then four, then five, so therefore next must be six, seven, eight, nine.

有一种观点认为，新知识就是这样产生的。

There's a belief that this is how new knowledge is created.

科学理论就是这样形成的，我们就是这样对宇宙做出合理解释的。

This is how scientific theories are formed, and this is how we can make good explanations about the universe.

归纳法有什么问题？新知识从何而来？

What's wrong with induction, and where does new knowledge come from?

你之前确实提到过黑天鹅，我想回到这个话题。

You did mention the black swan earlier, and I'd like to go back to that.

黑天鹅这个例子多年来被许多人用来阐释一个观点：反复观察相同现象不应让你确信未来会持续如此。

The black swan is an example that various people have used over the years in order to illustrate this idea that repeatedly observing the same phenomena over and again should not make you confident that it will continue in the future.

在欧洲，我们见到的是白天鹅。

In Europe, we have white swans.

因此任何研究鸟类的生物学家观察了一只又一只白天鹅后，很可能会据此得出结论说所有天鹅都是白色的。

So any biologist who's interested in birds be observing white swan after white swan, and apparently concluding on that basis that therefore all swans are white.

然后有人去了西澳大利亚，在那里发现有些天鹅与欧洲的天鹅外形完全一致，但羽毛却是黑色的。

Then someone travels to Western Australia, and there you notice that there are swans that otherwise look identical to the ones in Europe, but they're black.

让我们思考另一个归纳法的例子。

Let's consider another example of induction.

从你出生起，就观察到太阳每天都会升起。

Ever since the beginning of your life, you have observed that the sun has risen.

这是否意味着从科学角度你应该得出结论：太阳明天会升起，并且之后每天都会升起？

Does this mean that scientifically you should conclude the sun will rise tomorrow and rise every day after that?

这不是科学的本质。

This is not what science is about.

科学并非仅仅编录过去发生的事件历史并假定它们未来会再次发生。

Science is not about cataloging a history of events that have occurred in the past and presuming they're going to occur again in the future.

科学是一种解释性框架。

Science is an explanatory framework.

它是一种纠错机制。

It's an error correcting mechanism.

它从来不是'太阳过去总是升起，所以未来也会升起'这样的形式。

It's not ever of the form the sun always rose in the past, therefore, it will rise in the future.

我们可以用各种方式想象明天太阳可能不会升起。

And there's all sorts of ways in which we can imagine the sun won't rise tomorrow.

你只需要去一趟南极洲。

All you need to do is to take a trip to Antarctica.

在那里，一年中有几个月太阳根本不会升起。

And there, for some months of the year, the sun doesn't rise at all.

如果你去国际空间站，你不会看到太阳每天升起和落下一次。

If you go to the International Space Station, you won't see the sun rise once per day and set once per day.

在你快速绕地球飞行的过程中，太阳会反复升起和落下。

It will rise and set repeatedly over the course of your very fast journey around the earth.

科学中还有另一个类似的例子。

There's another example from science like this.

在热源上放一烧杯水，然后将温度计插入水中，再打开热源。

On a heat source, put a beaker of water, then put a thermometer into that water and turn on your heat source.

然后随着时间推移记录水温的变化。

Then record as the time passes what the temperature of the water is.

你会注意到水温会逐渐升高。

You will notice that the temperature of the water will increase.

你在家可以用平底锅做这个实验。

You can do this with a saucepan at home.

只要热源相对稳定，温度的上升也会相对稳定。

So long as the heat source is relatively constant, the temperature rise will be relatively constant as well.

所以一分钟后，温度可能从20摄氏度上升到30摄氏度。

So after one minute, the temperature might go from 20 degrees Celsius to 30 degrees Celsius.

想象每分钟它都会再升高10摄氏度。

Imagine every minute it climbs by another 10 degrees Celsius.

但达到沸点时温度就会停滞不前。

But at some point it's gonna stall when it hits the boiling point.

正是如此。

Precisely.

如果你是个彻底的归纳主义者或贝叶斯推理者，并且对沸点及其相关现象一无所知，你可以把这些漂亮的线段连成完美的对角线并无限外推。

Now if you're a thoroughgoing inductivist or even a Bayesian reasoner, and you don't know anything about the boiling temperature and what phenomena happens at that temperature, you can join all of those lovely lines into a perfectly diagonal straight line and extrapolate off into infinity.

