#89 – 斯蒂芬·沃尔夫勒姆：细胞自动机、计算与物理学

以下是与斯蒂芬·沃尔夫勒姆的对话，他是一位计算机科学家、数学家和理论物理学家，同时也是Wolfram Research的创始人兼CEO，该公司开发了Mathematica、Wolfram Alpha、Wolfram Language以及新的Wolfram物理项目。他著有多本书籍，包括《一种新科学》，就个人而言，这本书是我计算机科学与人工智能探索之路上最具影响力的著作之一，它让我深深迷恋上细胞自动机的数学美感与力量。诚然，对斯蒂芬的一个批评或许在于人性层面——他强烈的自我意识有时阻碍研究者充分领略其思想精髓。我们在对话中探讨了这一点。

The following is a conversation with Stephen Wolfram, a computer scientist, mathematician, and theoretical physicist who is the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram Alpha, Wolfram Language, and the new Wolfram Physics Project. He's the author of several books, including A New Kind of Science, which, on a personal note, was one of the most influential books in my journey in computer science and artificial intelligence. It made me fall in love with the mathematical beauty and power of cellular automata. It is true that perhaps one of the criticisms of Steven is on a human level, that he has a big ego, which prevents some researchers from fully enjoying the content of his ideas. We talk about this point in this conversation.

在我看来，自我意识可能使人迷失，但也能成为超能力，它催生拒绝向学术机构保守作风妥协的大胆创新思维。在此，我特别邀请您与我一同超越人性特质，敞开心扉感受斯蒂芬著作及本次对话中思想的瑰丽。我相信斯蒂芬·沃尔夫勒姆是我们时代最具独创性的思想家之一，其本质是个善良、好奇而卓越的灵魂。本次对话录制于2019年11月，当时Wolfram物理项目正在进行中，尚未像现在这样开放公众探索。我们已约定近期将再次对话，很可能不止一次。

To me, ego can lead you astray, but can also be a superpower, one that fuels bold, innovative thinking that refuses to surrender to the cautious ways of academic institutions. And here, especially, I ask you to join me in looking past the peculiarities of human nature and opening your mind to the beauty of ideas in Steven's work and in this conversation. I believe Steven Wolfram is one of the most original minds of our time and, at the core, is a kind, curious, and brilliant human being. This conversation was recorded in November 2019 when the Wolfram Physics Project was underway, but not yet ready for public exploration as it is now. We now agreed to talk again, probably multiple times in the near future.

因此这是第一回合，敬请期待不久后的第二回合。这里是人工智能播客，若您喜欢，请在YouTube订阅、苹果播客打五星好评、通过Patreon支持，或直接在Twitter上联系我@Lex Fridman（拼写为f r i d m a n）。照例我会插播几分钟广告，但绝不会在对话中途打断收听体验。希望这种方式不影响您的聆听感受。

So this is round one, and stay tuned for round two soon. This is the artificial intelligence podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple podcast, support it on Patreon, or simply connect with me on Twitter at Lex Fridman, spelled f r I d m a n. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience.

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Quick summary of the ads. Two sponsors, ExpressVPN and Cash App. Please consider supporting the podcast by getting ExpressVPN at expressvpn.com/lexpod and downloading Cash App and using code lex podcast. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code Lex podcast.

Cash App可实现朋友间转账、比特币购买及最低1美元的股市投资。因其支持零股交易，必须提及其幕后将零股订单抽象化的执行算法堪称工程奇迹——向Cash App工程师致敬，他们解决的复杂问题最终呈现为股市抽象层之上的简洁界面，极大降低了新投资者入门门槛并简化资产配置。重申：通过App Store或Google Play下载Cash App并使用代码Lex podcast，您将获得10美元，同时Cash App会向FIRST机构捐赠10美元，该组织致力于全球青少年机器人及STEM教育推广。

Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market. This makes trading more accessible for new investors and diversification much easier. So, again, if you get Cash App from the App Store or Google Play and use the code Lex podcast, you get $10, and Cash App will also donate $10 to First, an organization that is helping to advance robotics and STEM education for young people around the world.

