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Deutsch对世界有一种宏大的观点，他认为所有重要的事物都能被单个个体所理解。
Deutsch has this great view of the world where he believes that everything important is understandable by a single human.
他所说的'重要'，指的是那些驱动现实大部分运作的基础理论。
By important, he means underlying base theories that drive most of reality.
而他特别关注四种理论。
And he fixates on four theories.
我可能会争辩说或许还有更多，尤其是当你开始涉及亚当·斯密的《国富论》和其他一些社会学理论时。
I could argue maybe there's a few more, especially if you start getting into Adam Smith and the wealth of nations and a few other sociological ones.
但他显然是个物理学家。
But he's obviously a physicist.
他更关注现实和真理探索，而非人类系统。
He's concerned more with reality and truth seeking, not human systems.
他选择的四种理论是：认识论理论、自然选择进化论、量子理论（他将相对论等其他物理学纳入其中），以及计算理论（包括他的量子计算理论）。
The four that he picks are the theory of epistemology, the theory of evolution by natural selection, quantum theory, he subsumes relativity and other physics into that, and then the theory of computation, which includes his theory of quantum computation.
这四种理论都令人着迷。
These four are fascinating.
或许值得为不同听众分别探讨每一种理论。
It's probably worth touching on each one for various listeners.
这些理论各自有趣之处是什么？
What is interesting about each of these theories?
其中可能不太明显的突破点是什么？
What is the breakthrough here that might be non obvious?
让我们从认识论开始。
Let's start with epistemology.
我之所以喜欢认识论的初始部分，是因为多伊奇对认识论中的正确内容进行了非常严谨的审视。
The reason I love the beginning of affinity is because Deutsch does a very rigorous review of what is correct in epistemology.
在认识论中，我们所知的最佳答案是什么？
What do we know to be the best answers in epistemology?
一旦你掌握了这些，一旦你有了一个完善的知识理论，你就能判断其他什么是真实的。
And once you have that, once you have a good theory of knowledge, then you can decide what else is true.
如果你的知识理论基础不佳，那么当你认为某些事情可能为真时，实际上会误判一堆错误的事情。
If you're starting with a bad basis for a theory of knowledge, then you're going to decide on a bunch of things that are false when you think they might be true.
他的认识论以优质解释为核心。
His epistemology is centered around good explanations.
该理论采纳了波普尔将科学与真理探索视为纠错机制的观点，并进行了拓展。
It takes Popper's view of science and truth seeking as being error correcting mechanisms and expands on it.
不过我很想听听你对多伊奇提出的知识理论或认识论的总结。
But I'd love to hear your summary of the theory of knowledge or epistemology as Deutsch lays it out.
最初对知识本质的猜想形成了所谓的'被证实的真实信念'知识观。
The initial guesses at what knowledge was all about amounted to what is known as the justified true belief vision of knowledge.
这至今仍是最主流的观点。
And it's still the most prevalent idea today.
任何自称贝叶斯主义者的人都是'被证实的真实信念'的信徒。
Anyone who calls themselves a Bayesian is a justified true believer.
这种误解认为知识就是要试图证明你的信念是真实的。
And that's the misconception that knowledge is about trying to justify as true your beliefs.
如果你做到了这点，你就可以说：我知道那件事。
And if you've done so, then you can say, I know that thing.
那么，如果我能证明我的重力理论为真，我就应该相信那个重力理论，只有这样我才能说它是已知的吗？
So if I can justify as true my theory of gravity, then I should believe that theory of gravity, and only then can I say that it's known?
问题在于，没有任何方法能证明任何知识片段为真。
The problem with this is that there is no method of showing as true any piece of knowledge.
所以，多伊奇在他的书中提倡的改进就是波普尔给我们的这种观点：我们对现实所有的只是猜测，是猜想。
So the improvement Deutsch promotes in his books is this vision that Popper gave us that all we have are guesses about reality, conjectures.
人们会想，哦，这听起来有点含糊其辞。
People think, oh, that sounds a bit wishy washy.
这不过是个猜测。
It's just a guess.
但这不是随机的猜测。
Well, it's not a random guess.
不是随便谁决定做个猜测，就能与其他所有猜测平起平坐。
It's not just anyone decides to have a guess and therefore that stands on equal footing to every other.
不。
No.
这是一个经受住了考验的猜测，经受了试图证明其为假的尝试。
It's a guess that has stood up against trials, against attempts to show that it's false.
当人们无法通过这种反驳方法证明其为假时，我们就接受它作为知识的一部分。
And when people are unable to show that it's false via this method of refutation, then we accept it as a piece of knowledge.
这使得我们能够接受这样一个事实：我们未来将能够取得进步，因为我们所有的知识都是推测性的。
This allows us to thereby accept the fact that we're going to be able to make progress in the future because all of our knowledge is conjectural.
所有这些都是我们当时的最佳猜测。
All of it is our best guess at the time.
因此，知识中存在这种弹性，使我们能够承认会有错误，我们会纠正它们，从而能够在无限的未来中不断进步。
And therefore, there's this elasticity within the knowledge that allows us to say, there's going to be errors, we're going to correct them, and thereby be able to make progress off into the infinite future.
这与之前的知识观念不同，后者认为一旦某件事被证明为真，那么它就是真的。
This is unlike the previous conception of knowledge, which says, once you've justified something as true, well, it's true.
如果它是真的，就意味着其中没有任何虚假之处，因此它不可能被反驳。
If it's true, that means there is nothing false about it, and therefore it can't possibly be refuted.
这是一种非常宗教化的观念。
That's a very religious notion.
这种观念的现代表述是贝叶斯主义。
The modern incantation of this is Bayesianism.
贝叶斯主义认为你有一个理论，收集更多证据后，你会越来越确信你的理论是正确的。
Bayesianism says you have a theory, you collect more evidence, and you become more and more confident over time that your theory is correct.
情况甚至更糟，因为它声称这种贝叶斯推理能让你产生新理论，而实际上它做不到。
And it gets a little bit worse than that because then it says this Bayesian reasoning enables you to generate new theories, which it can't.
它最多只能表明你对这个理论比对那个理论更有信心。
The best that it can hope to do is to show you that you are more confident in this theory than what you are in that theory.
波普尔的观点是，如果你能证明某个特定理论存在缺陷，你就可以摒弃该理论。
The Popperian view says, if you can show that there's a flaw in a particular theory, you can discard that theory.
在几乎所有情况下，你手头只有一个可供选择的理论。
In almost all cases, you only ever have one theory on offer.
以引力为例，目前确实只有一个理论可供选择。
In the case of gravity, there literally is only one theory on offer at the moment.
那就是广义相对论。
There's general relativity.
此前，我们确实有两种理论。
Previously, we did have two theories.
我们有牛顿引力理论，也有广义相对论，但我们做了一个关键实验。
We had Newtonian gravity and we had general relativity, but we did a crucial experiment.
这种关键实验的理念是科学皇冠上的明珠。
This idea of crucial experiment is the cherry on top of science.
当存在两种竞争理论时，通过特定实验就能排除其一，而另一理论则得以保留。
You've got these two competing theories and you have a particular experiment that if it goes one way, one theory is ruled out, but the other theory is not.
在这种情况下，只要没有出现问题，该理论就会一直被沿用。
In which case, you keep that theory for so long as no problems arise.
这种知识观使我们能够无止境地追求进步，这与其他任何关于知识的理念都截然不同。
This vision of knowledge enables us to have an open ended quest for progress, which is completely unlike any other idea about knowledge.
绝大多数物理学家仍持贝叶斯主义观点。
The overwhelming majority of physicists are still Bayesian.
他们坚持贝叶斯主义的原因在于，这通常是大学里教授的内容，也被视为理解世界的严谨智识方式。
The reason they're still Bayesian is because this is typically what's taught in universities, and this is what passes for an intellectually rigorous way of understanding the world.
但这不过是我所称的某种科学主义变体。
But all it is is what I would call a species of scientism.
因为他们背后有贝叶斯定理这个公式——一个完全合理的统计公式。
It's because they have a formula behind them, Bayes theorem, which is a perfectly acceptable statistical formula.
人们经常以完全正当的方式使用它。
People use it all the time in perfectly legitimate ways.
只是它并非认识论。
It's just that it's not an epistemology.
这并不能保证甚至让你确信你的理论实际上是正确的。
It's not a way of guaranteeing or even being confident that your theory is actually true.
我最喜欢的例子是在1919年之前，几乎所有关于引力的实验都显示其与牛顿的引力理论一致。
My favorite example of this is prior to 1919, approximately, every single experiment that was done on gravity showed that it was consistent with Newton's theory of gravity.
贝叶斯主义者在这种情况下会说什么？
What does a Bayesian say in that situation?
贝叶斯主义者只能说对牛顿理论的信心越来越强。
What a Bayesian has to say is getting more and more confident in Newton's theory.
这怎么说得通呢？
How does that make sense?
在被证明错误的前一天，却是你对它最有信心的时刻，这如何自圆其说？
How do you square that circle of the day before it was shown to be false was the day when you were most confident in it?
而Purperion理论不存在这个问题。
Now, Purperion doesn't have this problem.
Purperion理论直接指出：牛顿的理论从未真正正确过。
Purperion just says, at no point was Newton's theory actually true.
它包含部分真理，但这些真理并非我们可以测量的东西。
It contains some truth, but that truth isn't a thing that we can measure.
我说它包含部分真理，是因为它确实比其他随机猜测重力本质的理论更接近现实。
I say it contains some truth because it's certainly got more direct connection to reality than some other random person's guess about what the nature of gravity is.
引力确实大致遵循平方反比定律，但并不精确。
Gravity does indeed approximately vary as the inverse square law, but not exactly.
因此我们需要广义相对论来修正牛顿引力理论的误差。
So we need general relativity to correct the errors in Newton's theory of gravity.
尽管广义相对论是我们目前最好的理论，但它终究不可能是引力的终极理论。
And even though general relativity is our best theory right now, that can't ultimately be the final theory of gravity.
根本不存在所谓的引力终极理论。
There can be no final theory of gravity.
我们所拥有的只是对现实越来越好的近似描述。
All we have is better and better approximations to reality.
我认为我们如此容易陷入贝叶斯主义，可能与为何我们容易陷入悲观主义有关。
I think the reason we fall into Bayesianism so easily is probably related to why we fall into pessimism so easily.
我们在进化上就被设定为贝叶斯主义者。
We're evolutionarily hardwired for Bayesianism.
地球上其他无法形成合理解释的动物都是贝叶斯主义者。
Every other animal on the planet that can't form good explanations is a Bayesian.
它们只是观察重复事件并认为：昨天太阳升起了，明天太阳也会升起。
They're just looking at repeated events and saying the sun rose yesterday, the sun will rise tomorrow.
如果我碰那个东西，它是烫的。
If I touch that thing, it's hot.
将来它很可能还是烫的。
It's probably gonna be hot in the future.
这就是我们大多数生物系统以及进化遗产的运作方式。
So that is how most of our biological systems and how most of our evolutionary heritage worked.
只是现在我们有了能够形成合理解释的新皮质，它能通过不可见的事物来解释场景，赋予我们更高层次的推理能力。
It's just now we have this neocortex that can form good explanations that can explain the scene in terms of the unseen and that gives us a higher level of reasoning.