根据你的贝叶斯推理和归纳法，两小时后我们应该认为那锅水的温度将达到一千摄氏度。

After two hours, according to your Bayesian reasoning, according to your induction, we should assume that the temperature of that water will be a thousand degrees Celsius.

但这当然是完全错误的。

But of course, this is completely false.

实际发生的是，一旦水开始沸腾，温度就会保持在沸点不变。

What actually happens is once it starts boiling, it stays at its boiling temperature.

我们得到一个平台期。

We get a plateau.

这个温度平台期大约在100摄氏度，会一直持续到所有水分蒸发完毕。

And this plateau of temperature, about a 100 degrees Celsius, remains there until all the water boils away.

如果不先进行实验或通过某种解释性方法预先猜测会发生什么，我们根本不可能知道这一点。

Now there's no possible way of knowing this without first doing the experiment or having already guessed via some explanatory means what was going to happen.

没有任何记录这些数据点并外推至未来的方法能给出正确答案。

No method of recording all of these data points and extrapolating off into the future could ever have given you the correct answer.

正确答案只能来自创造性思维。

The correct answer can only come from creativity.

注意，科学并不在于预测趋势的起点和走向。

And notice that science is not about predicting where the trend starts and where the trend goes.

事实上，要解释水的状态变化，我们需要考虑粒子行为——随着温度升高，粒子动能增加意味着其速度开始加快。

In fact, if we wanna explain what's going on with the water, we refer to the particles and how as the temperature increases, the kinetic energy of the particles starts to increase, which means the velocity of the particle starts to increase.

最终，液态中的粒子会达到脱离液体的逃逸速度。

Eventually, those particles in the liquid state achieve escape velocity from the rest of the liquid.

这时就发生了沸腾现象，而逃逸速度所需能量在专业术语中称为潜热。

At this point, we have boiling, but that escape velocity, the technical term is latent heat, requires energy.

正因如此，像水这样的物质可能在受热时不表现出温度上升。

And for this reason, we can have heating of something like water without any temperature increase.

这就是科学的本质。

That's what science is.

关于粒子加速运动的完整复杂解释，包括潜热这个术语的引入，其核心不在于趋势预测，而在于现象解释。

That whole complicated story about how the particles are moving faster, this invocation of the term latent heat, it's not about trends and predictions, it's about explanation.

只有当我们获得解释后，才能真正做出预测。

Only once we have the explanation can we in fact make the prediction.

更进一步说，这不仅仅是科学。

Going even further, it's not just science.

当我们审视创新、技术和建设时，比如托马斯·爱迪生和尼古拉·特斯拉所做的一切，这些都是通过试错完成的——即创造性的猜测和不断尝试。

When we look at innovation and technology and building, for example, everything that Thomas Edison did and Nikola Tesla did, these were from trial and error, which is creative guesses and trying things out.

如果你观察进化如何通过变异和自然选择运作，它会尝试大量随机突变，并筛选掉那些无效的。

If you look at how evolution works through variation and then natural selection, where it tries a lot of random mutations and it filters out the ones that didn't work.

因此，这似乎是所有复杂系统随时间自我完善的一个通用模式。

So this seems to be a general model through which all complex systems improve themselves over time.

它们进行大胆猜测，然后剔除那些无效的部分。

They make bold guesses, and then they weed out the things that didn't work.

这种模式在所有知识创造过程中都呈现出美妙的对称性。

Things like a beautiful symmetry to it across all knowledge creation.

它本质上是一种创造性行为。

It's ultimately an act of creativity.

我们不知道它从何而来，这不仅仅是观察结果的机械外推。

We don't know where it comes from, and it's not just a mechanical extrapolation of observations.

这方面最著名的例子，我们提到过黑天鹅。

The most famous example on this, we mentioned black swans.

我们讨论过沸水现象。

We talked about boiling water.

但有趣又简单的例子是火鸡。

But the fun and easy one is the turkey.

一只火鸡可能每天都被喂养得很好，长得肥肥胖胖，它以为自己属于并生活在一个仁慈的家庭里，农夫每天都会来喂它，直到感恩节到来，那时它将迎来一个非常残酷的觉醒，或者我应该说，一个结局。

You could have a turkey that's being fed very well every single day and fattened up, and it thinks that it belongs and lives in a benevolent household where the farmer comes and feeds it every day until Thanksgiving arrives, and then it's in for a very rude awakening or I should say an ending.

这展示了归纳法的局限性。

That shows you the limits of induction.

正是如此。

Precisely.