本期由ExpressVPN赞助，访问expressvpn.com/lexpod获取折扣并支持本播客。我使用ExpressVPN多年，操作简便令人称道。

This show is presented by ExpressVPN. Get it at expressvpn.com/lexpod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's really easy to use.

只需按下显眼的电源按钮，隐私保护即刻开启。您还可将虚拟定位设为全球任意地点，这带来诸多显著优势，比如访问日本版Netflix或英国Hulu等国际流媒体。ExpressVPN兼容您能想到的所有设备。

Press the big power on button, and your privacy is protected. And if you like, you can make it look like your location is anywhere else in the world. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or The UK Hulu. ExpressVPN works on any device you can imagine.

我在Linux系统上使用它，特别推荐Ubuntu。实际上新版本即将发布。Windows、Android也适用，但其他平台同样可用。再次提醒，访问expressvpn.com/lexpod获取折扣并支持本播客。

I use it on Linux. Shout out to Ubuntu. New version coming out soon, actually. Windows, Android, but it's available anywhere else too. Once again, get it at expressvpn.com/lexpod to get a discount and to support this podcast.

现在请收听我与史蒂芬·沃尔夫勒姆的对话。

And now here's my conversation with Stephen Wolfram.

你和儿子克里斯托弗共同为电影《降临》设计了外星语言。请允许我问个可能有点疯狂的问题：如果有外星人造访地球，你认为我们能找到共通的语言吗？

You and your son, Christopher, helped create the alien language in the movie Arrival. So let me ask maybe a bit of a crazy question. But if aliens were to visit us on Earth, do you think we would be able to find a common language?

当我们假设外星人来访时，其实已经预设了整个故事框架。因为‘外星人亲自造访’这个概念本身，就意味着我们默认了双方处于相似的物理维度——不是无线电信号，而是实体存在。

Well, by the time we're saying aliens are visiting us, we've already prejudiced the whole story. Because the concept of an alien actually visiting, so to speak, we already know the kind of things that make sense to talk about visiting. So we already know they exist in the same kind of physical setup that we do. It's not just radio signals. It's an actual thing that shows up and so on.

关于沟通的可能性，目前最好的参照是人工智能。这是我们首次接触的‘外星智能’。关键在于：我们如何与AI交流？假如你打开神经网络问‘你在想什么’——

So I think in terms of can one find ways to communicate? Well, the best example we have of this right now is AI. I mean, that's our first sort of example of alien intelligence. And the question is, how well do we communicate with AI? If you were in the middle of a neural net, and you open it up, and it's like, what are you thinking?

能否与之讨论？虽不简单但并非绝无可能。基于‘外星造访’这个前提，我认为答案是肯定的。总能找到某种沟通形式——无论‘沟通’如何定义，毕竟这涉及意图认知等哲学层面。

Can you discuss things with it? It's not easy, but it's not absolutely impossible. So I think I think by the time but given the setup of your question, aliens visiting, I think the answer is yes. One will be able to find some form of communication, whatever communication means. Communication requires notions of purpose and things like this.

这就像个哲学沼泽。

It's a kind of philosophical quagmire.

那么，如果AI是一种外星生命形式，你认为访问会是什么样子？如果我们想象外星人来访，稍后我们会讨论计算和计算的世界，但如果你要想象，你说你已经通过使用‘访问’这个词预设了一些前提。那么外星人会如何访问呢？

So if AI is a kind of alien life form, what do you think visiting looks like? So if we look at aliens visiting, and we'll get to discuss computation and and the world of computation, but if you were to imagine, you said you already prejudiced something by saying you visit, But what how would aliens visit?