但这种更高层次的推理并非我们的本能。
But that higher level of reasoning is not instinctual to us.
这需要付出努力。
It requires effort.
这需要深入思考。
It requires deep thinking.
但我们默认采用贝叶斯主义，因为至少在纯生物学层面上，我们周围的自然界似乎就是这样运作的。
But we default to Bayesianism because that is how a lot of the natural world around us seems to work at least at the purely biological level.
事实上，我手头有霍珀的著作《客观知识》，副标题是《一种进化论方法》。
In fact, I've got behind me Hopper's book called Objective Knowledge, and it's subtitled An Evolutionary Approach.
这绝非偶然。
And that's no accident at all either.
正如我们所理解的，认识论理论与进化论之间存在着对称性。
There's symmetry between the theory of epistemology and the theory of evolution as we understand it.
在我们理解所谓的达尔文进化论之前，人们唯一的想法是这些实体必须被创造出来。
Before we understood what is known as the Darwinian theory of evolution, the only idea that people had was these entities had to be created.
你周围看到的所有动植物都必须是我们的创造者创造的。
All the plants and animals that you see around you had to be created by our creator.
当时没有解释机制。
There was no explanatory mechanism.
有些人提出了随时间逐渐变化的想法。
Some people came up with the idea of gradual change over time.
拉马克就是其中之一。
Lamaque was one such.
长颈鹿之所以有长脖子，是因为它们的祖先脖子稍短，所以它们试图伸长脖子去够那些够不到的叶子。
The reason why giraffes have long necks is because their ancestors had slightly shorter necks, so they tried to stretch their necks to reach the leaves they couldn't reach.
但同样地，除了个人去健身房锻炼二头肌，随着时间的推移二头肌会变大这一事实外，并没有其他机制。虽然你可以通过健身增大二头肌，但这并不意味着你的孩子会继承这些特征。
But again, there was no mechanism for this beyond the fact that when individual goes off to the gymnasium and works on their biceps and their biceps get a little bigger over time, although you can work out in the gym and increase the size of your biceps, that doesn't mean your children are going to inherit those characteristics.
所以达尔文提出的观点与波普尔在知识领域的观点相似。
So what Darwin came up with is a similar idea to what Popper had in knowledge.
这就是纠错机制。
It was error correction.
这个观点认为生物体会在特定环境中进行自我试验。
The idea that an organism would trial itself out in a particular environment.
如果它不适应那个环境，就像我们说的，它就会消亡。
And if it wasn't, as we say, fit for that environment, then it would die off.
但如果它适应那个环境，就能存活下来。
But if it was fit in that environment, then it would survive.
因此，在生物体与环境之间存在着这种与现实的碰撞。
So you have this encounter with reality between living organisms and the environment.
正是环境从现实中给予反馈，并淘汰那些不够适应生存的生物体。
And it's the environment that's giving you feedback from reality and destroying those organisms that aren't fit enough to survive.
新达尔文主义的观点是为我们指明了选择的单位。
The neo Darwinist view is to give us what the unit of selection is.
不是群体或族群。
It's not the group or the herd.
甚至不是个体。
It's not even the individual.
而是基因。
It's the gene.
这是理查德·道金斯提出的'自私基因'理论，他指出如果某个基因恰好不适应特定环境，就可能导致该生物体的死亡。
It's the selfish gene ID, which comes to us from Richard Dawkins, who says, if any one of those genes happens to be not fit for the particular environment, that could cause the death of that organism.
但物种未必会灭绝。
But the species might not go extinct.
物种可能存活下来，但随着环境变化，其整个DNA会随时间发生极其微妙的变化。
The species might survive, but its entire DNA will ever so subtly change over time as the environment changes.
如今我们已经将其升级。
And now we have levelled that up.
我们人类是进化过程的下一阶段，能够创造解释性知识，实现同样的功能。
We human beings are the next step in that evolutionary process where we can create explanatory knowledge, which does the same thing.
多伊奇喜欢说基因进化只是个前奏。
Deutsch likes to say genetic evolution was merely a prelude.
接下来将要发生的是模因进化。
What's coming next is memetic evolution.
从此以后，宇宙的历史将是思想经历与基因相同进化过程的历史。
The history of the universe from here on out is going to be the history of ideas undergoing the same evolutionary process as what the genes did previously.
这四种理论中有三个呈现出有趣的模式。
Three out of these four theories have an interesting pattern to them.
通过优质解释和认识论，我们说的是猜想及其反驳，而纠错正是我们完善知识的方式。
With good explanations and epistemology, we're saying conjectures and their refutations, and error correction is how we improve knowledge.
在基因进化中，基因突变、变异和自然选择会淘汰那些无效的基因。
With genetic evolution, genetic mutations, variation, and natural selections weeds out the ones that didn't work.
在此基础上还有模因进化，我们产生各种想法，然后通过批评淘汰那些无效的观点。
And then there's mimetic evolution on top of that where we have ideas and then criticism weeds out the ideas that don't work.
在发明创造中与之相关的是试错过程。
Related to that in invention, there's trial and error.
或者在资本主义中，初创企业诞生而那些想法糟糕的终将失败。
Or in capitalism, startups get created and the ones that have bad ideas fail.
因此我们看到这种模式不断重复出现。
So we see this pattern recurring over and over.
然而有趣的是这里还存在另一个元模式。
What's interesting though is another meta pattern here.
这里的元模式就是人类是独一无二的。
And the meta pattern here is that humans are exceptional.
在认识论中，人类是唯一非贝叶斯推理者。
In epistemology, humans are the only non Bayesian reasoners.
在进化论中，人类是我们已知的唯一具有模仿能力的生物。
In evolution, humans are the only mimetic creatures that we know of.
在计算理论中，除了我们发明的计算机外，人类是我们已知的唯一通用解释者。
In the theory of computation, humans are the only universal explainers that we know of other than, of course, the computers that we've invented.
有趣的是，科学让我们从人类是宇宙中心的观点转变为认为人类其实并不特殊。
So what's interesting is that science took us from this view of humans being at the center of the universe to being actually humans are nothing special.
你只是众多可能孕育生命的类开普勒行星中微不足道的一个。
You're just one little planet out of an almost infinite number of now Kepler like planets that could be bearing life out there.
但我们讨论的这四个理论中有三个都指向人类极其特殊这个方向。
But three of these four theories that we're talking about are pointing us in this direction of humans are extremely exceptional.
人类能够获得最大限度的知识。
Humans are capable of maximal knowledge.
对我来说一个有趣的认知是：即使你是上帝，即使你拥有无限的知识与力量，即使你能控制整个宇宙，你依然无法确定自己是否身处模拟之中。
One interesting realization for me was that even if you were God, even if you had infinite knowledge and power, even if you could control the entire universe, you still wouldn't know you're not in a simulation.
你永远无法证明自己不在一个模拟世界里。
You still could never prove that you're not in a simulation.
即便作为引导者，你头脑中也不存在人类无法理解的概念——除非物理定律本身发生了改变。
And even as a guide, there's no concept that you could hold in your head that a human being couldn't hold, unless, of course, the laws of physics are different.
如果物理定律不同，那么一切结论都将失效。
If the laws of physics are different, then all bets are off.
谁知道呢？
Who knows?
但在现有物理定律框架下，人类完全能够达到认知与意识的巅峰。
But working within the current laws of physics, humans are capable of maximum knowledge, of maximum awareness.
这指向一个人类卓尔不群的世界观，而非将人类视为失控泛滥的另一种细菌。
And that points to a world where humans are exceptional and not just another form of bacteria that got out of control and overran this planet.
许多基础理论都导向人类独特、知识无限的视角。
A lot of these fundamental theories lead to a viewpoint that humans are special, that knowledge is infinite.
只要我们保持纠错机制不遭破坏并持续创造新知识，就有充分的理由保持乐观。
And as long as we don't destroy the means of error correction and we're always creating new knowledge, then there's good reason to be optimistic.
你现在提出的可是少数派观点。
Now you're pointing out a minority opinion there.
我认为文化认知仍停留在你所说的后半部分。
I think culture is still stuck in the second part of what you were saying.
最初我们曾以为自己是宇宙的中心。
Originally, we thought that we were at the center of the universe.
这是宗教对人类在宇宙中地位的构想。
This was the religious conception of man's place in the cosmos.
地球被天球所环绕，万物都围绕地球运转。
The earth was surrounded by the celestial spheres, and everything was orbiting around the earth.
因此我们是整个宇宙的继承者，这是上帝赐予我们的礼物。
So we were the inheritors of the entire universe, and God had gifted us with this.
而后科学向我们揭示，实际上我们在宇宙中并非处于什么特殊位置。
And then science showed us that, in fact, we're not at a particularly special place in the universe.
这就是宇宙学原理——宇宙各处大致相同，我们只是其中一个毫不起眼的地方。
This is the cosmological principle, this idea that the universe is roughly the same at every single place, and we are just one of those particularly unspecial places.
不仅在宇宙学意义上我们毫无特殊之处，从生物学角度看我们也并不特别。
And not only are we unspecial in the cosmological sense, but biologically, we're nothing particularly special.
我们只是处于从细菌到蟑螂，再到狗和黑猩猩的连续谱系上。
We're just on the continuum between bacterias to cockroaches through to dogs and chimpanzees.
我非常喜欢的天体物理学家尼尔·德格拉斯·泰森曾谈到，黑猩猩比我们想象的要聪明得多，它们可能思考着各种事情，而我们并没有比它们强多少。
An astrophysicist I absolutely love on almost every other topic, Neil deGrasse Tyson, was talking about how chimpanzees are a lot smarter than what we think, and chimpanzees might be thinking about all sorts of stuff, and we're just not that much better.
这几乎是所有人的共识。
So this is what almost everyone thinks.
但现在我们很多人正在推广的第三种观点是：黑猩猩与我们之间并非仅是微小的量变差异。
But this third view that a lot of us are trying to promote now is that it's not a slight quantitative difference between chimpanzees and us.
虽然存在从细菌到蟑螂再到狗和黑猩猩的连续谱系，但我们却偏离了这个轴线。
There is a continuum between bacteria to cockroaches to dogs and chimpanzees, but we're off axis.
我们是质的不同。
We are qualitatively different.
你只需要睁开眼睛。
And all you need to do is open your eyes.
你望向窗外，看着那座恰好在那里的美丽城市。
You look out your window and you look at that beautiful city that happens to be out there.
这无法用生物复杂性的逐渐增加来解释。
That cannot be explained by this gradual increase of biological complexity.
通用人工智能团队也完全误解了我们。
The artificial general intelligence crew gets us completely wrong too.
他们以为只要增加计算能力就能获得智能，而我们实际上并不清楚底层是什么让我们具有创造力并能提出好的解释。
Just add more compute power and you'll get intelligence when we don't really know what it is underneath that makes us creative and allows us to come with good explanations.
人们经常谈论OpenAI推出的文本匹配引擎GPT-3，这是一款非常令人印象深刻的软件。
People talk a lot about GPT three, the text matching engine that OpenAI put out, which is a very impressive piece of software.
但他们会说，嘿，我可以用GPT-3生成很棒的推文。
But they say, hey, I can use GPT three to generate great tweet.
