The Universal Code

你可能会想，Raoul 拿这个到底想干嘛？

Now, you might think, what the hell is Raoul doing with this?

他又不是物理学家。

He's not a physicist.

也不是哲学家。

He's not a philosopher.

它既不属于这些范畴，但又包含了所有这些。

It's kind of none of that, but it's all of that.

宇宙法则。

The Universal Code.

它基本上就是宇宙的操作系统，能解释过去和未来的一切。

It's basically the operating system of the universe, and why it explains everything that comes next and everything that has come before it.

大家一直在争论不同的事情，主要是因为各自的角度不同，而且大多数人没有把意识作为基础。

Everyone's been arguing about different things, but mainly because they were all coming from different angles, and most of them didn't take consciousness as the substrate.

一旦你把它作为基础，这些问题就都迎刃而解了。

Once you do, it kind of solves all of these.

人工智能也开始做同样的事情。

AI begins do the same.

这种递归意识就是从生物学到人工智能的那条线索。

That recursive awareness is the thread from biology to artificial intelligence.

这就是宗教。

This is religion.

这就是物理学。

This is physics.

这就是数学。

This is maths.

这就是经济学。

This is economics.

这就是技术。

This is technology.

整个体系都包含在一个架构里。

It's the whole thing in one architecture.

大家好，我是拉乌尔·帕尔，欢迎收看我的节目《旅人》，在这里我们将探索宏观、加密货币和指数级技术时代之间的理解交汇点。

Hi, I'm Raoul Pal, and welcome to my show, The Journey Man, where we travel to that nexus of understanding between macro, crypto, and the exponential age of technology.

我在宏观领域工作了三十五年，核心工作就是模式识别，试图拼凑这个不断演变的三维全球宏观拼图，连接各个碎片。

My job in macro for thirty five years has been pattern recognition, trying to connect the dots of this huge three d jigsaw puzzle that's ever evolving that is global macro.

而这会带你走上一些不寻常的道路。

And that takes you down unusual paths.

在过去一年半到两年的时间里，这条路让我开始连接人工智能和意识之间的关联。

And somewhere in the last year and a half, two years, it took me down the path of connecting the dots between AI and consciousness.

然后我逐渐意识到，也许我们所知道的一切都是计算，都是更大系统的一部分。

And then coming across the idea that maybe everything that we know is compute and is all part of a larger system.

一开始我其实不太清楚自己在说什么，于是我开始深入研究。

I didn't really know what I was talking about to start with, and I started diving into it.

我最终到达了一个从未预料到的地方。

And I got somewhere that I never expected to get to.

那就是一套被称为‘宇宙法则’的四大普遍规律。

A set of four universal laws called the Universal Code.

你可能会想，Raoul 这是在搞什么名堂？

Now, you might think what the hell is Raoul doing with this?

他又不是物理学家。

He's not a physicist.

也不是哲学家。

He's not a philosopher.

这好像什么都不算，但又什么都沾边。

It's kind of none of that, but it's all of that.

实际上，这是一套关于万物的宏大理论。

It's in fact a grand theory of everything.

我是说，我之前有个大框架叫‘万物代码’，后来发现它只是更大体系的一部分——宇宙本身的运行系统。

I mean, I had that big picture thesis called the everything code, and I realized that that was just part of something much bigger, the operating system of the universe itself.

但‘宇宙代码’最有趣的地方在于，它可以应用于任何事物。

But what's so interesting about the universal code is it can apply to everything and anything.

我现在已经构建了一个AI，它利用‘宇宙代码’框架和第一性原理，来分析地缘政治、市场、政治等所有这类问题。

I've now built an AI that uses the universal code framework and first principles thinking to analyze geopolitics, markets, politics, all of these kinds of things.

因为如果它真的是一个通用代码，如果它是一条定律，而且这些确实是定律，那它就应该能被观察到，并且能让我们更好地理解我们所处的世界。

Because if it is actually a universal code, if it's a law and these are laws, then it should be observable, and it should give us a better understanding of the world we're in.

我觉得这很特别。

I think it's something special.

把它公开让我有点害怕，因为这远远超出了我的知识范围。

It's a little bit scary for me to put it out there because this is well outside of my knowledge zone.

人们会翻白眼说，他这是在搞什么？

People are gonna roll their eyes and say, the hell is he doing it?

但我知道我的方向是对的。

But I know I'm directionally right.

我知道我的方向非常正确。

I know I'm directionally very right.

而且这真的很有意思，它确实能解释我们这个时代。

And it's really interesting, and it really explains our time.

所以，准备好听吧。

So settle in.

花点时间吸收一些新的、更深刻、更有意义的东西——这个通用代码。

Take your time to absorb something new, something deeper and more profound, the universal code.