说到‘访问’，这里隐含了一种意味，我们正在使用人类语言的不精确性。在未来世界中，如果用计算语言表达，我们或许能查阅‘访问’的概念文档，准确理解其含义和属性等。但在日常人类语言中，我倾向于认为‘访问’意味着某种物理实体乘坐飞船出现，因为我们知道这是必要的。我们不是在想象仅仅是无线电信号中的光子，或某种复杂模式的光子，而是想象由原子等构成的物理实体出现。

By visit, there's kind of an implication, and here we're using the imprecision of human language. You know, in a world of the future, and if that's represented in computational language, we might be able to take the concept visit and go look in the documentation, basically, and find out exactly what does that mean, what properties does it have, and so on. But by visit, in ordinary human language, I'm kind of taking it to be there's, you know, something, a physical embodiment that shows up in a spacecraft, since we kind of know that that's necessary. We're not imagining it's just photons showing up in a radio signal, photons in some very elaborate pattern. We're imagining it's physical things made of atoms and so on that show up.

可以是某种模式的光子吗？

Can it be photons in a pattern?

这是个好问题。关键在于是否存在这种可能性。什么才算智能？好问题。我曾经认为发现外星智能的意义会很明确，等等。

Well, that's a good question. I mean, whether there is the possibility. What counts as intelligence? Good question. And I used to think there was sort of a, oh, it'll be clear what it means to find extraterrestrial intelligence, etcetera, etcetera, etcetera.

随着科学研究的深入，我越来越意识到，所谓智能与纯粹计算之间其实并没有明确的界限。在日常讨论中，我们会说‘天气有自己的想法’。让我们拆解这个问题：大气中决定流体动力学的计算过程，与我们大脑中发生的物理过程有何区别？

I've increasingly realized, as a result of science that I've done, that there really isn't a bright line between the intelligent and the merely computational, so to speak. So in our kind of everyday discussion, we'll say things like, the weather has a mind of its own. Well, let's unpack that question. We realize that there are computational processes that go on that determine the fluid dynamics of this and that in the atmosphere, etcetera, etcetera, etcetera. How do we distinguish that from the processes that go on in our brains, the physical processes that go on in our brains?

我们如何区分它们？如何判定天气中代表复杂计算的物理过程，与我们大脑中代表复杂计算的物理过程不同？我认为根本不存在本质区别。对我们而言，区别在于有一条历史线索将不同大脑的活动联系起来，而天气现象则没有这种文明历史的线索与我们习惯的事物相连。

How do we separate those? How do we say the physical processes going on that represent sophisticated computations in the weather, oh, that's not the same as the physical processes that go on that represent sophisticated computations in our brains. The answer is, I don't think there is a fundamental distinction. I think the distinction for us is that there's kind of a thread of history and so on that connects kind of what happens in different brains to each other, so to speak. And what happens in the weather is something which is not connected by sort of a thread of civilizational history, so to speak, to what we're used to.

在我们的故事里，在人脑讲述的故事里——但也许天气有它自己的故事...

In our story, in the stories that the human brain has told us, but maybe the weather has its own stories that

确实如此。这就是我们在思考外星智慧时遇到的难题，就像那颗脉冲星的磁层产生的复杂无线电信号——我们是否该将其视为历经数百万年中子星演化过程形成的完整文明？这与我们所熟知的人类智慧截然不同。我认为，当人们讨论外星智慧何在、费米悖论为何宇宙中不见其他智慧迹象时，最终我们会发现面对的是两种异类智慧形式：人工智能与物理（或外星）智慧。而我的推测是，人们终将接受这两者几乎同时实现的事实。

Absolutely. Tells And that's where we run into trouble thinking about extraterrestrial intelligence, because, it's like that pulsar magnetosphere that's generating these very elaborate radio signals. Is that something that we should think of as being this whole civilization that's developed over the last however long millions of years of processes going on in the neutron star or whatever versus what we're used to in human intelligence. I think in the end, when people talk about extraterrestrial intelligence and where is it and the whole Fermi paradox of how come there's no other signs of intelligence in the universe, my guess is that we've got sort of two alien forms of intelligence that we're dealing with: artificial intelligence and physical or extraterrestrial intelligence. And my guess is people will get comfortable with the fact that both of these have been achieved around the same time.