理论必须被猜测出来，我们所有伟大的科学家都曾发出过类似的声音。

The theories have to be guessed, and all of our great scientists have always made noises similar to this.

只有哲学家或某些数学家认为科学就是这样发生的，认为这是一种从过去观察中寻求趋势并外推到未来的归纳方式。

It's only the philosophers or certain mathematicians who think that this is the way that science happens, that it's this inductive trend seeking way of extrapolating from past observations into the future.

爱因斯坦说过，他并不一定比大多数人聪明。

Einstein said that he wasn't necessarily brighter than most other people.

而是他对特定问题充满热情，拥有好奇心和想象力。

It's that he was passionately interested in particular problems and he had a curiosity and an imagination.

想象力对他来说至关重要。

Imagination was key for him.

他需要想象出可能解释这些事物的理论。

He needed to imagine what could possibly explain these things.

他并不是通过观察过去的现象来提出广义相对论的。

He wasn't looking at past phenomena in order to come up with general relativity.

他试图解释物理学中存在的某些问题。

He was seeking to explain certain problems that existed in physics.

归纳法与此无关。

Induction wasn't a part of it.

好的解释依赖于创造性。

Good explanations rely on creativity.

这些好的解释当然是可以检验和证伪的，但它们难以被轻易改变，并且能做出风险高且精确的预测。

These good explanations, testable and falsifiable, of course, but they are hard to vary, and they make risky and narrow predictions.

对于正在收听这个播客并试图弄清楚如何将其融入日常生活的人来说，这是一个很好的指导点。

That's a good guiding point for anybody who is listening to this podcast and trying to figure out how they can incorporate this in their everyday life.

你最好的理论将是创造性的猜测，而非简单的推断。

Your best theories are going to be creative guesses, not simple extrapolations.

我有一些题外话想深入探讨，比如费曼路径积分，因为在我看来多重宇宙理论和费曼路径积分之间存在某种深刻的对称性。

I had a bunch of asides that I wanna dive into, like Feynman path integrals, because it seems to me that there's some kind of a deep symmetry between multiverse theory and Feynman path integrals.

你说得完全正确。

You're absolutely right.

他相信多重历史，但至于他认为这些是实际存在的物理实体还是仅仅是数学对象，这一点尚存疑问。

He believed in multiple histories, but to the extent that he thought that these were actually physically real things or merely mathematical objects is open to question.

他对这个问题相对保持沉默。

He was relatively silent on the matter.

他无疑是个现实主义者，但他说过一句最糟糕的俏皮话。

He was certainly a realist, but he made one of the worst quips.

他是个绝对的天才，可能是仅次于爱因斯坦的二十世纪第二大物理学家。

And he's an absolute genius, probably next to Einstein, the second greatest physicist of the twentieth century.

但他说过，如果你认为你理解量子理论，那你就不理解量子理论，这简直是胡说。

But he said, if you think you understand quantum theory, you don't understand quantum theory, which is nonsense.

休·埃弗雷特就理解量子理论。

Hugh Everett understood quantum theory.

大卫·多伊奇理解量子理论。

David Deutsch understands quantum theory.

所以那是费曼少数几次陷入非理性和悲观主义的时刻之一。

So that was one of the few occasions where Feynman fell into irrationality and pessimism.

我想是普朗克说过，科学是以一场场葬礼为单位前进的。

I think it was a Plank who said science advances one funeral at a time.

是的。

Yes.

没错。

Yeah.

遗憾的是，即便是最优秀的人也会固步自封。

Unfortunately, even the best gets stuck behind.

我在自己的领域就目睹过这种情况，比如我们这个时代最伟大的投资者沃伦·巴菲特和查理·芒格，他们绝对是天才，却无法理解加密货币。

I see this in my own field where, you know, some of the greatest investors of our time like Warren Buffett and Charlie Munger who are just absolute geniuses, but they cannot wrap their minds around cryptocurrencies.

对他们而言，互联网原生的、可编程的超主权货币概念是完全陌生的，因为他们认为货币永远是政府提供并控制的，无法想象其他可能性。

The idea that there's going to be an extra sovereign money that is native to the Internet, is programmable, is foreign to them because to them money is always something that has been provided by the government and controlled by the government, and they just cannot imagine it any other way.

这就是人性使然。

So it's just the nature of people.

还有所罗门诺夫归纳理论。

There's also the theory of Solomonoff induction.