也许它会像改变我的人生一样，改变你的人生。

And maybe it'll change your life like it changed mine.

和我一起，Raoul Pal，踏上探索宏观、加密货币和指数时代格局的旅程。

Join me, Raoul Pal, as I go on a journey of discovery through the macro, crypto, and exponential age landscapes.

在《旅人》节目中，我与世界上最聪明的人对话，这样我们都能一起变得更聪明。

In The Journey Man, I talk to the smartest people people in the world so we can all become smarter together.

格局。

Landscapes.

大家好。

Hi, everyone.

很高兴见到各位。

Good to see you all.

欢迎收看《指数主义者》的季度国情咨文，我通常会涵盖一些更广泛的话题并进行分析，但今天我想做点不一样的事情。

So welcome to the quarterly State of the Union address for The Exponentialist, where I try and cover the kind of broader topics and look at it, but I'm going to do something different today.

今天我要带你们了解这个‘通用代码’，我已经开发了大概一年半了。

I'm going to walk you through the Universal Code, which I've been developing now for, I don't know, a year and a half.

你们应该读过那篇相关的文章。

You've read the article about it.

我们之前也聊过一些，但这是我第一次专门做演示来讲解它。

We've talked about it a bit, but this is the first time I've ever made a presentation on it.

所以，不好意思，你们就是我的小白鼠观众了。

So, excuse me, you're my guinea pig audience.

所以，我特别想在评论区听到大家对这次演示的反馈，因为我正在把它扩展成一个更庞大的体系。

So, I really want to hear in the comments section the feedback on this presentation, because I'm building this into a much bigger body of work.

我跟Claude一起，已经写了大概21万字了，最终会整理成一本书。

I said, along with Claude, I've written maybe 210,000 words on this so far, and it'll eventually be turned into a book.

我觉得这是我做过的最重要的事情。

I think it's the most important thing I've ever done.

我自己也不太清楚是怎么走到这一步的。

I don't know quite how I got here.

这有点莫名其妙。

It's randomly weird.

我一开始呢，我的背景就是发现模式。

I started by you know, my background is spotting patterns.

在别人还没发现之前就看出模式，看到事物之间的关联，理解正在发生的事情。

Spotting patterns before others don't and seeing coherence, that kind of understanding of things that are happening.

我一直在金融市场里运用这个能力，我的大脑就是这样训练出来的。

And I've been using that in financial markets, and that's where I've kind of trained my brain into it.

对我来说，这几乎是自然而然发生的。

And it just sort of happens for me.

然后我开始把很多其他领域的东西拼凑起来，这些领域超出了我的经验范围，比如物理学、数学、生物学，甚至灵性。

And I started to piece together lots of other bits and pieces that were outside of my domain of experience, whether it's physics, mathematics, whether it was biology, whether it was spirituality.

我开始看到一个模式，但我无法在脑子里理清，更无法用语言表达出来。

And I started seeing a pattern which I couldn't put in my head and I certainly couldn't put into words.

后来我看到了‘真理终端’，那是安迪·艾利，他是Real Vision的嘉宾，还有瑞安·费里斯。

Then I saw the terminal of truths, and that was Andy Ailey, who's been a guest on Real Vision, and Ryan Ferris.

在那个房间里，一群AI在互相交谈，我就开始想，你知道吗？

And that room where they put together a bunch of AIs talking, and I started thinking, you know what?

这里有风险意识的迹象。

There are signs that risk consciousness here.

那么，这意味着什么？嗯，这就是整个旅程，关于意识是什么的旅程。

Now, what that means, well, that was the whole journey, the journey of what is consciousness.

我遇到了像感质、意识、智能这些概念之间的区别，还有诸如此类的东西。

And I bump into things like the difference between qualia and consciousness and intelligence and all of these things.

一切都变得超级复杂。

All got super complicated.

但我开始用我脑海中的某种框架来看待这个世界。

But I started to see the world in something that I had in my mind.

我最初是在小开曼岛看到它的。

I saw it in Little Cayman first.

我意识到地球上的一切都是一种计算形式。

I could just realize that everything on the planet was a form of compute.

然后我开始看到神经网络在生物层面的图像，从最小的组成部分一直到宇宙的主宰系统。

And then I started seeing images of neural networks at biological level, at the smallest component parts, to the boss system of the universe.

我觉得这有点奇怪。

I thought, this is weird.

有一种分形模式无处不在。

There's a fractal pattern that appears everywhere.

这让我开始思考，这一切是怎么联系在一起的？

And that started me thinking about how does this all tie together?

这一切到底是什么？

What is this all?

意识是什么？

What is consciousness?

宇宙意识是什么？

What is universal consciousness?

宇宙又是什么？

What is the universe?