换言之，人们会说：是的，我们已习惯自己创造的计算机和数字产物具有类人智慧；同时也会逐渐接受宇宙中存在其他类人智慧体——只是它们没有我们这样的文明史。它们如同进化树上的不同分支。这就像讨论生命时，你几乎将生命形式与智慧等同——虽然人工智能听到这种等式可能会抗议。

And in other words, people will say, well, yes, we're used to computers, things we've created, digital things we've created, being sort of intelligent like we are. And they'll say, oh, we're kind of also used to the idea that there are things around the universe that are kind of intelligent like we are, except they don't share the sort of civilizational history that we have. And so we don't they're different branch. I mean, it's similar to when you talk about life, for instance. I mean, you kind of said life form, I think, almost synonymously with intelligence, which I don't think is the AIs would be upset to hear you equate those

可能特指生物生命体。

really probably implied biological life.

对，没错。

Right. Right.

但你的意思是——我们稍后会深入探讨——你认为这其实是个光谱，所有智慧本质上都是某种计算形式。整个光谱连续存在，我们只是通过编织叙事，让自己这类计算显得特殊。

But you're saying I mean, we'll explore this more, but you're saying it's really a spectrum, it's all just a kind of computation. And so it's a full spectrum, and we just make ourselves special by weaving a narrative around our particular kinds of computation.

正是。我逐渐认识到，某种程度上令人沮丧的是：我们实在没什么特别之处。

Yes. I mean, the thing that I think I've kind of come to realize is, you know, at some level, it's a little depressing to realize that there's so little that's special.

或者说解放性的。嗯，确实。

Or liberating. Well, yeah.

但这就是科学的故事。从哥白尼开始，我们先是坚信自己的行星是宇宙的中心。不，那不是真的。然后我们又确信，作为生物有机体，我们的化学构成非常特殊。不，那也不完全正确。

But it's the story of science. From Copernicus on, it's like, first, we were convinced our planets are the center of the universe. No, that's not true. Well, then we were convinced there's something very special about the chemistry that we have as biological organisms. No, that's not really true.

接着我们仍抱持着希望，哦，我们拥有的这种智能特质，那才是真正独特的。我认为并非如此。不过从某种意义上说，正如你所言，这反而是一种解放：你意识到独特之处在于我们自身的细节，而非某些抽象属性——我们可能会想，哦，是否会有其他事物也具备那种抽象属性？是的，我们拥有的每个抽象属性，其他事物也可能拥有。但我们文明历史的完整细节，没有其他事物能与之相同。

And then we're still holding out that hope, oh, this intelligence thing we have, that's really special. I don't think it is. However, in a sense, as you say, it's kind of liberating for the following reason: that you realize that what's special is the details of us, not some abstract attribute that we could wonder, oh, is something else gonna come along and also have that abstract attribute? Well, yes, every abstract attribute we have, something else has it. But the full details of our history of our civilization and so on, nothing else has that.

可以说，那是我们的故事。这几乎从定义上就是独特的。所以我最初觉得这很糟糕，觉得这有点...你知道，我们该如何对所做的事保持自尊？后来我意识到，我们所做之事的细节本身，就是故事。

That's our story, so to speak. And that's almost by definition special. So I view it as not being such a Initially, was like, this is bad. This is this is kind of you know, how can we have self respect about about the things that we do? Then I realized the details of the things we do, they are the story.

其他一切都像是一张空白画布。

Everything else is kind of a blank canvas.