这首先是因为作为人类，你从它生成的所有垃圾中筛选出哪些推文是好的。
Well, that's because first, as a human, you're selecting which tweets out of all the garbage that it generates are good.
其次，它通过某种抄袭和同义词匹配等组合来生成听起来合理的内容。
Second, it's using some combination of plagiarism and synonym matching and so on to come up with plausible sounding stuff.
但最容易看出它生成的内容实际上毫无意义的方法，就是问它一个后续问题。
But the easiest way to see that what's generating doesn't actually make any sense is just ask it a follow-up question.
拿一个GPT-3生成的输出，问问它为什么。
Take a GPT three generated output and ask it why.
为什么会是这样？
Why is that the case?
或者基于此做出预测，然后看着它彻底崩溃，因为缺乏根本的解释。
Or make a prediction based on that and watch it completely fall apart because there's no underlying explanation.
它只是在鹦鹉学舌。
It's parroting.
这是绝妙的贝叶斯推理。
It's a brilliant Bayesian reasoning.
它基于网络上人类已生成的内容进行模仿，但缺乏能通过未观察到的因素来解释场景的现实底层模型。
It's dating from what it already sees out there generated by humans on the web, but it doesn't have an underlying model of reality that can explain the scene in terms of the unseen.
我认为这至关重要。
And I think that's critical.
这正是人类独有的能力——没有其他生物、计算机或我们遇到过的任何生物/人工智能能做到这一点。
That is what humans do uniquely that no other creature, no other computer, no other intelligence, biological or artificial that we have ever encountered does.
不仅这是我们的独有能力，如果我们遇到同样能产生这种合理解释的外星物种，他们提出的任何解释我们都能理解。
And not only do we do it uniquely, but if we were to meet an alien species that also had the power to generate these good explanations, there is no explanation that they could generate that we could not understand.
我们的理解能力是无限的。
We are maximally capable of understanding.
在这个物理现实中，不存在人类在给予足够时间、资源和教育后仍无法理解的概念。
There is no concept out there that is possible in this physical reality that a human being given sufficient time, resources, and education could not understand.
他们是科学思维型的人。
They're scientifically minded types.
这令人震惊。
It's astonishing.
那些人说我们或许无法理解下一套物理定律。
Who say perhaps we won't be able to understand the next set of laws of physics.
也许我们无法理解外星人。
Perhaps we won't be able to understand the aliens.
这不过是对超自然的诉求。
It's nothing but the appeal to the supernatural.
从逻辑上讲，这等同于上帝存在而我们无法理解上帝的本质。
It's logically equivalent to God's out there and you can't possibly understand what God is.
上帝是超越我们存在的全知全能者。
God is this infinite omniscient being that is beyond us.
如果你愿意，你可以相信这一点。
You can believe that if you like.
你可以相信模拟假说。
You can believe the simulation hypothesis.
你可以相信其中任何一种说法。
You can believe any one of these things.
这些都是关于我们无法触及的现实的形而上学主张。
They're all metaphysical claims about a reality that we have no access to.
无论你是否想引入那些拥有我们无法理解思想的外星人，这些说法都站在相同的基础上。
And whether or not you want to introduce aliens who will have ideas that we can't comprehend, it's all standing on the same footing.
至少关于上帝的形而上学，你可以说，好吧。
At least the god metaphysics, you could say, okay.
那是在我们物理法则之外的另一个宇宙。
That's in a different universe that's outside of our laws of physics.
但外星人按理应遵循相同的物理法则，所以我甚至不明白这种说法的依据是什么。
But the aliens presumably would be under the same laws of physics, so I don't even see what the basis for that is.
任何智慧到能离开母星的物种都明白，限制因素在于思想。
Any species that is smart enough to get off its home planet knows that the limiting factor is ideas.
因此他们最应该从遇到的任何其他物种那里获取的，就是新思想。
So the thing that they should want the most from any other species they encounter is new ideas.
而他们应该进行的交易，就是思想交流。
And the trade that they should be making is the trade of ideas.
科幻界有种马尔萨斯哲学叫黑暗森林假说，认为每个文明都像细菌，我们会耗尽生存空间。
There's this Malthusian philosophy in science fiction now called the dark forest hypothesis that every human species like bacteria and we're gonna run out of room.
不。
No.
宇宙的规模是无限的。
The universe is infinite in size.
它还在膨胀。
It's expanding.
多元宇宙的规模更是无限广阔。
The multiverse is even more infinite in size.
我们正处在无限的开端。
We are at the beginning of infinity.
我们不会耗尽资源。
We're not running out of resources.
所有人都在渴求思想。
Everybody's craving ideas.
智慧的外星文明会交换思想，成功的文明也进行思想交易，因为这些思想能将原本无用的东西转化为资源。
Smart alien civilizations trade ideas, and successful civilizations trade ideas because those ideas take things that were useless before and turn them into resources.
每个外星文明都能与其他文明交流思想，因为这些都是普适的解释者。
And every alien civilization can trade ideas with every other civilization ideas because they're all universal explainers.
它们具备最大限度的理解能力。
They're capable of maximal understanding.
事实上，最令人震撼的是你的思维不会被震撼——
In fact, the mind blowing thing here is that your mind cannot be blown.
只要给予时间和努力，没有哪种思想是你的心智无法吸收的。
There's no idea out there that your mind cannot absorb given the time and the effort.
所以如果我们遇到外星物种，或许应该感到欣喜。
So if we encounter an alien species, we should probably rejoice.
除了我们的思想，他们可能对我们的星球别无所求。
They probably don't want anything from our planet other than our ideas.
而交流思想的最佳方式，就是建立一个充满活力、富足繁荣的文明。
And the best way to trade ideas is to have a dynamic, abundant, thriving civilization.
由于我从小接触程式化的科幻作品，曾对外星接触持悲观态度。
Because I grew up on rote sci fi, I used to be pessimistic about alien encounters.
哦，是啊。
Oh, yeah.
要是遇到外星人，他们只会毁灭我们——
If we encountered aliens, they'll just destroy us.
就像《银河系漫游指南》里，沃贡人为了建造超空间通道就随意摧毁了地球。
Like in Hitchhiker's Guide to the Galaxy, the Vogons thoughtlessly demolished the Earth to make room for a hyperspace bypass.
但现实是，任何发现我们的物种都会立即分享他们所有的知识，同时渴望获取我们的新知识——因为他们会意识到，这将帮助他们点亮暗物质、暗能量这些宇宙未开发资源，让他们自身也得以繁荣发展。
But the reality of it is that any species that finds us is going to immediately give us all the knowledge that they have, and they're gonna be craving new knowledge that we have because they will realize that that would allow them to light up the dark matter, the dark energy, the unused resources in the universe to have themselves thrive as well.
既然谈到外星人，我们就简单聊聊费米悖论。
Let's talk briefly about the Fermi Paradox since we're talking about aliens.
为不了解的听众介绍一下，恩里科·费米是参与曼哈顿计划的著名物理学家，他曾提出：外星人在哪里？
For those of listeners who don't know, Enrico Fermi was a famous physicist part of the Manhattan Project, and he said, where are the aliens?
宇宙如此浩瀚，很可能存在无数能够支持某种生命形式的行星。
Universe is so large, there's probably so many planets that are capable of supporting life of some kind or another.
难道我们到现在还没发现它们吗？
Shouldn't we have seen them by now?
几乎每颗恒星周围都存在类似我们太阳系的行星系统。
Around almost every star, there is a contingent of planets much like our own solar system.
而像银河系这样的典型星系中，恒星数量约为2000亿颗，最高估计可达4000亿颗。
And the number of stars that exists within a typical galaxy like the Milky Way is something like 200,000,000,000, although the estimates go up to about 400.
我们可观测到的星系数量大约在2000亿到3000亿之间，但可观测宇宙只是整个宇宙的一小部分。
And the number of galaxies that we can see is around 200 to 300,000,000,000, but the observable universe is just a small fraction of the entire universe.
这意味着行星的数量绝对令人震惊，简直是天文数字。
That means that the number of planets is absolutely astonishing, astronomical.
根据这些数字，宇宙中不仅应该存在适合生命的行星，更该充斥着比我们更先进、更落后或发展程度相近的文明。
Surely, given these numbers, it has to be the case that there are not only planets out there that are suitable for life, but the universe should be teeming with civilizations far more advanced than ours, less advanced than ours, and some that are similar in advancement to ours.
那么它们在哪里呢？
So where are they?
这是一种观点，但在面对不确定性时我们必须保持谦逊。
Now, that's one argument, and we have to be humble in the face of uncertainty here.
没有人知道答案。
No one knows.
但我想提出一个鲜少被讨论的观点。
But I wanna give an argument that rarely gets any airtime.
这个观点认为我们是孤独的，且与天文学毫无关系。
The argument is that we are alone, and the argument has nothing to do with astronomy.
它与生物学息息相关。
It has everything to do with biology.
这个观点是这样的。
The argument goes like this.
看看地球上的物种数量——不仅包括现存的上百万种，还包括曾在地球上存在过的数亿物种。
Look at planet Earth and look at the number of species, not only that exist right now, millions of them, but the number of species that have ever existed on planet Earth, hundreds and millions.
生命约在35亿年前诞生，在随后约25亿年里——也就是地球生命史的大部分时期——除了细菌别无他物。
When life arose something like three and a half billion years ago, for about two and a half billion years, for most of the history of life on Earth, there was nothing but bacteria.
显然生命缺乏快速进化超越细菌的内在动力。
So life apparently doesn't have much impetus to evolve quickly beyond bacteria.
它只是尽可能保持简单形态。
It just remains as simple as possible.
许多人误解了达尔文真正推翻的观点——即进化具有既定方向。
A lot of people have this misconceived idea that Darwin really did away with, the idea that evolution has a direction in mind.
你看到高中教科书里那些进化示意图：猴子最初四肢着地蹒跚而行，弓着背，最终却直立起来提着公文包——仿佛这就是进化的目标。
You see these pictures of evolution that appear in high school textbooks of the monkey that's hobbling around on all fours and he's hunched over, then eventually he's standing up and holding a briefcase, as if this is what evolution had in mind.
这不过是事后回顾时产生的错觉。
It only seems to be what evolution had in mind in retrospect by looking backwards.
美国学者查理·莱恩威弗称之为'人猿星球假说'——仿佛移除了人类后，猿类就会自然进化填补智慧生态位。
This American academic, his name is Charlie Lineweaver, and he calls this the planet of the apes hypothesis, as if if you remove the humans from a planet, the apes would naturally evolve to fill the intelligence niche.
他说，你可以想象另一种情景：作为一头能自我思考的大象，你反思自己鼻子的长度，回顾生物进化历程，却发现象鼻变得越来越短。
And he said, you can imagine another situation where you're an elephant that is able to think about themselves, and they reflect on the length of their trunk, and they look back through biological evolution, and they see that trunks get ever shorter.
于是它们得出结论：啊，进化一直在致力于让象鼻变得更长。
So what they conclude is, ah, evolution has been geared towards making ever longer trunks.
这就是进化的全部意义。
That's what evolution is all about.
当然，我们知道这很荒谬。
Of course, we can see that that's ridiculous.