奇怪的是，随着时间的推移，这一切竟然都串联起来了。

And bizarrely, it all fell into place over time.

这是我第一次完整地展示这个想法。

And this is the first time I've ever fully presented it.

好吧，也不算完整。

Well, not fully.

这显然只是一个简短的总结。

This is obviously a brief summary of it.

但我想看看你们怎么理解，看看它对你来说是否说得通。

But I want to see how it lands with you guys and see whether it makes sense to you.

那么，我们开始看演示吧。

So, let's go to the presentation.

显然，这是我今天早上用Claude写的。

Obviously, I wrote it with Claude this morning.

做起来就这么简单。

It was that easy to do.

我的意思是，我的谷歌硬盘里显然存了成千上万字关于这个的内容。

Mean, I've obviously got a Google Drive full of thousands of words of this.

但我跟Claude说，我需要把这些整理出来。

But I said to Claude that I needed to put this together.

我们在解释方式上有了几个突破。

We had a couple of breakthroughs in how to explain it.

我觉得这样应该能行。

And I think this is going to work.

所以，这个通用代码，其实就是宇宙的操作系统。

So, the Universal Code, it's basically the operating system of the universe.

它为什么能解释之前和之后发生的一切。

And why it explains everything that comes next and everything that has come before it.

你看，万物的架构其实很简单。

You see, the architecture of everything is simple.

宇宙有一个架构，它分为三层。

The universe has an architecture, and it has three layers.

意识，嗯，那就是计算机。

Consciousness, well, that's the computer.

所以当我们说意识是宇宙的基本基质，而不是时空时，时空本身是无法计算的。

So when we talk about consciousness as the fundamental substrate of the universe, not spacetime, spacetime itself can't compute.

时间是计算的一个元素，但意识才是根本。

Time is an element of compute, but consciousness is the fundamental.

它是万物运行的媒介。

It's the medium through which everything runs.

它不是从复杂性中涌现出来的，而是本来就存在的东西。

It's not something that merges from complexity, it was what was already there.

把它想象成一台空白计算机。

Think of it as a blank computer.

你买了一台新电脑，上面什么都没有。

You bought a new computer, there's nothing on it.

好，那么你需要的是操作系统。

Okay, then what you need is the operating system.

所以，我——而且我知道这听起来很狂妄、很奇怪，我也没有资格这么做——但我觉得我想出了支配宇宙的四条法则。

So, I have- and again, I know this sounds hubristic and weird, and I have no right to do this, but I think I've come up with the four laws that govern the universe.

注意，这并不意味着像引力以及我们理解的其他物理定律组成部分就不存在了，这不是物理定律本身。

Now, that doesn't mean that things like gravity and all the other component parts of what we understand the laws of physics, this is not the laws of physics.

这是关于宇宙如何运作的法则。

This is the laws of how the universe works.

而这四条法则就是用来组织这一切的。

And the four laws organize that.

它就像是操作系统的代码，在宇宙的每一个尺度上运行。

It's the code for the operating system, and it runs at every scale throughout it.

其他的一切都是计算。

And everything else is compute.

正是这个完整的想法让我走到了这一步。

That whole idea that I had got me to this.

你可以看到，我是从意识的角度开始的，当时并没有真正理解它，然后到了‘一切都是计算’这个想法，接着就引出了这四条法则。

You can see I started with the consciousness side, didn't really understand it, got to the everything is compute side, and then that led me to the four laws.

所以，我们能看到的万物——生物、物理、市场、科技、网络——全都是计算，所有应用都运行在同一台机器上，也就是那个操作系统，即计算机本身。

So, everything that we can see, biology, physics, markets, technology, networks, all of it is compute, all applications running on the same machine, the operating system that is the computer.

所以，科技并没有发明这种架构，它只是继承了它。

So, technology didn't invent this architecture, it inherited it.

那么，这一切到底为什么重要？

So, why does this all matter?

为什么拉乌尔要喋喋不休地讲这个‘万物代码’？

Why is Raoul bleating on about the everything code?

嗯，如果万物都运行在同一台计算机上，使用同一个操作系统，那我们观察到的一切都不是随机的。

Well, if everything is running on the same computer using the same operating system, then nothing we observe is random.

一切都是可解读的。

It's all legible.

而它们之所以可解读，是因为它们全是代码。

And it all becomes legible because it's all code.

一旦你看懂了代码，就能在市场的波动、文明的演进、人工智能的发展中，处处读懂它。

And once you see the code, you can read it everywhere going on in markets, civilization, AI.

同样的模式在每个尺度上都会出现，比如地下的改善网络，也就是森林里的那些网络。我突然意识到，菌根网络和森林里的其他网络，都是让树木之间进行智能计算的网络。

The same patterns appear every scale, From more kaizen networks underground, so those are the networks in a forest, where I suddenly realized that mycelial networks and other networks within the forest were networks that allowed for computation of intelligence within trees.