或许稍微跑个题，你刚才让我想到——你怎么看待《2001太空漫游》中的黑色方碑？就外星人与我们沟通并激发人类特有智能计算能力这点而言。从这部科幻作品中能得出什么有趣的见解吗？

So maybe on a small tangent, you just made me think of it, but what do you make of the monoliths in February space odyssey in terms of aliens communicating with us and sparking the the kind of particular intelligent computation that we humans have. Is there anything interesting to get from that sci fi

是的。我觉得有趣之处在于，那些方碑是1:4:9完美比例的长方体。在百万年前的地球上，或者电影描绘的猿人时代，那种完美程度的东西显得格格不入，明显是经过高度构造和设计的。这是个值得思考的问题。

Yeah. I mean, I think what's what's fun about that is, you know, the monoliths are these, you know, one to four to nine perfect cuboid things. And in the Earth of a million years ago, or whatever they were portraying with a bunch of apes and so on, a thing that has that level of perfection seems out of place. It seems very constructed, very engineered. So that's an interesting question.

所谓的'技术特征'是什么？就是当你看到某物时会惊叹'这绝对是 engineered 的'。事实上，我们也看到晶体——它们同样非常完美，尤其是那些完美的晶体，呈现出漂亮的多面体形态。

What's the techno signature, so to speak? What is it that you see it somewhere and you say, my gosh, that had to be engineered? Now, the fact is, we see crystals, which are also very perfect. And the perfect ones are very perfect. They're nice polyhedra or whatever.

从这个意义上说，如果你认为完美的多边形或多面体形状是一种技术特征标志，那是不准确的。因此，这就引出了一个有趣的问题：什么才是正确的特征标志？比如著名数学家高斯，

And so in that sense, if you say, well, it's a sign of it's a techno signature that it's a perfect polygonal shape, polyhedral shape. That's not true. And so then it's an interesting question. What is the right signature? Mean, like Gauss, famous mathematician.

他曾有个想法，认为应该将西伯利亚森林砍伐成勾股定理证明的经典图形，理由是这很酷。虽然最终未实施，但依据他的理论，火星人看到后会惊叹地球存在数学家。这可能是对人类文明成就的最佳宣传方式。不过这个问题确实值得探讨。

He had this idea, you should cut down the Siberian forest in the shape of a typical image of the proof of the Pythagorean theorem on the grounds that it was a kind of cool idea. Didn't get done. But, you know, was on the grounds that the Martians would see that and realize, gosh, there are mathematicians out there. It's kind of in his theory of the world, that was probably the best advertisement for the cultural achievements of our species. But it's a reasonable question.

我们能够发送或创造什么，才能在其形成过程中体现智能，甚至展现创造意图？

What can you send or create that is a sign of intelligence in its creation or even intention in its creation?

是的。你在讨论如果我们要发送信标，应该发送什么？数学是我们最伟大的创造吗？什么才是我们最伟大的创造？

Yeah. You talk about if we were to send a beacon, can you can you what what should we send? Is math our greatest creation? Is what is our greatest creation?

我认为这是个哲学上注定无解的问题。我们发送自认为非凡的东西，但本质上我们属于宇宙的一部分。我们创造的——包括那些构成我们本质的计算行为——在抽象层面上看，其实在宇宙中异常普遍。我们可能以为自己是经过层层工程技术才达到微处理器水平，才能进行复杂计算。

I think I think it's a it's a philosophically doomed issue. So, I mean, in other words, you send something, you think it's fantastic, but it's kind of like we are part of the universe. We make things that are, things that happen in the universe. Computation, which is sort of the thing that we are, in some abstract sense, using to create all these elaborate things we create, is surprisingly ubiquitous. In other words, we might have thought that we've built this whole giant engineering stack that's led us to microprocessors, that's led us to be able to do elaborate computations.

但计算行为无处不在，关键问题在于是否存在将人类意图与这些计算联系起来的线索。因此，关于如何最好地展示人类文明这个问题，我认为我们生产的任何随机产物都与其他东西具有同等代表性。这属于那种...

But this idea that computations are happening all over the place. The only question is whether there's a thread that connects our human intentions to what those computations are. And so I think this question of what do you send to show off our civilization in the best possible way, I think any kind of almost random slab of stuff we've produced is about equivalent to everything else. I think it's one of these things where

这种表述方式真不够浪漫。抱歉打断——我刚和卡尔·萨根的夫人安·德鲁扬聊过。嗯哼。不知道你是否熟悉旅行者号项目...她当时参与了...哦对的。

Such a nonromantic way of phrasing it. I just sorry to interrupt, but I just talked to Anne Druann, who's the wife of Carl Sagan. Uh-huh. And so I don't I don't know if you're familiar with the Voyager. Mean, she was part of Oh, yeah.