我可能描述得不够准确，但大意是说：如果你想找到一个解释某现象的理论（这里的理论是指用二进制字符串编码的内容），那么正确的理论应该是概率加权的，它考虑所有可能的理论，但根据其复杂性进行加权。

I'm gonna mangle the description, but it says if you want to find a theory that explains why something is happening, and now a theory here is something that's encoded as a binary string, then the correct theory is actually going to be a probability weighted theory that takes into account all the possible theories but weighs them based on their complexity.

所以越简单的理论越可能是正确的，越复杂的理论可能性越低。

So the simpler ones are more likely to be true, and the more complex ones are less likely to be true.

你把它们全部加起来，这就是你找出解释的正确概率分布函数的方法。

And you sum them all together, and that's how you figure out the correct probability distribution function for your explanation.

这类似于贝叶斯主义，不是吗？

That's similar to Bayesianism, isn't it?

在这两种情况下，他们都假设你可以列举出所有可能的理论，但实际上你做不到，因为这里涉及到创造性。

In both cases, they're assuming that you can enumerate all the possible theories, but you can't because that's the creativity coming in.

在科学中，很少会出现多于一个可行理论的情况。

It's very rare in science to have more than one viable theory.

在物理学中，我们提到过牛顿的万有引力理论，还有广义相对论。

In physics, we mentioned Newtonian theory of gravity and there was general relativity.

这是少数几个你实际上有两个竞争理论的罕见例子之一。

That's one of the rare occasions where you actually have these two competing theories.

几乎从未听说过有三个竞争理论的情况。

It's almost unknown to have three competing theories.

让人们困惑的是，归纳法和贝叶斯主义在已知的有限约束空间内效果很好。

What confuses people is that induction and Bayesianism work really well for finite constrained spaces that are already known.

它们不适用于新的解释。

They're not good for new explanations.

贝叶斯主义说的是我获得了新的信息。

Bayesianism is I got new information.

我用它来调整我之前已有的概率预测。

I used it to wait the previous probability predictions that I had.

现在我已经根据新数据改变了我的概率，所以我相信会发生不同的事情。

Now I've changed my probability based on the new data, so I believe that something different is going to happen.

例如，我不知道你是否还记得蒙特霍尔秀。

For example, I don't know if you remember the Monty Hall show.

蒙特霍尔打电话给你，那里有三扇门，其中一扇后面有宝藏，另外两扇什么都没有。

Monty Hall calls you up and there's three doors and there's treasure behind one of them and then two of them don't have anything.

然后你选择一扇门，一号门、二号门或三号门。

And you pick which door it's gonna be, door number one, two, or three.

接着他会打开另外两扇门中的一扇，向你展示后面什么都没有。

Then he opens one of the other two doors and shows you there's nothing behind it.

现在你想改变你的选择吗？

Now do you wanna change your vote?

朴素概率的理解认为，不，我不会改变选择。

The understanding of naive probability says, no, I wouldn't change my vote.

为什么他给我看的那扇门后面没有东西会改变概率呢？

Why should it matter that one of the ones he showed me doesn't have something?

概率不应该发生变化。

The probability should not have changed.

但贝叶斯主义认为，你获得了新的信息。

But Bayesianism says, you've got new information.

你应该修正你的猜测，并选择另一扇门。

You should revise your guess and you should switch the other door.

更简单的说法是想象有100扇门，你随机选择一扇后，他打开了剩下的99扇中的98扇，向你展示后面什么都没有。

And the easier way to say that is imagine there were a 100 doors and then you picked one at random, then he opens 98 of the remaining 99 shows you there's nothing.

现在你会换门吗？

Now do you switch?

当然，你会想换一个选择，因为你一开始选中那100个中的一个的概率能有多大呢？

And of course, you'd wanna switch because what are the odds that you picked one of the 100 in the first place?

现在你的概率是100分之99。

Now your odds are 99 out of 100.

人们发现这一点后会说，当然了，现在我是个聪明的贝叶斯主义者了。

And people discover this and say, of course, now I'm a smart Bayesian.

我能根据新信息更新我的先验概率。

I can update my priors based on new information.

聪明人都是这么做的，因此我也是个贝叶斯主义者。

That's what smart people do, and therefore, I'm a Bayesian.

但这完全无助于你发现新知识或新解释。

But it in no way helps you discover new knowledge or new explanations.

这是贝叶斯主义毫无争议的用途，它是一个非常强大的工具。

That's the uncontroversial use of Bayesianism, which is a very powerful tool.