只是碰巧这种名为大象的生物进化出了长鼻子。
It just happens to be the case that this creature called the elephant has evolved and it's got this long trunk.
但象鼻长度似乎并非我们所说的进化趋同特征。
But length of trunk doesn't appear to be a convergent feature of evolution, so we say.
进化趋同特征是指生物体内反复独立出现的特征。
A convergent feature of evolution is a feature that exists within biological entities, which has arisen again and again independently.
翅膀是我最喜欢的例子。
Wings is my favorite example.
鱼类拥有某种形式的翅膀。
Fish have wings of certain kind.
比如飞鱼。
There's flying fish.
蝴蝶也有翅膀，昆虫界同样存在。
Butterflies have wings, so we've got them in insects.
哺乳动物中也进化出了翅膀，比如狐蝠和某些袋貂。
They arose in mammals as well with flying foxes and certain kinds of possums.
当然，鸟类和恐龙也拥有翅膀。
And, of course, birds and dinosaurs had wings as well.
因此，在这些物种中，翅膀是独立演化出现的。
So independently in all these species, the wings keep on arising.
眼睛如此，发声器官亦是如此。
So do eyes, so do organs for sound.
但现在让我们思考一下进行数学运算或建造射电望远镜的能力。
But now let's think about the capacity to do mathematics or to build radio telescopes.
换句话说，成为一个具有智慧创造力的物种。
In other words, to be an intelligent creative species.
在地球的地质历史中，这种情况出现过多少次？
How many times has that arisen on geological history of the earth?
仅在一个物种中，且独一无二。
In one species and one species alone.
我们能否据此得出结论，认为智慧物种的出现是必然的？
Can we conclude on that basis that therefore it's inevitable that intelligent species will arise?
如果你在宇宙中所有适宜生命的行星上撒播细菌来重复这个实验，是否就必然会产生像我们这样的智慧生命？
If you were to repeat the experiment by sprinkling a little bit of bacteria around all the bio friendly planets that exist throughout the universe, would you be guaranteed to get an entity like us?
还有一种思考方式会让那些相信外星人存在并终将造访地球的人感到数学上的恐惧。
Here's another way to think about it that is mathematically frightening for the people who think that the aliens are out there and they're going to visit us at some time in the future.
我们之前讨论过已知宇宙中存在数万亿颗可能适宜生命诞生的行星。
We were talking earlier about trillions of planets that exist throughout the known universe that might even be friendly for life to arise.
假设在我们这样的智慧人类与所能想象的最简单细菌之间，仅存在100个独立的进化步骤。
Imagine that between us as intelligent human beings and the most simple form of bacteria that we can imagine, there are only 100 independent evolutionary steps.
这不是真的。
Now that's not true.
很可能需要发生上百万次甚至更多有利的突变，才能让任何生物存活至今，使我们得以存在。
It's probably a million or more different mutations that had to happen and were favorable, allow any organism to survive such that we exist today.
但就算只算100次。
But just make it only a 100.
假设这些独立的步骤每一步发生的概率只有十分之一。
And imagine that each of those independent steps had a probability of just one in ten of happening.
实际上，概率可能更接近百万分之一，但我们姑且慷慨一点。
Now, fact, it's probably more like one in a million, but we'll be generous.
我们就说是十分之一吧。
We'll say one in 10.
现在我们得到的是一个概率链。
So now what we have is a chain of probability.
十分之一乘以十分之一乘以十分之一，重复100次。
One in 10 times one in 10 times one in 10 a 100 times.
如果你懂数学，就会明白这是十分之一的100次方，也就是1后面跟着100个零分之一。
And if you know how to do mathematics, you will realise that this is one over 10 all to the power of 100, which is one over one followed by a 100 zeros.
这个数字远超我之前提到的行星数量那种天文数字。
That number swamps the astronomical number I was talking about with planets earlier on.
换句话说，我们基于这个特定论点产生的概率微乎其微。
In other words, the probability of us arising on this particular argument is infinitesimally small.
它竟然发生过一次这个事实，应该让我们感到震撼。
The fact that it's happened once should blow our minds.
这些都是不确定的假设。
These are all uncertain hypotheses.
但我们也要记住，关于自然选择进化，我们还有很多未知之处。
But we also have to keep in mind that there's so much about evolution by natural selection we don't know.
大卫·多伊奇有句俏皮话。
David Deutsch has this little quip.
如果你无法编程实现它，说明你并不真正理解它。
If you can't program it, you don't understand it.
这意味着在通用人工智能（AGI）的案例中，我们无法编程实现AGI。
Which means in the case of AGI, we can't program AGI.
这说明我们并不真正理解我们所认为的通用智能这个概念。
That means we don't understand what this idea of general intelligence that we have is.
同样的情况也适用于自然选择进化。
And the same happens to be true of evolution by natural selection.
虽然存在所谓的进化算法，但这并不是对自然选择进化的编程实现。
There are these things called evolutionary algorithms, but this is not programming evolution by natural selection.
我们无法在计算机中创建这样的人工实体：当它们受到真实环境压力时，能够朝着日益复杂的方向进化。
This is not being able to create artificial entities inside of a computer that when subject to actual environmental pressures are able to evolve towards this increasing complexity.
我们仍然面临这个问题：DNA在大约25亿年的时间里（地球生命历史中的绝大部分时期）究竟在做什么？
We still have this problem of what DNA was doing for that approximately two and a half billion years, the overwhelming majority of the history of life on Earth.
为什么在那段漫长岁月里它完全没有进化？
Why didn't it evolve at all during that time?
到底发生了什么？
What's going on?
沃德和布朗利合著了一本精彩的书《稀有地球》，书中探讨了地球进化史上所有奇特而古怪的事件。
There's a wonderful book called Rare Earth by Ward and Brownlee, and these guys talk about all the weird, quirky things that happened in the evolutionary history of Earth.
我只是注意到一个事实：我们这些能解释宇宙的智慧生命，其进化过程看似偶然，且仅此一次。
I just picked on the fact that we, universal explainers, evolved seemingly fortuitously, seemingly once.
但回溯历史你会发现，从单细胞细菌进化到多细胞生物本就非常奇特罕见，至今无法在实验室环境中复现。
But you can go back and realise that evolving from single cell bacteria to a multicellular organism was weird and unusual and hasn't been able to be repeated in the laboratory setting.
再从多细胞生物进化到类似植物的生物，再到类似动物的生物。
And then to go from the multicellular organism to something that's like a plant and then something that's like an animal.
这些进化节点似乎都源于我们尚未理解的偶然因素。
Each of these things seems to have occurred for chance reasons that we don't understand.
我认为可能是多种因素共同作用的结果。
I think there could be a combination of things going on.
你的论点可以基于统计学而非绝对性。
Your argument can be statistical rather than absolute.
我们在宇宙中或许并不孤独，但能成为宇宙解释者的文明可能极其稀少，再乘以浩瀚的星际距离...
We may not be alone in the universe, but to becoming universe explainers might be so rare that when you start multiplying that by interstellar distances, which are quite vast.
而且我认为费米还做了个不合理假设——外星文明能突破光速限制，可我们连这种可能性的理论雏形都没有。
And I think Fermi also had the unreasonable assumption that interstellar aliens would figure out how to get past the speed of light, when we have no hypothesis whatsoever as to how that might be possible.
在突破光速限制这个领域，我们甚至没有任何模糊的理论框架。
We have nothing even vaguely in the category of how to get past the speed of light.
所以如果受限于光速，而成为宇宙解释者的文明又极其稀少，那我们可能只是相距太远了。
So if you're limited by the speed of light and if the jump to universal explainers is rare, then we might just be too far apart.
这个过程可能需要更漫长的时间。
And it might just take a lot longer.
宇宙非常浩瀚，但至少在行星和恒星方面，它几乎完全是空的。
The universe is very big, but it's also, at least as far as planets and stars are concerned, almost entirely empty.
即便如此，说人类和类似人类的解释者相当罕见仍然是相当合理的。
Given that, it's still quite reasonable to say that, yeah, humans and human like explainers are quite rare.
我们在宇宙中仍处于文明形成的早期阶段，彼此被难以置信的遥远距离分隔，以至于尚未相遇。
We're still early in their formation across the universe and they're just spread out by such incredibly vast distances that we haven't encountered each other.
如果我们真的相遇了，我想我们会知道的。
And if we did encounter each other, I think we'd know.
例如，当外星飞船到达这里时，它们的无线电波早就已经抵达了。
For example, by the time an alien spacecraft got here, their radio waves would have arrived long before.
因为在文明发展史上，有一段相当长的时期是先发明无线电并开始向外广播无线电波，之后才发明星际旅行技术并向宇宙发送火箭和文明。
Because there's a pretty long period in a civilization's history where it invents radio and starts broadcasting radio waves out before it invents interstellar travel and sending rockets and civilizations around the universe.
我记得斯蒂芬·霍金本人说过，向宇宙广播无线电波是个错误，因为外星人就在那里，他们会像征服者一样，想要为了资源和各种其他目的占领我们的星球。
I think Stephen Hawking himself said that it was a mistake to broadcast radio waves out into the universe because the aliens are gonna be out there, and they're gonna be like conquistadors, and they're gonna wanna take over our planet for their resources and various other things.
对于邪恶外星人来袭的想法，可以有几种回应方式。
There's a couple of responses you can have to the idea of evil aliens coming to get us.
第一种观点是：要向着无限未来进步，获得穿越银河的技术，唯一途径就是拥有波普尔所倡导的那种知识观——即能够自由探索思想空间，证伪假设，没有中央集权机构和对人民使用暴力，因为这些会抑制创造力。
The first of which is the only way to make progress off into the infinite future, to have the technologies that would enable you to traverse the galaxy, is to have this vision of knowledge that Popper had, namely that you are freely able to explore the space of ideas, able to falsify assumptions, and to not have central centralized authorities and force being used on people, which dampens down creativity.
要建立一个最具创造力的社会，必须拥有自由和解放，因此你将得到一个非暴力的社会。
To have a maximally creative society, you have to have freedom, you have to have liberty, and therefore you will have a nonviolent society.
你会拥有一个将创造力本身视为终极价值的社会。
You'll have a society which values creativity as an end in itself.
当我们遇到外星人时，不该预期他们是想要掠夺资源的道德败类，而应该预期相反的情况。
When we encounter the aliens, we should expect not that they're going to be immoral bastards that are gonna wanna take over our resources, but the opposite.
他们会看着我们，认为我们是多么原始的野蛮人。
They're going to look at us and think what primitive savages we are.
他们会觉得我们是道德侏儒，并且想要教导我们。
They're going to think that we're moral midgets, and they're gonna wanna teach us.
并不是说他们会想把我们关进监狱之类的。
Not They're gonna wanna put us in prison or anything like that.
因为知识是一个统一的整体，如果他们的物理学比我们先进得多——这使他们能够接近光速，或者利用某些奇特的广义相对论引力效应制造虫洞，从而以超光速穿越太空。
Because knowledge is a unified whole, if their physics is so much better than ours, which enables them to approach the speed of light or to use some weird general relativity gravity thing that creates a wormhole so they can get through space faster than the speed of light.
他们所有的科学领域都将遥遥领先。
All of their sciences are gonna be so much further ahead.