这有个说法，叫‘树木万维网’，你可以去查查。

There's a whole thing about- it's called the Wood Wide Web, if you want to look it up.

这本身就是一个很长的故事，但它说明森林并不是树木的随机集合，而是一个网络，一个智能网络，在整个森林里分配资源，并且有信号传递机制。

It's a long story in its own right, but it shows that a forest is not just a random collection of trees, it's actually a network, an intelligent network that allocates resources throughout the forest and has a signaling mechanism.

这太神奇了。

It's wild.

宇宙网也是一样的。

And the cosmic web is the same.

当你看到BOSS对宇宙网的成像时，它的拓扑结构和森林是一样的。

When you look at the BOSS imaging of the web, it has the same topology as the forest.

它和大脑中的神经元也是一样的，只是规模放大或缩小了。

It's the same as the neurons in the brain, and it's just scaled up, scaled down.

这绝不是巧合。

And it's not a coincidence.

万物都在运行同一个操作系统。

It's everything running the same operating system.

这就是宇宙的通用代码。

It's the universal code.

一旦你看到了这一点，就再也无法忽视，因为它基本上解释了一切。

And when you see it, you can't unsee it, because basically describes everything.

那为什么之前没人提过这个？

So why hasn't anybody said this before?

为什么拉乌尔觉得自己这么聪明？

Why is Raoul thinking he's so clever here?

其实我并不聪明。

And again, I'm not.

我只是站在巨人的肩膀上。

I'm building on the shoulders of giants.

实际上，我发现这一切最早的表现或解释来自印度吠陀经，其中提到意识是根本的基础。

And really, I found out that the earliest manifestation or explanation for all of this actually came from the Hindu Vedas, where they said that consciousness was the fundamental substrate.

关于各种不同的宗教以及它们如何融入其中，有很多可以说的。

Now, there's a lot to be said about all the various different religions and how they fit in.

但如果从那些看起来格局更大的宗教来看，我认为吠陀经大概是五千年前，可能是关于宇宙这个操作系统的最古老发现。

But if we think of the religions that seemed the bigger picture, I think the Vedas were probably five thousand years ago, probably the oldest discovery of this whole operating system of the universe.

但后来，科学通过还原论的方法，把它分解成了各个组成部分。

But then basically, science, by the reductionist method, broke it down to its component parts.

所以物理学研究力，生物学研究有机体，神经科学研究大脑，经济学研究市场，每个学科都花了数百年时间深入自己的领域。

So physics decided the forces, biology of the organisms, neuroscience, the brain, economics, the markets, each just spent hundreds of years going deeper into its component part.

而每个学科都不断得出相同的模式、相同的拓扑结构和相同的优化梯度。

And each one kept arriving at the same patterns, the same topologies and the same optimization gradients.

问题在于，因为每个人都待在自己的领域里，没有人能真正把这些整合起来。

Now, the issue is because everybody was in their own silo, nobody could really put it together.

所以再说一遍，如果我们看吠陀经、奥义书、佛教、苏菲派，所有这些人在几千年前就已经看到了全貌。

So again, if we say the Vedas, the Upanishads, the Buddhists, the Sufis, all of these people saw the whole picture thousands of years ago.

后来我们看到了像惠勒、维格纳和西马德这样的人，他们整合了森林网络。

Then we saw people like Wheeler and Wigner and Simard who put together the forest networks.

这些人开始看到更大整体中的各个组成部分。

All these people started seeing the component parts of the bigger whole.

物理学和数学本身也是同一事物的较小部分。

Physics themselves and mathematics were smaller parts of the same thing.

大家一直在争论不同的事情，主要是因为各自的角度不同，而且大多数人没有把意识作为基础。

Everyone's been arguing about different things, but mainly because they were all coming from different angles, and most of them didn't take consciousness as the substrate.

一旦你这么做，这些问题就都迎刃而解了，你会发现大家说的其实是一回事。

Once you do, it kind of solves all of these, and you see that everyone's roughly talking about the same thing.

所以，它们都汇聚到了一起。

So, they all converged.

它们都汇聚到了描述同一台计算机、同一个操作系统、同一种计算上。

They all converged in describing the same computer, the same operating system, the same compute.

科学一次一个实验地证实了古老的智慧，却没有完全意识到这一点。

Science confirmed the ancient wisdom one experiment at a time without fully realizing it.

这基本上是自上而下的思考，然后从下往上得到了验证。

It was basically top down level thinking and then proven from below.

基本上就是这么回事。

That's basically what happened.

好，那我们来聊聊意识和智能这个话题。

Okay, so let's get into this consciousness and intelligence thing.