它被用于医学领域，试图找出哪些药物可能比其他药物更有效。

It's used in medicine of trying to figure out which of these medicines might be more effective than others.

因此，像贝叶斯主义这样的整个数学领域，完全可以毫无争议地应用于科学。

So there are whole areas of mathematics like Bayesianism, can be applied in science without controversy at all.

但当我们说贝叶斯主义是我们生成新解释的方式，或是评判一个解释优于另一个的方式时，就存在争议了。

It's where we say that Bayesianism is the way in which we can generate new explanations or the way in which we can judge one explanation against another.

事实上，我们生成新解释的方式是创造力，而评判解释优劣的方式要么是通过实验证伪，要么直接通过批评认识到某个解释本身就是糟糕的。

In fact, the way in which we generate new explanations is creativity, and the way in which we judge one explanation against another is either experimental refutation or straightforward criticism of realizing that one of those explanations is just a bad explanation.

归纳法还认为预测是科学存在的主要原因，但事实并非如此。

Induction also says that prediction is the main reason for the existence of science, but it's not.

这是解释。

It's explanation.

你想要的是一种对正在发生之事的解释，即便你无法确切预知接下来会发生什么。

You want an explanation of what's going on, even if you can't necessarily predict with any certainty what's gonna happen next.

事实上，带着某种确定性预知未来反而会令人泄气，而未知的乐趣可能远胜于对明日之事的确信无疑。

And in fact, knowing what's gonna happen next with some degree of certainty can be deflating, and the unknown can be far more fun than having absolute certitude about what tomorrow will bring.

这引出了一个相关观点：科学从无定论。

This brings us to a related point that the science is never settled.

我们应当永远保持新创意与新猜想的空间。

We should always be free to have new creativity and new conjecture.

你永远不知道最好的想法会从何处涌现，必须认真对待所有真诚提出的见解。

You never know where the best ideas are going to come from, and you have to take everything that's made in good faith seriously.

因此所谓'科学已成定论'或'科学已封闭'的说法纯属无稽之谈。

And so this idea that the science is settled or the science is closed is nonsense.

这暗示着我们能就提出新理论的过程达成共识，而实际上这个过程需要创造性与猜想。

And it implies that we can all agree upon the process with which we come up with new theories, rather it's through creativity and conjecture.

大门永远向带着新想法加入并参与其中的人们敞开。

And the door is always open for new people with new ideas to come in and do that.

正如帕帕所说，在无限的未知面前我们都是平等的。

As Papa said, we're all equal in our infinite ignorance.

所以即便有人自称专家，甚至他们的专家身份确凿无疑——

So even if someone claims expertise, they might even be valid in their claim to expertise.

仍有无数事物是他们所不知的，而这些未知可能影响他们已知的领域。

There's an infinite number of things they do not know, and those infinite number of things they do not know could affect the things they do know.

所以那个正在上学、对任何领域都不精通的孩童，仍能提出挑战最伟大专家根基的想法。

So the child who is coming through school who is not expert in anything can still come up with an idea that can challenge the foundations of the greatest expert.

因为专家和孩童一样，对许多事物都一无所知。

Because the expert, like the child, is ignorant about a whole bunch of things.

他们可能犯错，但这并不妨碍其他缺乏精细知识的人指出错误并提出更好的想法。

They could have error that does not preclude someone else who lacks that fine tuned knowledge from being able to point out there's an error and here's a better idea.

许多关于我们即将创造AGI的理论，都是基于对计算能力的简单外推。

A lot of the theories as to why we're imminently going to create an AGI are based on a naive extrapolation of computational power.

这就像我们不断通过增加计算能力来归纳推理，AI已经在视觉、国际象棋和电子游戏上超越了我们，所以它很快就要开始思考了。

It's almost we'll do the induction of more and more computational power, and AI has already gotten good at vision and beating us at chess and at video games, so therefore it's gonna start thinking soon.

我想讨论的另一个分支观点是：人类是地球上的资源消耗者，我们正在耗尽地球的所有资源。

Another offshoot that I wanna discuss is this idea that humans are this resource consumers on the earth, and we're eating up all the earth's resources.

因此地球上增加更多人口是个坏主意。

So having more humans on the earth is a bad idea.