他们所有的知识体系都会更先进，包括数学、道德观和政治制度。
All of their knowledge is gonna be further ahead, their mathematics, their morality, their political institutions.
所以我们不必担心外星人。
So we don't have to worry about the aliens.
顺便说，我们也不用担心他们会掠夺我们的资源。
And by the way, we don't have to worry about their stealing our resources.
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他们不会说'啊，那里有个充满煤炭和水的星球'。
It's not like they're gonna go, ah, there's a planet full of coal and water.
我们要去占领它。
We're gonna take it.
不会的。
No.
他们将掌握从星际空间收集氢原子，将其转化为聚变反应堆，并通过3D打印制造任何所需技术的知识。
They're gonna have the knowledge to be able to sweep up the hydrogen in intergalactic space and turn that into a fusion reactor and use three d printing to create any technology that they want.
事实上，这可能是对费米悖论的另一种解释。
And in fact, that might be another answer to the Fermi Paradox.
他们无需离开本地区域，因为已有技术能在相对狭小的太空区域内完美维持生存。
They don't need to leave their local area because they've already got the technology to perfectly sustain them in a relatively small region of space.
是啊。
Yeah.
他们拥有戴森球。
They've got Dyson spheres.
他们能获取所需的所有能源。
They can gather all the energy they need.
他们能收集所有物质。
They can gather all the matter.
他们能创造任何想要的东西。
They can create anything they want.
还能在虚拟现实中体验任何想要的现实。
And they can have any reality in VR space that they want.
所以严格来说，他们唯一欠缺的就是尚未掌握的新知识。
So literally, the only thing that they would be lacking is new knowledge that they don't have.
这确实是他们唯一缺少的东西。
It's literally the only thing they would be lacking.
人类有征服史是因为我们争夺完全相同的资源。
Humans have a history of conquest because we fight for the same exact resources.
但即便在人类历史中，最早的探险者也是商人。
But even in human history, the first explorers were traders.
他们外出是为了寻找香料、黄金、丝绸、可驯化的新植物、新动物等等。
They were going out there to find spices, gold, silk, new plants to domesticate, new animals, etcetera.
他们外出并不一定是为了征服土地。
They weren't going out there necessarily to conquer land.
最终他们这样做了，因为当你被困在地球上时，就会面临资源有限的困境。
Eventually, they did because of the finite resource dilemma when you're stuck on Earth.
但一旦你掌握了离开地球的技术，资源有限的问题就消失了。
But the moment you had technology to get off of Earth, finite resources go away.
如果你想要某种资源，那就去找一颗中子星。
And if you want a resource, then you go find a neutron star.
去找一个恒星系统。
You go find a star system.
而不是去争夺一个小行星。
You don't go after a little planet.
宇宙中有无数开普勒行星，它们会更接近那些资源。
There's infinite Kepler planets out there that are gonna be much closer to them.
人们真正需要的是创意和贸易。
It's ideas and trade that people want.
如果你观察现代社会，尽管我知道这不是普遍观点，但随着文明进步，我们正变得不那么好战。
And if you look at modern society, even though I know this is not the common belief, we're becoming less warlike as we become more civilized.
原因在于你不再为了自然资源去征服俄罗斯。
And the reason is because you don't conquer Russia anymore for its natural resources.
你不会派出坦克，因为你试图掠夺所有自然资源。
You don't roll in the tanks because you're trying to grab all the natural resources.
当今世界上最富有的地方是那些拥有最佳创意的地方。
The wealthiest places in the world now are the ones that have the best ideas.
硅谷曾一度作为财富创造引擎位居榜首，因为它拥有最好的创意。
Silicon Valley was on top for a while as a wealth creation engine because it had the best ideas.
新的石油就是创意。
The new oil is ideas.
一切都是数字化的。
It's all digital.
所有新财富都在创意领域创造。
All the new fortunes are being created in idea space.
事实上，如果你今天作为一个有抱负的年轻人起步，你不会去学习房地产。
In fact, if you're starting out today as a young ambitious person, you don't learn real estate.
你不会去学习煤炭和石油开采。
You don't learn coal and oil mining.
你不会通过开采实体资源来创造财富。
You don't go into extraction of physical resources to create wealth.
你要进入创意领域。
You go into idea space.
你要投身编程、书籍、电影、博客和播客，以及建造机器人——这些本质上大多是知识产权。
You go into programming, books, movies, blogs, and podcasts, and building robots, which are mostly intellectual property underneath.
因此，即使作为人类文明，我们也在逐渐远离对实体资源的征服，更多地转向创意的交易。
So even as a human civilization, we're moving away from conquest of physical resources and moving much more into trading of ideas.
人类物种的悲观前景是，太多大国和民族国家认为他们已经实现了最大化的创意。
The downside scenario for the human species is that too much of our larger countries and nation states believe that they've achieved maximal ideas.
现在是时候节约资源了。
Now it's time to save resources.
他们最终摧毁了进步、纠错和创造的手段，最终陷入停滞。
They end up destroying the means of improvement, error correction, and creativity, and they end up stagnating.
然后你会看到创意来自一小部分城邦，而这些城邦不得不抵御更大规模、更具掠夺性的僵化国家。
Then you have the idea generation coming out of a much smaller set of city states, which then have to defend themselves against this larger mass of more predatory ossified states.
每次人们谈论中国多么令人印象深刻时，看看他们的火箭发射，看看他们的GDP，或者看看他们建造的城市。
Every time people talk about China being so impressive, look at their rocket launch, look at their GDP, or look at the city that they built.
等他们发明出新东西时再联系我。
Call me when they invent something new.
等他们提出我们从未有过的惊人创意，并开发出我们未曾拥有的技术时再联系我。
Call me when they come up with some incredible idea that we haven't had, and they build some technology that we haven't had.
因为到目前为止，一切都是模仿的。
Because so far, it's all imitative.
他们只是在利用从我们这里获取的技术，现在正在追赶。
It's all them taking advantage of technology that they've picked up from us that they're now catching up on.
他们只是应用规模优势，因为他们有更多人口。
They're just applying scale to it because they have more people.
但等他们的人均GDP超过我们时再联系我。
But call me when their GDP per citizen crosses hours.
等他们研发出我们不会制造的药物、疫苗、航天器、能源发生器或聚变反应堆时再联系我。
Call me when they come up with pharmaceuticals or vaccines or spacecraft or energy generators or fusion reactors that we do not know how to build.
等这个威权社会自上而下地创造出全新事物时再联系我——当他们的艺术更优秀、科学更先进、技术更卓越时，那才叫真正的创造力。
Call me when the authoritarian society figures out top down how to build something brand new, but it's more creative when their art is better, when their science is better, when their technology is better.
等民主自由资本主义社会出现这种情况时再告诉我，因为我从未见过这样的案例。
Call me when that happens over a democratic free capitalist society because I've never seen the case of that ever.
中国培养的理学学士和工程学士数量比世界上任何国家都多。
China keeps on graduating more bachelor of science and bachelor of engineers than anywhere else in the world.
我们落后于中国，因为他们的大学正在培养更多理科毕业生。
We're lagging behind China because their universities are pumping out more science graduates.
但他们培养的并不是更多的创新者。
They're not pumping out more innovators.
中国那些获得科学学位的大学毕业生，并不是都去攻读博士学位或从事创新工作。
It's not like the students that are coming out of those universities in China with their science degrees are going off and doing PhDs and doing innovative stuff.
恰恰相反。
Quite the opposite.
因为他们接受的是特定模式的训练——背诵教材、应对考试，实际上无法跳出框架思考。
Because they've been trained in a particular way, because they've been trained to memorise this textbook, respond to this exam, and they actually can't think outside of the box.
他们被灌输这就是真理。
They've been trained that this is what's true.
这是不容质疑的、正确的科学思维方式。
This is the unquestioned, correct way of thinking about science.
这种模式或许擅长模仿（正如我们所见的），但无法推动技术前沿发展，更不用说基础物理或其他领域了。
And that might be good for being able to imitate as we see, but it's not going to be the thing that enables you to push forward the frontier in technology, let alone fundamental physics or anywhere else.
所以我不在乎他们有多少理科毕业生的统计数据。
So I don't care what the statistics are on how many science graduates they've got.
这毫无意义。
That makes no difference.
我宁愿要10个富有创新精神、创造力强的年轻物理系毕业生，也不要5万个只会以100%效率通过考试的物理系毕业生。
Give me 10 innovative, creative, young physics graduates over 50,000 physics graduates that all are able to pass the exam with a 100% efficiency any day.
是啊。
Yeah.
一个爱因斯坦抵得上一群拥有物理学博士学位的庸才。
One Einstein is worth a legion of drones with PhDs in physics.
无所谓。
Doesn't matter.
创造力本质上就是从零到一的突破。
Creativity by its nature goes zero to one.
靠人海战术永远无法实现真正的创新。
And no amount of throwing bodies at the problem will get you there.
这就是模因进化的本质，也是创造力的本质。
That's just the nature of mimetic evolution and it's just the nature of creativity.
当今社会有许多机构都在依赖信誉背书。
There are a lot of institutions in our society today that are relying upon credibility stamps.
过去这些背书是你获得社会公信力的方式。
They used to be how you gain credibility in society.
比如你若是《纽约时报》或《华盛顿邮报》的记者，就自然拥有这两家媒体的公信力背书。
So if you were a journalist writing for The New York Times or Washington Post, then you had the masthead of The New York Times and Washington Post.
如果你是哈佛教授，你的公信力就来自哈佛教授这个头衔。
If you're a professor at Harvard, you have credibility because you're a professor at Harvard.
所以这些体系当然会被钻空子。
So of course those systems got hacked.
许多没有资格指导世界的社会科学家，现在却伪装成经济学家或自然科学家，带着他们荒谬的政治模型混迹其中。
A lot of social scientists who have no business telling the world what to do are now in there with their nonsense political models masquerading as economists or natural scientists.
还有一些活动人士，打着这些昔日大报的旗号发表文章，逐渐耗尽这些报纸多年来积累的公信力资本。
Or you have people who are activists writing under the mastheads of these formerly great newspapers and burning up the credibility capital that these newspapers have built up over time.
互联网正在缓慢而坚定地揭露他们，我们正处于转型期——大众仍相信这些机构，而我们却困在这个炮火点，这个为机构服务的协调点上。
The internet is exposing them slowly but steadily, and we're going through a transition phase where the masses still believe in the institutions and we're caught in this shelling point, this coordination point for the institutions.
我如何判断是否应该雇佣你？
How do I know if I should hire you?
你会有哈佛大学的文凭吗？
Will you have a diploma from Harvard?
我知道它已经不如从前了。
I know it's not as good as it used to be.
我知道现在哈佛人文学科的文凭可能毫无价值，但我没有其他可信的筛选标准，而且我需要高效地完成这件事。
I know Harvard humanities diploma is probably nonsense at this point, but I don't have any other credibility metric to filter you, and I need to do it in an efficient way.
我们正在见证权力从机构向个人的转移，但这个过程会非常混乱。
What we're seeing is the transition of power from institutions to individuals, but it's gonna be messy.
这需要几代人或至少一代人的时间。
It's gonna take a couple of generations or at least a generation.