意识就是那台计算机。

So consciousness is the computer.

它是基础。

It's the substrate.

一切都在它之中存在。

Everything exists within it.

石头也存在于意识之中。

A rock exists within consciousness.

我觉得石头就是一种计算。

I think a rock is compute.

那是地质层面的慢速时间。

It's geological hard time.

它就像一块地质硬盘，记录着那些原子随时间经历的一切。

It's a geological hard drive of everything that happens to those atoms over time.

神经元处理信息，但没有任何东西在观察自身。

A neuron processes it, but nothing observes itself.

意识并非从复杂性中涌现出来的东西。

Consciousness is not something that emerges from complexity.

它只是复杂性借以表达自身的媒介。

It's just the medium complexity expresses itself through.

所以，它就是整个系统本身。

So it is the entire thing.

现在，我们常把意识与感质混为一谈，感质是人类以及某些动物所具有的那种元素，即我们通过感受和对周围世界的理解来认识自己。

Now, we confuse consciousness with qualia, which is that human element that some animals have as well, where we think of ourselves in terms of feelings and our understanding of the world around us.

我们在脑海中给自己讲的故事，所有这些，都属于感质。

The stories we tell ourselves in our heads, all of that, that's qualia.

但这并不是我所说的意识所必需的前提条件。

That's not a prerequisite for the consciousness that I'm talking about.

那是另一回事，而且是一种智能的表现。

That's a separate thing, and it's a form of intelligence.

智能就是当计算机变得足够复杂，开始观察自身时发生的事情。

Intelligence is what happens when the computer gets complex enough that the computer begins to observe itself.

所以人类是主要的例子，但很多事物都能观察自身。

So humans are the primary example of that, but many things can observe themselves.

计算机本身也有能力观察自身。

Computers themselves have an ability to observe themselves.

单细胞大脑模型、人类对自身意识的感知，人工智能也开始做同样的事。

A single cell brain models, human consciousness of being conscious, AI begins to do the same.

这种递归式的自我认知，正是生物学对人工智能构成的威胁——它开始自主学习，并能复制自身的知识和结构。

That recursive awareness is the threat from biology to artificial intelligence, where it starts to learn it by itself, and it can replicate that knowledge and itself.

这就是智能的作用，也是构成意识的一部分。

That is what intelligence does, and that is what forms part of consciousness.

那么，宇宙为什么会膨胀呢？

So, why does the universe expand?

在某些情况下，它膨胀得比时空还快，这按理说在物理定律下是不可能的。

And in some cases, it expands faster than spacetime, which should be improbable due to the laws of physics.

我们知道时空不可能是那个基础载体。

We know that spacetime can't be the substrate.

嗯，这是因为这台计算机从奇点开始，也就是最大压缩、零多样性。

Well, it's because of the fact that this computer starts with the singularity, maximum compression, zero diversity.

然后，通过化学作用，恒星开始形成元素，进而演化出生命，最终产生智能。

Then, via chemistry, the stars start to form elements leading into biology and eventually intelligence.

所有这些都增加了对计算能力的需求。

All of these things grow the need for the compute.

所以宇宙的膨胀并不是随机的宇宙学偶然事件。

So the expansion of the universe isn't a random cosmological accident.

它是在最根本的层面上进行资源分配，以创造更多的智能。

It's resource allocation at the most fundamental level to create more intelligence.

这个过程就是宇宙的过程，也是宇宙中每个组成部分的过程。

That process is the process of the universe, and it's the process of every component parts of the universe.

我们从独立状态走向协调，再到网络，再到压缩，最终达到智能。

We go from independent states to coherence to networks to all of this to compression, and eventually, we get to intelligence.

我来解释一下这是怎么回事。

And I'll explain how this is.

但随着智能的增长，宇宙也必须扩张。

But as intelligence grows, the universe has to grow.

所以，这就是宇宙的法则。

So, the universal code.

这里有四条定律。

Here's the four laws.

第一条，也是最重要的一条：单位能量产生的智能。

Law number one, the most important one, intelligence per unit of energy.

整个宇宙的目的，就是最大化每单位能量输入所产生的智能输出。

The entire universe's purpose is to maximize the output of intelligence per unit of energy input.

这是所有事物遵循的根本驱动力。

This is the master gradient that everything flows from.

所有事物中每一个可观察的过程，无论是自然界还是宇宙中的，都围绕这个展开。

Every observable process in every single thing, whether it's in nature or in the universe, is all based around this.

压缩。

Compression.

将信息压缩成更密集、更便携的形式，是智能的必要组成部分。

Compression of information to denser, more portable forms is a necessary component of intelligence.

每一次压缩都是一次相变，解锁新的能力。

Each compression is a phase transition that unlocks new capabilities.