发送的，我想是，脑电波，你知道的，我想要

Sending, I think, brainwaves of, you know, I want

那是她的吗？

to Was it hers?

是她的。她爱上卡尔·萨根初期时的脑电波。对吧？所以这是个美丽的故事。没错。

It was hers. Her her brainwaves when she was first falling in love with Carl Sagan. Right? So this beautiful story. Right.

也许你会通过说‘我们不如发送其他任何东西’来削弱那种力量，这很有趣。所有这些都是一种有趣的奇特现象。是的。是的。好吧，我是说，想想它是

That that perhaps you would shut down the power of that by saying we might as well send anything else, and that's interesting. All of it is kind of an interesting peculiar thing that's Yeah. Yeah. Right. Well, I mean, think it's

看看旅行者号上的金唱片挺有意思的。其中一个可爱之处在于它制作于70年代末、80年代初？而且，它是一张留声机唱片。上面还有如何播放留声机唱片的图示。令人震惊的是，仅仅三十年后，如果你把这个图示给现在的随便一个孩子看——我做过这个实验——他们会说，我完全不知道这是什么。

kind of interesting to see on the on the Voyager, you know, Golden Record thing. One of the things that's kind of cute about that is it was made, when was it, in the late '70s, early '80s? And one of the things, it's a phonograph record. And it has a diagram of how to play a phonograph record. And it's shocking that in just thirty years, if you show that to a random kid of today and you show them that diagram, and I've tried this experiment, they're like, I don't know what the heck this is.

而人们能想到的最好办法是，把整张唱片数字化，别管它有什么螺旋轨道，直接成像整个东西看看里面有什么。这就是我们今天会做的。仅仅三十年，我们的技术已经发展到播放留声机唱片上的机械螺旋轨道现在成了件怪事。所以这是个警示故事，我认为，关于制作某种能详细引导外星人或任何存在做某事的能力。就像我说的，如今我们不会造个带唱针的螺旋扫描装置。

And the best anybody can think of is, take the whole record, forget the fact that it has some kind of helical track in it, just image the whole thing and see what's there. That's what we would do today. In only thirty years, our technology has kind of advanced to the point where the playing of a helical, mechanical track on a phonograph record is now something bizarre. So that's a cautionary tale, I would say, in terms of the ability to make something that, in detail, sort of leads by the nose some of the aliens or whatever to do something. It's like, no, best you can do, as I say, if we were doing this today, we would not build a helical scan thing with a needle.

我们会直接用高分辨率成像系统获取所有数据位，然后说，哦，他们弄成螺旋形真麻烦。我们就把螺旋展开从头开始吧。你认为这会涉及到尝试理解AI的可解释性、计算的可解释性，以及能与各类计算进行沟通的能力。

We would just take some high resolution imaging system and get all the bits off it and say, oh, it's a big nuisance that they put in a helix, you know, in a spiral. Let's just unravel the spiral and start from there. Do you think and this will get into trying to figure out interpretability of AI, interpretability of computation, being able to communicate with various kinds of computations.

你觉得如果我们戴上你的外星人帽子，能不能研究出这张唱片该怎么播放？

Do you think we'd be able to, if you put put your alien hat on, figure out this record, how to play this record?

嗯，这取决于人们想要做什么。

Well, it's a question of what one wants to do.

我是说，理解对方试图传达的内容，或者了解关于对方的任何信息。

I mean Understand what the other party was trying to communicate or understand anything about the other party

这就是理解的本质吗？我是说，问题就在这里。这就像人们试图让计算机理解自然语言一样。对吧？人们为此努力了很多年。

that's understanding mean? I mean, that's the issue. The issue is it's like when people were trying to do natural language understanding for computers. Right? So people tried to do that for years.