与此同时，这些机构正在反击。
And in the meantime, the institutions are fighting back.
我们正处于'帝国反击战'阶段——他们试图控制Twitter、Facebook和Patreon等赋能个人的新平台。
We're in the empire Strikes Back phase where they're trying to take over the new platforms like Twitter, Facebook, and Patreon, which empower the individuals.
大学和整个学术界握有巨大权柄，因为他们能培养自己的下一代教师，而这些教师将继续教育中小学的下一代学生。
The university and all of academia has a very big stick in terms of being able to train their own next generation of teachers who then go on to teach the next generation of primary and secondary school students.
是啊。
Yeah.
这是一种祭司制度。
It's a priesthood.
你只能说出祭司们认可的内容，而且只有当你自己也是祭司时才能说这些话，而祭司们有权决定谁有资格成为祭司。
You're only allowed to say what the priests have approved, and you can only say that if you were yourself a priest, and the priests get to decide who's a priest.
创新需要几个条件。
Innovation requires a couple of things.
其中一个似乎需要的条件就是去中心化。
One of things that it seems to require is decentralization.
我不认为这是巧合：雅典城邦、意大利城邦，甚至是联邦政府控制较少、形式更自由的美国，都曾是创新的温床。
I don't think it's a coincidence that the Athenian city states, the Italian city states, or even The United States when it was more free form and less federal government control were hotbeds of innovation.
因为存在大量竞争，如果人们的想法不受欢迎，他们可以从一个州转移到另一个州，从而形成激烈的思想竞争。
Because you had lots and lots of competition, people could switch from one state to another if their ideas weren't welcome and there was a robust competition of ideas.
真正重要的多样性是思想的多样性，而不是肤色的多样性。
The real diversity that matters is diversity of ideas, not diversity of skin color.
你还需要一个前沿领域。
And you also need a frontier.
你需要探索新事物，无论是知识前沿还是物理前沿。
You need something new to explore, either an intellectual frontier or physical frontier.
我们已经占据了加利福尼亚。
We've occupied California.
如果说有什么变化的话，现在的加州已成为体制，是既得利益集团，不再是狂野西部的边疆了。
If anything, now California is the institution, the establishment, no longer the front of the Wild West.
也许我们需要一个在太空中的。
Maybe we need one in space.
也许我们需要像加密货币那样的知识型人才。
Maybe we need intellectual ones like we have in cryptocurrencies.
而这就是西部荒野的本质——总是充斥着骗子。
And it's the nature of Wild West that they're always filled with scammers.
那里总是犯罪横行。
They're always filled with crimes.
那里总是充满各种离奇怪诞的事物，因为它们往往吸引着古怪的人群，但同时也是许多创新发生的地方。
They're always filled with very strange and odd things because they tend to attract a weird crowd, but at the same time it is where a lot of the innovation is going on.
我看到许多传统科学家和企业家在哀叹。
I see a lot of lamenting from old school scientists and entrepreneurs.
新创业者在哪里会受到欢迎？
Where are the new entrepreneurs welcome?
我记得前几天保罗·格雷厄姆在推特上提到过这个。
I think Paul Graham tweeted this the other day.
他是Y Combinator的创始人，非常杰出的人物。
He's the Y Combinator founder, brilliant guy.
他说了些类似'今天的史蒂夫·乔布斯可能无法在硅谷公司找到工作或生存'的话。
He said something along the lines of Steve Jobs today wouldn't be able to get a job or wouldn't be able to survive at a Silicon Valley company.
他会被自己的团队抵制。
He'd be canceled by his own team.
但今天的史蒂夫·乔布斯会投身加密领域。
But Steve Jobs today would be in crypto.
他本该混迹于加密货币圈，与骗子、罪犯和怪人为伍，但至少在那里，他能有个做怪人的空间。
He'd be in crypto with all the scammers and all criminals and all the weirdos, but at least there, he'd have a space to be weird.
他能有个与众不同的容身之处。
He'd have a place to be different.
他能有个尝试新事物的地方，而不必时刻向他人交代。
He'd have a place to try new things without having to constantly answer to someone.
中心化与去中心化之间存在着钟摆效应。
There's a pendulum between centralization and decentralization.
比如在加密货币领域，中心化金融最终会变得极其僵化。
For example, if you look in the crypto world, centralized finance ends up very ossified.
政府和监管机构会严格规定你能做什么、不能做什么。
You have the government and the regulators telling you exactly what you can and can't do.
监管俘获现象随之而来，转眼间华尔街就从经济中抽走20%的利润——而加密货币可以取代这种模式。
You get regulatory capture, next thing you know, Wall Street is sucking 20% of the profits out of the economy, and crypto can replace that.
于是去中心化的压力出现了，人们可以用自由编程的方式实现它。
So you get decentralization pressure where people can do it in a free form programmatic way.
但随之而来的是更多的骗局、欺诈和损失。
But then you end up with a lot more scams and fraud and losses as well.
古时候，人们担心森林里的强盗土匪，于是求助于国王。
In the old times, you worry about brigands and robbers in the forest, so you appeal to the king.
国王建起了漂亮的城堡，铸造钱币，但转眼间就开始货币贬值，把百姓投入大牢。
Well, the king builds a nice keep, the king mints the money, but next thing you know the king is debasing the currency and the king is throwing people in jail.
于是有些人逃进森林重新当起强盗——因为他们渴望自由。
Then some people run off into the forest and they become brigands again because they want their freedom.
但现在，他们当然会受到同行的攻击和骚扰。
But now of course, they're subject to attacks and harassment from their peers.
历史上，集权与分权之间自然存在着钟摆式的摇摆。
So there's natural pendulum swing that goes on in history between centralization and decentralization.
我认为过去十年间，技术的发展轨迹实际上将我们推向了集权化。
And I think the arc of technology actually swung us towards centralization in the last decade.
我是亚马逊的忠实粉丝，但它是一个非常集权化的实体。
I'm a big fan of Amazon, but it's a very centralized entity.
即使在那个行业，也正在发生着一场分权化的变革。
There's a decentralization arc that is taking place even in that industry.
像Shopify这样的平台正在崛起，使小商店能够参与竞争，还有像DoorDash这样的本地配送服务。
Things like Shopify that are coming up and enabling small stores to compete or even local delivery services like DoorDash.
它们虽然是集中式服务，但正让一支由餐厅和本地商店组成的分散化大军能够与集中式服务竞争。
They're centralized services, but they're allowing a decentralized army of restaurants and local shops to compete against centralized services.
所以我们看到这种趋势在来回摆动。
So we're see this arc going back and forth.
这种质疑那些在特定领域数千年来被认为无可争议的事物的理念。
This idea of questioning things that hitherto you thought were unassailable in a particular domain for millennia.
人们一直在思考如何最好地理解民主的本质。
People were wondering about the best way to conceive of what democracy is.
甚至柏拉图也曾思考什么是民主，并对谁应该统治提出了疑问。
Even Plato had this idea of what is democracy, and he had the question about who should rule.
这大概就是民主的全部理念所在。
That's the whole idea of democracy supposedly.
我们得确定应该由谁来统治。
We'd have to figure out who should rule.
应该是哲学家国王来统治吗？
Should it be the philosopher kings who should rule?
还是应该由全体公民来决定？
Should it be the population of citizens?
他认为暴民会轻易投票剥夺少数群体的权利。
And he decided that a mob would readily vote away the rights of a minority.
这就是他对民主的理解。
That's what he thought democracy was.
但波普尔质疑这种探究民主本质的思维方式。
But Popper questioned this whole idea of looking at what democracy was.
他更深入地指出，民主与应该由谁统治毫无关系。
He went even deeper and said, democracy has got nothing to do with who should rule.
民主是一种能让你最有效、非暴力地废除政策和统治者的制度——这才是评判不同民主体系的标准。
Democracy is the system which allows you to remove policies and rulers most efficiently without violence, and that's how you judge different democratic systems.
因此你实际上可以评判法国、英国、美国和加拿大。
So you can actually make a judgment on France, England, The United States, Canada.
这些地方的民主制度各有优劣。
These places have better or worse kinds of democracy.
我们或许都称之为民主，但衡量标准在于能否快速、高效、和平地清除民主体系中我们不满的人。
We might all call them democracy, but to the extent that we're actually able to get rid of the people that we don't like from the democratic system quickly, efficiently, easily without violence.
这才是优良民主制度的衡量标准，而非纠结哪种制度能产生最英明的统治者。
That's the measure of a good democratic system rather than trying to figure out which system's going to give us the best rulers.
这种说法就像在问：科学方法中哪一种能带给我们真正的理论？
That's the same mistake as saying, what method of science is going to give us the true theory?
没有任何科学方法能带给我们真正的理论。
No method of science is going to give us the true theory.
科学是一种纠错机制。
Science is an error correcting mechanism.
我们所能期望的只是剔除那些糟糕的想法。
All we can hope for is to get rid of the bad ideas.
通过这样做，我们纠正了一些错误，然后才能继续前进，找到比之前更好的理论。
And by doing that, we've corrected some of our errors, and then we can move forward to find something that's a better theory than what we had before.
这实际上引出了一个问题：当你与他人意见相左时，如何做出好的决策。
Which actually raises the idea of how to make good decisions when you're at loggerheads with someone else.
有人认为妥协是某种美德，其实并非如此。
This idea that compromise is supposed to be a virtue of some kind, and it's not.
如果两个人无论如何都无法达成一致，可能会引发某种冲突，那么妥协总比暴力对抗要好。
It's preferable to having a violent confrontation if you've got two people who otherwise can't possibly reach an agreement, and they're gonna get into a battle of some sort.
但如果你处于这样一种情况：A有X想法，B有Y想法，通常理解的妥协就是介于X和Y之间的某个点。
But if you're in a situation where a person A has idea X and person B has idea Y, the common understanding of what a compromise is is it's somewhere between x and y.
A不会得到他们想要的一切，B也不会得到他们想要的一切。
Person a won't get everything they want, and person b won't get everything they want.
所以让我们达成一个妥协方案吧。
So let's come up with a compromise.
这就是Z理论。
This is theory zed.
当政策被证明无效时，我们不应感到惊讶，因为无论是A还是B，从一开始就没人认为这是个好主意。
When that policy proves not to work, we shouldn't be surprised because neither person a or person b actually ever thought it was the best idea in the first place at all.
他们认为X或Y才是正确的方案。
They thought that X or Y was the correct idea.
所以当他们实施Z方案时，一旦失败，结果就是无人从中吸取教训。
So when they implement Zed, what happens when it fails is that no one learns anything.
A会回头说：我早就说过X才是正确的方案。
Person A goes back to saying, I always told you that X was the correct idea.
而B则会坚持说：我一直认为Y方案才是最佳选择。
And person B goes back to saying, I always told you that idea Y was the best idea.
因此他们根本没有任何实质进展。
So they haven't made any progress whatsoever.
他们证明了Z是错误的，但最初就没人认为Z是正确的。
They've shown that Z is wrong, but no one ever thought that Z was correct in the first place.
这就是妥协的贫瘠之处，也是科学领域某些时候会出现的现象。
So this is the poverty of compromise, and this is what you get in science at certain times.
这种现象在政治领域也随处可见。
It's everywhere in politics as well.