但如果你相信知识源于创造力，那么明天出生的任何一个孩子都可能成为下一个爱因斯坦或费曼，用具有非线性输出的创造力发现永远改变世界的事物。

Whereas if you believe that knowledge comes through creativity, then any child born tomorrow could be the next Einstein or the next Feynman and discover something that will change the world forever with creativity that has nonlinear outputs and effects.

但目前我们非常关注污染或某些物种的灭绝问题。

But at the moment, we're very concerned about the pollution or the loss of certain species.

这些确实是部分人合理的担忧，但绝不能以牺牲长远愿景为代价——只要我们能够通过现有资源加速进步，或许就能解决所有这些问题甚至更多。

And these are legitimate concerns for some people, but it should never be at the expense of the long term vision that perhaps we can solve all of those problems and far more if only we could have progress at a faster rate by using the resources that we have available to us.

有个问题是：为什么世界上悲观主义者似乎总是比乐观主义者多，尤其当我们仍主要生活在启蒙价值观和巨大创新之中时。

There's a question why the world always seems to be full of more pessimists than optimists, especially when we still live with mostly enlightenment values and such tremendous innovation.

这可能有多重原因，但做悲观主义者总是比做乐观主义者更容易。

There are probably multiple reasons for that, but it's just easier to be a pessimist than an optimist.

更难预测生活会如何改善。

It's harder to guess how life is gonna improve.

更容易确切地推断出它会如何变得更糟。

It's easier to literally extrapolate how it's gonna get worse.

你还可以辩称，毁灭的风险如此之大，以至于无法挽回，也许我们天生就是悲观主义者，因为如果你乐观时是对的，那只会获得微小收益。

You could also argue that the risk of ruin is so large that you can't come back from it that maybe we're hardwired to be pessimist because if you're correct when you're optimistic, then you have a small gain.

但如果你乐观时错了，被老虎吃掉，那就全完了。所以从这个意义上说，我们可能天生就是悲观的。

But if you're wrong when you're optimistic and you get eaten by a tiger and it goes to zero, So maybe we're hardwired to be pessimistic in that sense.

如果你是某种学者，能够解释所有存在的问题、这些问题有多危险，以及为何需要资金来更深入研究这些问题，这似乎是学术上严肃的立场。

If you're an academic of some kind, then being able to explain all of the problems that are out there and how dangerous these problems are and why you need funding in order to look at these problems in more depth, That appears to be the intellectually serious position.

有人声称我们能解决这个问题。

Someone who claims that we can solve this.

听起来有点理想化，尽管很正确，但实际上，协作、合作和资源开发才是推动知识经济前进的动力，从而解决所有这些问题。

It sounds a little bit kumbaya, even though it's quite right, but in fact, collaboration, cooperation, and resource exploitation will actually be the thing that's going to drive this knowledge economy forward so that we can solve all these problems.

如果你能站在TED演讲台上，皱着眉头对观众说'这些都是我们将失败和毁灭的方式'，似乎总是显得更学术严肃。

It always seems more intellectually serious if you can stand up there with a frown in your face in front of a TED Talk audience and say, these are all the ways in which we're going to fail and which we're going to come to ruin.

我也有过录制末日预言播客的罪过，内容是关于外星人炸毁地球的。

I'm guilty of having recorded one of these doomsayer podcasts about enders blowing up the earth.

那是我最后悔的一期播客。

That was the one podcast that I regretted the most.

我们进行了精彩的对话，但我从根本上不同意任何可能得出的结论，比如世界要毁灭了，所以我们应该放慢脚步。

We had a great conversation, but I don't fundamentally agree with any of the conclusions that might come out of that which say the world is gonna end, so we should slow down.

唯一的出路就是通过进步。

The only way out is through progress.

因此，我没有像推广其他播客那样大力推广这个。

And subsequently, I haven't promoted as much as I promoted my other podcast.

在阅读德意志的文章后，我明白了原因。

And upon reading Deutsche, I realized why.

因为做一个悲观主义者很容易。

It's because it's easy to be a pessimist.

这是一个容易陷入的陷阱，但它暗示人类缺乏创造力。

It's an easy trap to fall into, but it implies that humans are not creative.

它没有承认我们通过创新摆脱以往困境的所有方式。

It doesn't acknowledge all the ways that we have innovated our way out of previous traps.

从根本上说，企业家天生乐观，因为乐观会得到回报。

And fundamentally, entrepreneurs are inherently optimistic because they get rewarded for being optimistic.

正如你所说，知识分子因悲观而获得回报。

As you're saying, intellectuals get rewarded for being pessimistic.