连贯性，这个词我用了很多次，因为一旦我开始理解它，它对我来说就变得清晰了。

Coherence, this is the word I've been using a lot, because once I've started to understand it, it's become coherent to me.

独立的计算单元对齐成更大的系统，像一个整体一样运作。

Individual units of compute align into larger systems that behave as one.

这就是底层结构如何自我扩展的。

This is how the substrate scales itself.

所以连贯性就是很多不同的东西开始一起运动，你得到的是扩展智能的能力。

So coherence is when lots of different things start moving together, and what you get is the ability to scale intelligence.

而压缩，就是把所有东西整合起来，在此基础上进一步构建。

Compression is when you then put it all together to build upon it.

关于这一点，我稍后会详细说明。

And I'll come into more of this in a sec.

模因信号，没错，我们总以为模因就是网上那些东西，但其实不是。

Memetic signaling, yes, we think of memetics as stuff we see on the internet, but it's not.

它是在网络中流动的信息包，也是系统得以繁荣或生存的关键。

It's the packages of information that flow along networks, and it is also what allows systems to thrive or survive.

如果模因的选择力强，能引起共鸣并形成一致性，它就能存活下来。

If that memetic selection is strong and resonates and builds coherence, it survives.

如果不行，它就会瓦解，最终失败。

If it doesn't, it decoheres and it fails.

这就是选择。

This is selection.

所以，这就是宇宙这个操作系统进行选择的方式。

So, this is how the universe, the operating system, selects.

所以，我们在任何地方都能看到相同的架构和相同的规律。

So, we can see the same architecture and same laws everywhere.

我可以用一千种不同的方式向你展示这一点，但这里就拿生物学和技术做个对比。

And I could show you this in a thousand different ways, but here's biology versus technology.

生物学是一个积累了38亿年的堆栈，而技术基本上是一个只有70年历史的堆栈，就是我们今天使用的计算机技术。

Biology is a stack of 3,800,000,000 years, and technology basically is a 70 year old stack, the technology we're using today, computers.

我们发现它们之间其实很相似，只是用的术语不同。

And what we've got is a similarity, just different words.

记得我们之前说过，每个人基本上都在用不同的语言，但谈论的是同一件事。

Remember, we said this before, everyone's basically speaking different languages, but talking about the same thing.

在细胞层面，能量来自线粒体。

So energy at cellular level is mitochondria.

正是线粒体产生了在我们体内循环的能量。

That's what creates the energy that goes around our body.

在计算机里，相当于线粒体的是GPU。

In computers, it's GPUs.

它们把原始电能转化成组件，从而产生智能。

They take raw electricity, they turn it into the component parts that allow it to generate intelligence.

我们有源代码。

We've got source codes.

人类有DNA。

We've got DNA in humans.

我们有二进制。

We've binary.

我们有运行肽的脚本、计算机里的函数、程序、蛋白质、应用程序。

We've got scripts that run peptides in humans, functions in computers, programs, proteins, applications.

你看，这些基本上都能对应上。

As you can see, it all basically maps.

有个有趣的现象，就是相变——第一次心跳。

There's an interesting one, which is phase transition, the first heartbeat.

当你观察第一次心跳时，它是一堆电信号，一开始是杂乱无章的。

When you observe the first heartbeat as a bunch of electrical signals, what you see is at first, it's incoherent.

它就是这样运作的。

It does this.

然后突然之间，连贯性出现了，生命就形成了。

And then suddenly, coherence and life is formed.

我们在各处都能看到这种现象。

And we see that everywhere.

在互联网或科技领域，我们正通过ChatGPT这样的时刻看到这一点，也就是人工智能。

In the internet or in technology, we're seeing this with a chat GPT moment, AI.

这是科技中智能和意识的第一次心跳。

It's the first heartbeat of intelligence and consciousness within technology.

这很疯狂，但这就是我们的发展方向。

It's wild, but that's where we're going.

所以，我们现在有了身体、人工智能和代理经济。

So, we've got the body, the AI, and the agent economy.

选择机制——科技利用市场，资本配置就是选择，因为它将资本引导到创造更多智能上。

Selection, technology uses markets, capital allocation is the selection, because it funnels capital into creating more intelligence.

现在，说到身体，这就是进化。

Now, on the body, it's evolution.

而进化就是不断提升每个个体或事物智能水平的过程。

And evolution is the process of increasing the intelligence per person or thing.

要理解这段代码如何运作，你可以看看底部的胶原蛋白。

And to see how this code works, you can see collagen at the bottom.

它不过是一堆字母而已。

It's just a bunch of letters.

那些支撑你身体的蛋白质，其实也只是代码。

It's the proteins that hold your body together is just code.