马克·安德森对此有个精妙的总结：坚定主张，松散持有。
Marc Andreessen summarizes this nicely as strong opinions loosely held.
所以作为一个追求真理的社会，你应当持有坚定主张，但要保持灵活态度。
So as a society, if you're truth seeking, you wanna have strong opinions but very loosely held.
你需要尝试这些主张，验证其有效性，若行不通就及时纠错。
You wanna try them, see if they work, and then error correct if they don't.
但我们实际得到的要么是固执己见的强硬派（这是不宽容的少数群体），要么是摇摆不定的软弱派（这是妥协模式——无人担责、无人受赏、无人能按自己意愿尝试，最后大家只能推脱说'真正的共产主义还没实践过'）。
But instead what we get is either strong opinions strongly held, which is the intolerant minority, or we get weak opinions loosely held, which is the compromise model where no one really takes blame, no one gets credit, no one gets to try it the way that they want to, and everybody can then fall back on real communism hasn't been tried.
不过话说回来，真正的共产主义确实实践过了。
Although in that case, real communism has been tried.
只是效果不太理想。
It just hasn't worked out well.
插句题外话，我常听到一种批判说'我们需要进入后资本主义时代'。
As a digression, one of the common critiques that I hear people say, we need to move to a post capitalist world.
资本主义行不通了。
Capitalism isn't working.
好吧。
Okay.
那么你的替代方案是什么？
Well, what is your alternative?
通常这时人们就开始支吾其词，因为确实没多少选择。
And usually this is where people start fumbling because there aren't a lot of choices.
当你试图分配荣誉、分配资源并给予劳动回报时，本质上只有两种选择：
When you're trying to figure out how to divvy up credit, divvy up resources, and reward people for their work, you essentially have two choices.
要么接受现实自由市场的反馈——最佳模式就是货币体系；
Feedback from free markets in reality, and the best model for that is money.
要么接受人为反馈——这就是共产主义的归宿，由一群人判定谁工作最出色。
Or you have feedback from people, which is where communism ends up, which is a group of people decide that you did the best work.
那么谁来判定谁工作最出色呢？
Now who decides you did the best work?
总得有人负责做这件事。
Someone has to be in charge of doing that.
无一例外，最终都是由最强势的恶霸来掌控。
Invariably, that ends up being the biggest thug.
所以我认为每个共产主义国家都沦为独裁政权并非偶然。
So I don't think it's an accident that every communist country degenerates into a dictatorship.
共产主义似乎从未真正由人民大众共同管理。
Communism never seems to actually be run by distributed majority of the people.
最终总是由一群掌权者在操控。
It always ends up being run by a bunch of people who are taking charge.
因为人性使然——如果由我来决定黄金归谁，那肯定会分给我的朋友、家人和我喜欢的人。
Because it's just human nature that if I get to decide who gets the gold, it's going to go to my friends, family, and the people that I like.
而这正是最终必然发生的结果。
And that's invariably what ends up happening.
要么你需要一个客观分配机制——金钱就是已知的客观标准，要么就会完全变成主观分配。
Either you need an objective function to carve it up, and money is the known objective function, or it becomes all subjective.
如果是主观分配，凭什么由你而不是我来决定分配？
And if it's subjective, then who's to say you carving it up instead of me?
那我们只能靠谁武力更强、谁枪更多来决定了。
We're just going to decide based on who has more physical force, who has more guns.
我们自由市场派的主张是：我们已经从这种决策过程中剔除了强制因素。
What we say on the side of free markets is that what we've extracted out of that decision making process is the coercion.
没有人是被迫购买服务或签订协议的。
No one is forced into purchasing a service, undertaking an agreement.
唯一动用武力的时候就是政府介入的时候。
The only time that force is applied is when the government gets involved.
然后高层人士会说这是最佳决策，你们所有人都必须同意。
The people at the top then say this is the best decision and you will all have to agree with it.
否则就会有个佩戴徽章、手持枪支的人出现在你家门口。
Otherwise, there's going to be a man with a badge and a gun turn up at your door.
我们所说的自由市场，就是指个人可以在不受胁迫的情况下自主决定什么对他们可能有效。
All that we're saying when it comes to free market is that the individual gets to decide without being coerced what might work for them.
他们可能会犯错，但为什么不该让他们尝试并犯错呢？
Now they could be wrong, but why shouldn't they try and make mistakes?
这才是取得进步的唯一途径。
That's the only way to make progress.
纠错的唯一方法就是实际尝试其他方案，或许会失败。
The only way to error correct is to actually try something else, perhaps fail.
将事物社会化会摧毁其真实性，因为社会群体需要共识才能生存。
Making something social destroys the truth of it because social groups need consensus to survive.
否则他们就会争斗。
Otherwise, they fight.
他们无法和睦相处。
They can't get along.
而共识全是关于妥协，而非追求真理。
And consensus is all about compromise and not about truth seeking.
科学曾是这门独特学科，至少在自然科学领域，个人可以代表社会其他成员追求真理。
Science was this unique discipline, at least in natural sciences where where you could have individuals truth seeking on behalf of the rest of society.
其他那些验证自己确实掌握了现实运作最佳模型的人，可以通过发明创造将这些成果传播给社会其他成员。
Other individuals that verify that they did indeed have the best current model of how reality works, and then that could be spread out through inventions to the rest of society.
但社会科学或这种悄然渗入学术界并接管社会科学本身的病毒已经完全腐化。
But the social sciences or this virus that crept into academia and have taken over social sciences themselves are completely corrupted.
首先，他们需要向社会争取资金支持，因此实际上带有政治动机。
Firstly, they need to appeal to society for funding, so they are actually politically motivated.
然后他们自身又在影响社会，因为他们的研究和模型被用来推动政策制定。
And then they themselves are influencing society because their studies and models are used to drive policy.
所以这些领域最终也难免被腐蚀。
So of course that ends up corrupted as well.
但现在连自然科学也受到社会科学的侵袭，变得越来越社会化。
But now even the natural sciences are under attack from the social sciences, and they're becoming more and more socialized.
群体思维参与得越多，离真相反而越远。
The more groupthink you see involved, the further from the truth you actually are.
确实，表面和谐度可能提高了，但完全可以在保持社会和谐的同时，允许其中的真理探索者发现真相，并找到为整个群体改变和改善现实的方法。
And yes, the more you're getting along, but you can have a harmonious society while still allowing truth seekers within that society to find truth and to find the means to alter and improve reality for the entire group.
即便从历史来看，大多数科学突破也并非来自科学机构。
Even historically, most of the scientific breakthroughs didn't come from scientific institutions.
重大突破往往来自特立独行的自然哲学家，他们在当时备受诋毁，常遭迫害，却坚持基于自己发现的真理与社会抗争。
The big ones came from individual natural philosophers who were very independent thinkers, who were reviled in their time, often persecuted, who fought against the rest of society on the basis of their truths.
通常要等到他们去世几十年甚至几个世纪后，这些真理才被世人接受。
And it took decades or centuries often after their deaths before those truths were accepted.
如果你观察心理学界的现状，会发现很多学术理论既经不起重复验证，也经不起现实检验。
A lot of these academic theories don't actually stand up either to replication, if you look at what's going on in psychology, or even to reality.
罗里·萨瑟兰有一句名言，大意是说营销就是了解经济学家所不知道的东西。
Rory Sutherland had this great quote where he said something along the lines of marketing is the knowledge of what economists don't know.
经济学家假设行为完全理性，但人类显然是生物性的湿件，所以你可以通过营销手段绕过这一点。
Economists assume perfectly rational behavior, but humans are obviously wetware biological creatures, so you can hack around that using marketing.
或者像纳西姆·塔勒布更进一步说的那样，他们假设了一种虚假的理性，而人类实际上在考虑毁灭风险、归零风险，学术界则在遍历性推理上犯了错误。
Or Nassim Taleb would go even further and say they assume a false rationality, whereas humans are pricing in the risk of ruin, the risk of going to zero, and the academics are making mistakes about ergodic reasoning.
他们假设对整体有利的必然对个体有利，但事实并非如此，因为个体不愿意归零，不愿意死亡。
They're assuming that what's good for the ensemble is good for the individual, and it's not because an individual doesn't want to go to zero, doesn't want to go die.
因此他们不会承担毁灭性风险，也不会承担破产风险，而群体应该愿意承担破产风险，因为这会分散到众多不同个体身上。
So they will not take risks of ruin, and they will not take risks of bankruptcy, whereas a group should be willing to take risk of bankruptcy because that's spread out among so many different people.
群体从不承认失败。
Groups never admit failure.
群体宁愿活在'我们是被压迫的'这种神话中，也绝不承认失败。
A group would rather keep living in a mythology of we were oppressed than ever admit failure.
只有个体才会承认失败。
Individuals are the only ones who admit failure.
即便是个体也不愿承认失败，但最终他们可能会被迫承认。
Even individuals don't like to admit failure, but eventually they can be forced to.
群体永远不会承认他们错了。
A group will never admit they were wrong.
群体永远不会承认我们犯了错误，因为试图改变想法的群体会分崩离析。
A group will never admit we made a mistake because a group that tries to change its mind falls apart.
因此我很难在历史上找到大型群体承认'我们原以为A，但答案其实是B'的例子。
So I'm hard pressed in history to find examples of large groups where they've said, we thought a, but the answer is actually b.
通常在这种情况下会发生分裂，比如从天主教会转向新教等等。
Usually, what happens in that case is a schism where you go from Catholic church to Protestant and so on.
会出现分歧，通常还伴随着大量内部斗争。
There's a divergence and usually a lot of infighting.
这在加密货币领域也会发生，比如代币分叉。
This happens in crypto land too where the coins fork.
比特币不会突然说我们应该有智能合约，以太坊也不会突然说我们应该保持不可变性。
Bitcoin doesn't suddenly say we should have had smart contracts, or Eth doesn't suddenly say we should have been immutable.
我曾在一个基金会董事会任职，该基金会负责为某项事业分配资金。
I was on a board of a foundation that was charged with giving out money for a cause.
这让我感到非常幻灭，因为我发现无论基金会做什么，他们都会宣布胜利。
And I found it very disillusioning because what I learned was that no matter what the foundation did, they would declare victory.
他们会为特定事项提供资金。
They would give money for a certain thing.
他们会支持特定项目。
They would support a certain project.
而每个项目都宣称取得了胜利。
And every project was victorious.
每个项目都宣称获得了成功。
Every project was a success.
有很多互相吹捧的情况。
There was a lot of back slapping.
有很多听起来很高尚的使命宣言和愿景声明。
There was a lot of high sounding mission statements and vision statements.
许多祝贺。
A lot of congratulations.
许多美好的晚餐。
A lot of nice dinners.
但从未真正完成任何事情。
But nothing ever got done.
而我意识到这是因为缺乏客观反馈，因为没有损失，全是社交收益，他们不可能失败。
And what I realized was because there is no objective feedback, because there is no loss, it's all social profit, they couldn't fail.
正因为他们不会失败，所以整天都在错误地分配资源。
And because they couldn't fail, they misdirected resources all day long.
最终，这样的团体自然会耗尽资金。
And eventually of course such groups run out of money.