但它的意义并不明确。换句话说，你拿出一段英语或其他语言，然后说，哇，我的电脑理解了。好吧，这很好。但你能用它做什么呢？比如，当我们开发Wolf Malfa时，其中一个功能就是问答系统，它需要进行自然语言理解。

It wasn't clear what it meant. In other words, you take your piece of English or whatever, and you say, gosh, my computer has understood this. Okay, that's nice. What can you do with that? Well, so for example, when we built Wolf Malfa, one of the things was it's doing question answering and so on, and it needs to do natural language understanding.

事后我才意识到，我们能够很好地实现自然语言理解而其他人之前做不到的原因，首要的一点是我们有一个明确的目标。我们试图将自然语言转化为计算语言，这样我们就可以用它来做事情。同样地，当你想象自己是外星人时，你会说，好吧，我们在给他们播放唱片。他们理解了吗？

The reason that I realized after the fact, the reason we were able to do natural language understanding quite well and people hadn't before, the number one thing was we had an actual objective for the natural language understanding. We were trying to turn the natural language Into computation. Into this computational language that we could then do things with. Now, similarly, when you imagine you're alien, you say, okay, we're playing them the record. Did they understand it?

嗯，这取决于你的意思。如果他们有一种表达方式，如果它能转化为某种我们可以识别的表达方式，表示他们理解了，那就很好。但实际上，我认为唯一能代表理解的表达方式是那些之后能做出我们人类认为对我们有用的事情的表达方式。

Well, depends what you mean. If they you know, if we if there's a representation that they have, if it converts to some representation where we can say, oh, yes, that's a representation that we can recognize represents understanding, then all well and good. But actually, the only ones that I think we can say would represent understanding are ones that will then do things that we humans kind of recognize as being useful to us.

嗯。也许试图理解并量化这个特定文明的技术先进程度。那么从军事角度看，他们对我们构成威胁吗？是的，是的。

Mhmm. Maybe trying to under understand, quantify how technologically advanced this particular civilization is. So are they a threat to us from a military perspective? Yeah. Yeah.

这可能是他们最初感兴趣的那种理解。天哪。

That's probably the kind of first kind of understanding they'll be interested in. Gosh.

这太难了。我是说，就像《降临》电影里那样。关键问题之一就是，你知道，用他们的话说，你们为什么来这里？是的。还有你们会伤害我们吗？

That's so hard. I mean, that's like in the Arrival movie. That was sort of one of the key questions is is, you know, why are you here, so to speak? Yeah. And it's Are you gonna hurt us?

对。但即便是这个问题，你知道，也非常模糊。比如你们会伤害我们吗？这引申出许多有趣的AI伦理问题，因为我们可能创造一个AI说，以自动驾驶汽车为例，你会伤害我们吗？

Right. But even that is, you know, it's very unclear. Know, it's like are you gonna hurt us? That comes back to a lot of interesting AI ethics questions because we might make an AI that says, well, take autonomous cars, for instance. Are you going to hurt us?

好吧，让我们确保你只严格按照限速行驶，因为我们想确保不会伤害你，可以这么说。因为这样...然后，你知道，但你说，但这实际上意味着我会迟到，这在某种程度上也伤害了我。所以很难界定。甚至伤害某人这个定义本身就不明确。当我们开始思考AI伦理等问题时，这是必须解决的问题。

Well, let's make sure you only drive at precisely the speed limit, because we want to make sure we don't hurt you, so to speak. Because that's some and then, well, something, you know, but you say, but actually that means I'm going be really late for this thing, and that sort of hurts me in some way. So it's hard to know. Even even the definition of what it means to hurt someone is unclear. And as we start thinking about things about AI ethics and so on, that's, you know, something one has to address.

总是需要权衡取舍，这就是伦理令人头疼的地方。是啊，没错。

There's always trade offs, and that's the annoying thing about ethics. Yeah. Well, right.