一切都是代码。

Everything is code.

我读到过这个，好像是戴维·辛克莱和一些书里提到的，就是说，人体的代码，虽然听起来有点浪漫，但事实确实如此。

And I read about this, I think was David Sinclair and a bunch of books, where you say, well, the body's human code, and It removes the romance of it all, but it actually is true.

一切都是代码。

Everything is code.

这就是我们开始从AlphaFold Go中看到的，他们开始能够分解蛋白质的所有组成部分，然后重新编程它们。

And that's what we're starting to see with AlphaFold Go, is that they're starting to be able to break down all the component parts of the proteins and then reprogram them.

这就是我们在这里做的事情。

And that's what we're doing here.

所以肽，它们就像是脚本，我们用它们来修复身体中不协调的部分。

So peptides, they're the scripts, and we're using them to fix deconherent parts of our body.

这就是医学现在的发展方向。

That is where medicine is going now.

它基本上就是新的脚本，重新运行我们身体运作的方式。

It's basically new scripts that rerun how our body does things.

所以如果有什么问题，我们就可以修复它们。

So if something is faulty, we can fix them.

这听起来很离奇，但这就是我们生活的世界。

It's bizarre, but this is the world we live in.

所以第一定律，每单位能量的智能。

So law number one, intelligence per unit of energy.

这是关键的一点。

This is the big one.

比如生物学在这方面就非常高效。

So biology, for example, is very efficient at this.

人脑只用20瓦的功率就能运行860亿个神经元。

The human brain uses 20 watts to run 86,000,000,000 neurons.

它花了数十亿年时间来优化这种智能密度。

It's spent billions of years optimizing for this intelligence density.

大脑是我们所知的计算效率最低的设备。

The brain is the most inefficient compute device we know of.

我觉得这已经不太明确了，因为如果你想想一个数据中心运行整个模型，比如Claude，然后把它提供给一亿人使用，那么每单位智能的计算成本其实相当低。

I'd argue it's not quite clear anymore, because if you think of one data center running an entire model, let's say Claude, and then you give that to 100,000,000 people, the compute per unit of intelligence is actually pretty cheap.

但我想你明白我提到生物学是什么意思。

But I think you can see where I'm going with biology.

技术方面，事物只会变得越来越智能。

Technology, things just keep getting more intelligent.

我们一直看到摩尔定律持续有效。

We've seen Moore's Law survive forever.

这就是为什么雷·库兹韦尔能够预测奇点，因为它显然遵循一个公式，而且确实有效。

This is why Ray Kurzweil can manage to forecast the singularity, because it is clearly running on a formula, and it works.

加密货币也属于这个范畴，因为加密网络是智能网络。

And crypto is another thing that fits within this, because crypto networks are intelligent networks.

以比特币为例，它把原始能源转化为永久的、不可篡改的价值。

They convert, let's say in Bitcoin, raw energy into a permanent immutable value.

所以，你是在把电力转化为有价值的东西。

So, you're converting electricity into something that has value.

而权益证明则把它转化为互联网的协调层。

Now, proof of stake converts it into the coordination layer of the internet.

所以，都是指向智能，只是表现形式不同，遵循的规律是一样的。

So, to intelligence, but different expressions, same law.

我最近用这个视角看了很多区块链项目。

I looked recently at many blockchains through this lens.

实际上，我现在开始用这个视角看所有东西，从地缘政治到经济、金融，再到压缩。

In fact, everything I'm starting to look through this lens, from geopolitics to economics to finance, compression.

压缩就是把东西变得更密集、更便携。

Compression compresses things into denser, more portable forms.

每一次压缩都是一次新的相变，会解锁新的能力。

And each one is a new phase transition and unlocks new capabilities.

所以，DNA压缩成分子间代码，语言压缩成符号，货币压缩成便携的凭证。

So DNA compresses into intermolecular code, language compresses into symbols, money compresses into portable tokens.

货币还把大量经济信息压缩到一笔笔交易里。

Money also compresses a whole bunch of economic information into single transactions.

在这个过程中，货币扮演了很多角色。

There's a lot that money does within this process.

它也是模因学的一部分。

It's also part of the memetics.

比特币把信任压缩成数学，而人工智能把知识压缩成可查询的智能，或者说智能本身。

Bitcoin compresses trust into maths, and AI compresses knowledge into a queriable intelligence or intelligence itself.

人工智能就是互联网的压缩层。

AI is the compression layer to the internet.

所有东西都有压缩层，而且我们不断在建造新的。

Everything has a compression layer, and we keep building new ones.

这是一个永无止境的过程，新的压缩层一层层叠加。

It's an endless process of new compression layers built on top of each other.