如果你想改变世界使其变得更美好，最好的方式是通过营利性组织，因为它们必须接受现实的反馈。
If you wanna change the world to a better place, the best way to do it is a for profit because for profits have to take feedback from reality.
讽刺的是，营利性实体比非营利性实体更具可持续性。
Ironically, for profit entities are more sustainable than nonprofit entities.
它们是自我维持的。
They're self sustainable.
你不需要总是拿着乞讨碗四处奔走。
You're not out there with a begging bowl all the time.
当然，你会失去美好的非营利身份，必须缴纳税款，而且纯粹追求利润也可能导致腐败。
And of course you lose the beautiful nonprofit status, you have to pay your taxes, and also you can get corrupted by being purely for profit.
但我认为最好的企业是那些长期兼顾营利性、可持续性和道德性的，这样才能吸引最优秀的人才。
But I would argue that the best businesses are the ones that long term are both for profit, sustainable and ethical so you can attract the best people.
你能坚持下去是因为这是一项使命，不仅仅关乎金钱，因为赚钱存在边际效益递减。
You can sustain it because it's a mission, it's not just about the money because there's diminishing returns to making money.
金钱在你生活中的边际效用是递减的。
There's diminishing marginal utility to money in your life.
所以我明白，如果你想改变世界，或许通过营利性方式尝试会更好。
So I learned that if you wanna change the world, you're probably better off trying to do it with a for profit.
知识是让资源存在变得无限的东西。
Knowledge is the thing that makes the existence of resources infinite.
知识的创造是无止境的。
The creation of knowledge is unbounded.
我们将持续创造更多知识，从而了解更多不同的资源。
We're just gonna keep on creating more knowledge and thereby learning about more and different resources.
在《无限起源》开头有个关于铕的精彩寓言，大卫提到大约六十年前首批彩色电视开始制造时的情况。
There's this wonderful parable of Europium in the beginning of Infinity where David talks about sixty years ago or so when the first color television started to be manufactured.
那时是阴极射线管类型，向荧光屏发射电子束，荧光屏上有三种不同颜色的像素点，其中一种是红色。
They were cathode ray tube type where you'd fire a stream of electrons at a phosphorescent screen, and the phosphorescent screen have these pixels, three different colors, one of which was red.
屏幕上那些红色荧光粉含有铕元素。
And those red phosphors on the screen were filled with the element europium.
铕的有趣之处在于通电激发时会发出这种红色光芒。
And the interesting thing about europium is when you put electricity through it, when you excite it, it glows with this red colour.
铕更特别的是，它是元素周期表上唯一具有这种特性的元素。
And the extra interesting thing about europium is that it is the only such element on the periodic table.
它是唯一能做到这点的化学物质。
It's the only chemical that will do that.
如果用电子轰击它，它会发出红色光，这正是彩色电视所需的。
If you fire electrons at it, it will glow the red that you need to have colour television.
据计算，地球上铕元素的储量有限，而阴极射线管制造正在快速消耗这些铕资源。
Now, it was calculated that there's only a certain amount of europium on the earth, and that amount of europium was quickly being consumed by cathode ray tube manufacture.
因此科学家们建立了一个非常可靠的数学理论，证明阴极射线管的数量是有限的。
So the scientists had a perfectly robust mathematical theory about how the number of cathode ray tubes was finite.
所以阴极射线管终将耗尽。
Therefore, they're gonna run out of cathode ray tubes.
从狭义上讲确实如此——地球上的任何特定资源总量都是有限的。
And it's true in a very narrow sense that for any given resource, you're going to have a finite amount on planet Earth.
当然外太空可能存在铕元素，或许可以在那里开采。
Of course, there's gonna be europium in outer space, you could probably mine it there.
但更深层的问题是：现在已经没人使用阴极射线管了。
But the deeper point is no one has cathode ray tubes anymore.
如今的彩色电视原理与铕元素的激发完全无关。
The whole idea of colour television has nothing to do with the excitation of europium these days.
我们都在使用液晶屏幕。
We've all got LCD screens.
我们曾拥有等离子屏幕。
We had plasma screens.
未来很可能还会出现与现有技术毫无关联的新技术，但我们依然能享受彩色电视或彩色屏幕。
And there'll probably be something else coming in the future as well that will have absolutely nothing to do with the technology we have today, but we're still going to have color television or color screens.
这个规律适用于我们能想到的任何资源。
And this is true for absolutely any resource that we can think of.
你完全可以做一个完美的马尔萨斯式计算：如果我们生活在非洲大草原上，就不能继续燃烧木材，因为最终所有森林都会被烧光。
You might very well make a perfectly good Malthusian calculation that we can't keep on burning wood if you happen to be living on the African Savannah because eventually all the forests are gonna be burned down.
显然，我们会耗尽木材。
Obviously, we're gonna run out of wood.
木材的数量是有限的。
There's a finite amount of wood.
即使你能种植更多木材，最终木材的消耗量也会超过现有储量。
Even if you can grow more wood, eventually the consumption of wood is going to outstrip the amount that's there.
这就是针对煤炭、石油和我们正在消耗的其他一切资源所提出的论点。
And this is the argument that's made for coal, oil, and everything else that we happen to be consuming.
即便是所谓的真空，也蕴含着大量物质和可转化为能量的东西。
Even so called empty space has a lot of matter and a lot of things that could be converted into energy.
宇宙中的资源是无限的。
There is no limit to the amount of resources out there.
唯一有限的只是知识。
There's purely a limit to knowledge.
可悲的是，这里存在一种人们常有的悲观假设：认为人类的创造力是有边界的。
And unfortunately, there's a pessimistic assumption here that people make that human creativity is bounded.
我认为，恰恰是那些从未亲手建造过东西、从未从零创造新事物的人，最容易产生这种感受。
And I think it's the people who themselves have not built things, who have not created new things from scratch, who seem to feel this the most.
英国独立电视台曾报道过亚马逊公司产生大量所谓浪费的新闻，称亚马逊定期批量销毁大量产品。
There was a story on ITV in UK, and they were talking about how much supposed waste that Amazon produces, that Amazon was destroying a whole bunch of products regularly, routinely.
我当时就想：这些人为什么要把自己的观点强加给一个他们完全不了解的行业？
And I thought, why are these people inserting their opinion into a business that they know absolutely nothing about?
他们会更倾向于哪种选择？
What would they prefer?
他们是否更希望亚马逊拥有不可能实现的能力，即精确掌握需要生产多少产品的完美知识？
Would they prefer Amazon to have the impossible, namely perfect knowledge of precisely how many products need to be made?
换句话说，这是一种认识论上不可能实现的处境。
In other words, an epistemologically impossible situation to be in.
还是他们更希望亚马逊生产不足，导致想购买的人实际上无法获得产品？
Or would they prefer that Amazon made insufficient products so the people who wanted to purchase them weren't actually able to get hold of them?
当然，亚马逊的做法是生产略多于他们所需的数量。
What Amazon, of course, does is make slightly more than what they need.
这是任何企业都会发生的情况。
That's what happens in any business.
他们时不时会生产比当前需求略多的产品。
They make slightly more than what they need now and again.
我曾听一位风险投资家向我争辩说，现在的鞋类品种太多了。
I once had a venture capitalist argue to me that there were too many kinds of shoes.
他认为这是资本主义失败的例证，因为没人需要这么多运动鞋款式，显然我们已经让社会不堪重负。
And it was an example of how capitalism had failed because nobody needs as many kinds of sneakers and clearly we've overshadowed society.
我反问他的问题是：你从什么时候开始知道鞋子种类过多的？
My question to him was, when did you know that there were too many shoes?
历史上哪个时间点让我们判定鞋子种类已经过剩？
What's the point in history where we decide there's too many shoes?
在此之前，我们明明需要更多鞋子——需要更有弹性的鞋、更耐穿的鞋、更厚底的鞋、更轻便的鞋，需要各种惊人的鞋类创新。
Where before that we need more shoes because we need more stretchy shoes, we need more durable shoes, we need thicker soles shoes, we need lighter shoes, we need all kinds of amazing shoe innovation.
然后某个时刻，有人决定我们现在鞋子够多了，需要砍掉其他所有鞋款生产线。
And then at some point somebody decides now we have enough shoes, now we need to kill all the other shoe lines.
你怎么会想到这个主意，觉得自己恰好生在对的时空，能断定‘是的，我们的鞋子已经足够’？
Where did you come up with this idea that you just happened to be born in the right time and the right place to identify that yes, we have enough shoes.
这是每个人都容易陷入的一种狭隘观念。
This is a certain parochialism that everyone falls into.
更宏观层面的表现就是‘资源枯竭论’的哲学。
There's a more macro version of that which is we're running out of resources philosophy.
它始于‘地球资源是有限的’这个前提。
And it starts with the earth is finite.
存在这么一组有限的资源。
There's this finite set of resources.
我们正在耗尽这些资源，如果再不抑制消费，我们都将走向灭亡。
We're running out and we're consuming them all, and therefore we're all going to die if we don't tamp back our consumption.
首先，你如何确定边界就是地球？
First of all, how did you decide it was the earth?
你如何确定资源枯竭的不是你所在的城镇？
How did you decide that your town wasn't running out of resources?
为什么不是把城镇作为你想拯救的实际范围，而把之外都视为遥不可及的外界？
Why wasn't the town the actual area that you wanted to save and then everything outside of that was foreign and unreachable?
为什么要把边界划定在地球范围？
Why draw the boundary around the earth?
我们完全可以放眼太阳系。
We could go to the solar system.
我们可以去银河系。
We could go to the galaxy.
我们可以去宇宙。
We could go to the universe.
我们可以去多元宇宙。
We could go to the multiverse.
如果你知道如何利用，那里有大量资源。
There's a lot of resources out there if you know how to harness them.
那么你如何定义什么是资源？
And then how do you define what a resource is?
资源就是通过知识可以将一种东西转化为另一种东西的事物。
A resource is just something that through knowledge you can convert from one thing to another.
曾经有段时间煤不是资源，铁也不是资源。
So there was a time when coal wasn't a resource, iron wasn't a resource.
对穴居人来说，几乎没有什么东西是资源。
To a caveman, very few things are resources.
只有少数可食用植物和一些可食用动物，仅此而已。
Just a few edible plants and a few edible animals and that's it.
但驯化、收割、作物、冶金、化学、物理、发展发动机和火箭技术。
But domestication, harvesting, crops, metallurgy, chemistry, physics, developing engines and rockets.
所有这些都将我们原本认为毫无价值的东西转化为资源。
All of these are things that are taking things that we thought were worthless and turning them to resources.
铀从一文不值变成了不可思议的资源。
Uranium has gone from being completely worthless to being an incredible resource.
所以这种世界的有限资源模型隐含地假定了知识也是有限的。
So this finite resource model of the world implicitly assumes finite knowledge.
它声称知识创造已经走到了尽头。
It says knowledge creation has come to an end.
我们被困在当前这个节点，因此基于现有的知识，这些就是我们所能获取的全部资源。
We are stuck at this current point, and therefore based on the knowledge that we have currently, these are all the resources available to us.
现在我们必须开始节约了。
Now we must start conserving.
但知识恰恰是我们总能不断创造更多的东西。
But knowledge is the thing that we can always create more of.
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