所以这里总是存在很多激励偏差。

So there is always a lot of incentive bias here.

作为学者，你可能被激励去悲观。

As an academic, you may be incented to be pessimistic.

作为企业家，你可能被激励去乐观。

As an entrepreneur, you may be incented to be optimistic.

如果你是悲观主义者，你会从他人那里获得反馈。

If you're a pessimist, you get your feedback from other people.

这是一种社会行为。

It's a social act.

你正在用你的悲观主义说服他人。

You're convincing other people of your pessimism.

到目前为止，他们的大部分悲观预测都被证明是错误的。

And so far, most of their pessimistic predictions have turned out to be false.

如果你看看那些预言世界末日或环境灾难的时间线，它们都错得离谱。

If you look at the timelines on which the world was supposed to end or environmental catastrophes were supposed to happen, they've been quite wrong.

但如果你观察那些乐观的企业家，他们的评价来自自然和自由市场的反馈，我认为这些才是更现实的反馈机制。

But if you look at the optimistic entrepreneurs, they are rated by feedback from nature and free markets, which I believe are much more realistic feedback mechanisms.

一般来说，那些从同行那里获得反馈的职业往往容易变得腐败。

In general, professions in which you get your feedback from other members of that profession tend to get corrupted.

当你看到记者写文章是为了打动其他记者，或者餐馆老板经营餐厅是为了取悦美食家和其他餐馆老板时，这些最终都不实用且质量不高。

When you see a journalist writing articles to impress other journalists or a restaurateur running a restaurant that's designed to impress other foodies and other restaurateurs, those end up not being practical and high quality.

他们可能在某个精英圈子里获得赞誉和奖项，但这并不能反映现实。

They may receive accolades and prizes within certain elite circles, but they're not reflecting reality.

那些从大自然（如科学家或实验者）或自由市场（人们用金钱和时间投票）获得反馈的人，他们的预测会准确得多。

Where someone who is getting feedback from either mother nature, like a scientist or an experimentalist, or from free markets where other people are voting with their money and their time, those are going to be much better predictors.

在现实世界中工作并获得报酬的人往往是乐观主义者。

The people who are operating in the real world and are getting paid for it tend to be optimists.

那些生活在象牙塔里的人则被激励成为悲观主义者。

The people who are operating in ivory towers are incented to be pessimists.

要成为一名企业家，你必须对自己创造的东西对他人有价值持乐观态度。

To be an entrepreneur, you need to be optimistic about the fact that you're creating something that other people are going to find value in.

持有悲观哲学的人往往也有悲观的心理学倾向。

And people who have a pessimistic philosophy tend to have a pessimistic psychology as well.

如果你不断思考这个世界正在分崩离析的种种迹象，这将对你的社会观、家庭观、朋友观乃至一切事物产生日常影响，因为你认为这个世界注定要毁灭。

If you're constantly thinking about all the ways in which the world is going to rack and ruin, then this has a day to day impact upon your outlook on the rest of society and on your family, on your friends, on everything, because you think that this world is condemned.

因此你会感到肩头沉重，这种情绪会通过你向外界展现自我的方式流露出来。

So you're going to feel that weight upon your shoulders and it's going to come through in the way in which you present yourself to the rest of the world.

眼下我们在社交媒体上经常看到这种现象。

We see a lot of this on social media right now.

企业家通常太忙而无暇花大量时间在社交媒体上，但你会发现科学家、学者和记者们对生活感到沮丧，因为他们对现实持悲观态度，这必然会影响他们对世界的主观体验——与那些正在创造、试图为世界带来新生事物的人截然不同。

Entrepreneurs are typically too busy to spend a whole lot of time on social media, but you do get scientists, academics, journalists who are depressed with life because they have a pessimistic view of reality, and that's gotta have an impact upon their subjective experience of the world, unlike people who are creating, trying to bring something new into existence.

但不幸的是，悲观主义会自我实现。

But, unfortunately, the pessimism is self fulfilling.

一切恶果皆源于认知不足。

All evils are due to lack of knowledge.

理性乐观主义才是出路。

Rational optimism is the way out.

数据支持这一点。

The data supports it.

历史也佐证这一点。

History supports it.

我们总能通过创造力找到改善自身及全人类生活的完美方案。

And we can always come up with good explanations through creativity to improve our lives and everybody else's lives.

所以请保持乐观。

So stay optimistic.