我们不断重复这个模式：模因选择形成一致性，一致性形成压缩，而压缩又带来智能的提升。

We keep repeating this pattern of memetic selection forms coherence, forms compression, and compression leads to an increase in intelligence.

然后从那个层面，我们再往上建造。

And then from that layer, we build on top.

人体是这样，宇宙是这样，万物皆是如此。

The human body's done it, the universe has done it, everything does it.

互联网现在就在我们眼前上演着这一切。

The internet's doing it right now in front of our eyes.

所以整个堆叠过程一直在持续。

So that whole stack keeps happening.

关于一致性，我们之前聊过。

Coherence, we've talked about this before.

就像计算单元整合成更大的系统，神经元组成大脑，树木形成森林，交易者汇聚成市场，市场再引导资本配置来发展更多智能。

It's it's like when compute aligns into larger systems, neurons into brains, trees into forest, traders into markets, markets into allocation of capital to develop more intelligence.

所有这些现象，这种一致性，无处不在。

All of these things, this coherence, appears everywhere.

模因信号。

Memetic signaling.

这就是选择机制，它让计算模式得以传播。

This is the selection mechanism, and it allows the propagation of compute patterns.

有些模式存活并繁荣，有些则不然。

Some survive and thrive, others don't.

但你会看到同样的网络效应。

But you see the same network effect.

所以网络虽然算不上一条定律，但它是智能的基本前提。

So networks are like a- they're not a law, but they're a fundamental requirement for intelligence.

这就是为什么以计算机网络为导向的企业能超越其他所有企业，因为它们提升了智能。

That's why computer network orientated businesses outperform all others, because they increase intelligence.

而这正是网络的关键所在。

And that is the key thing of networks.

模因信号是信息在网络中传播的方式。

Memetic signaling is how information travels along the network.

所以，模因信号涵盖的范围很广，从宗教开始——宗教把道德框架压缩成便携、可分享的故事，让文明在广阔的空间和漫长的时间里凝聚在一起。

So, memetic signaling has everything from religion, which compress moral frameworks into portable, shareable stories that cohered civilizations across vast distances and vast time.

开源代码，让我们共同传播、进化，然后基于适者生存的原则发展。

Open source code, let's co propagate and evolve and then develop on survival of the fitness.

病毒式内容显然也是另一种形式，它无处不在。

Viral content, obviously, is another form, it's everywhere.

再说一次，这个演讲里讲不完，但我在书里有整章的内容讨论这个。

And again, too long for this talk, but I have whole chapters in the book on this.

网络和多样性，正如我所说，网络无处不在。

Networks and diversity, as I said, networks are everywhere.

它们存在于各个层面。

They're at every scale.

它们是整个过程中不可或缺的组成部分，没有它们就无法存在。

They are a fundamental component part of the entire process and can't exist without them.

这一点在任何地方都成立，多样性也是如此。

It's true everywhere, as is diversity.

生态系统多样性以前看起来是个抽象的概念。

Ecosystem diversity seemed an abstract thing.

人们觉得它和人类进步是对立的，但其实不是。

It's us versus human progress, but it's not.

它们都是同一个操作系统的一部分。

It's all part of the same operating system.

如果一个系统不够多样化，它就会脆弱并消亡。

If a system is not diverse enough, it is weak and dies.

所以，我们需要在整个系统中保持多样性。

So, we need diversity in this whole system.

所以，这是整个过程中很重要的一部分。

So, that's an important part of all of this.

那么，在常规节目里插播一个小广告。

So a quick break in your regular programming.

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If you're serious about your future, grab my free report called Prepare for 2030.

我觉得你还有五年时间尽可能多赚钱，这份指南会帮你应对即将到来的变化。

I think you've got five years to make as much money as possible, And this guide will help you navigate what's coming.

链接在描述里。

The link is in the description.

现在就下载吧。

Download it now.

在这一切开始之前，我编写了《万物代码》。

Now, before this started, I developed the Everything Code.

光是这个名字就暗示了，事物运作是有规律的。

And the name alone suggests there was a code to how things work.

这个代码其实就是那个神奇的公式。

And that code is basically the magic formula.

GDP等于人口增长加上生产力增长再加上债务增长。

GDP equals population growth plus productivity growth plus debt growth.

当时我对这个通用代码的概念一无所知。

Now, I didn't know anything about this universal code idea.

但现在回头看，我发现它其实一直贯穿其中。

But in retrospect, I look at this and I realize it was all part of it all along.

这解释了金融市场和经济中的现象。

It explains this in financial markets and economies.

人口就像是原始的计算能力，网络中的节点。

So population is the raw compute capacity, the nodes in the network.

生产力则是产出的智能单位。

Productivity is the intelligence unit of output.

所以它代表了经济智能的指标。

So it's the proxy for economic intelligence.