我认为伦理就像我们讨论的其他问题一样，是极其人性化的东西。不存在抽象的，比如说写下证明某种行为伦理正确的定理。这种想法毫无意义。你需要一个所谓的'基本事实'，归根结底是人类想要什么。而他们的诉求并不相同。

And I mean, I think ethics, like these other things we're talking about, is a deeply human thing. There's no abstract, you know, let's write down the theorem that proves that this is ethically correct. That's a meaningless idea. You know, you have to have a ground truth, so to speak, that's ultimately sort of what humans want. And they don't all want the same thing.

因此，这给人们在思考这个问题时带来了各种额外的复杂性。将伦理转化为计算的一个便利之处在于，

So that gives one all kinds of additional complexity in thinking about that. One convenient thing in terms of turning ethics into computation,

你可以提出一个问题：什么能最大化物种生存的可能性？

you can ask the question of what maximizes the likelihood of the survival of the species.

是的。这是个很好的存在主义问题。但是，当你说物种的生存时，你可能会说，比如说，忘掉技术，只是悠闲地生活，快乐地过日子，繁衍下一代，经历许多代，某种意义上什么都没发生。这样行吗？

Yeah. That's a that's a good existential issue. Yeah. But then when you say survival of the species, right, you might say you might, for example for example, let's say forget about technology, just hang out and be happy, live our lives, go on to the next generation, go through many, many generations where, in a sense, nothing is happening. Is that Okay?

这样不行吗？很难判断，试图做复杂的事情可能反而对物种的生存不利。比如，这也有些难以确定，好吧，我们把这当作一个思想实验。你可以问，我们需要应对哪些生存威胁？超级火山、小行星撞击等等。

Is that not Okay? Hard to know in terms of the attempt to do elaborate things and the attempt to might be counterproductive for the survival of the species. Like, for instance, think it's also a little bit hard to know, so Okay, let's take that as a sort of thought experiment. You can say, well, what are the threats that we might have to survive? The supervolcano, the asteroid impact, all these kinds of things.

好，现在我们列举这些可能的威胁，我们说，让我们尽可能增强物种对这些威胁的抵抗力。我认为最终，这是一个无法预知的事情，需要什么条件。既然你有了这个AI，并告诉它要最大化长期效益，那么‘长期’是什么意思？是指直到太阳燃尽吗？那行不通。是指未来一千年吗？

Okay, so now we inventory these possible threats, we say, let's make our species as robust as possible relative to all these threats. I think in the end, it's sort of an unknowable thing, what it takes to So given that you've got this AI, and you've told it maximize the long term, what does long term mean? Does long term mean until the sun burns out? That's not going to work. Does long term mean next thousand years?

好，可能有一些针对未来一千年的优化策略，就像经营一家公司。你可以让公司在某段时间内非常稳定。比如，如果你的公司被某个私募集团收购，你可以通过停止所有研发，让公司平稳运行五年，公司最终会衰落，但短期内会运作良好。所以，如果你告诉AI，让人类安稳度过一千年，可能会采取一些优化措施，其中许多可能会让人觉得，这对历史的未来来说是个巨大的遗憾。但最终，当你思考这个问题时，你会发现存在大量不可判定性和计算不可约性。

Okay, there are probably optimizations for the next thousand years that it's like if you're running a company. You can make a company be very stable for a certain period of time. Like if your company gets bought by some private investment group, you can run a company just fine for five years by just taking what it does and removing all R and D, and the company will burn out after a while, but it'll run just fine for a little while. So if you tell the AI, keep the humans Okay for one thousand years, there's probably a certain set of things that one would do to optimize that, many of which one might say, well, that would be a pretty big shame for the future of history, so to speak, for that to be what happens. But I think in the end, as you start thinking about that question, what you realize is there's a whole raft of undecidability, computational irreducibility.

换句话说，我们的文明和我们人类经历的一个好处在于，它具有一定的计算不可约性，即你无法仅从外部观察就断言‘答案会是这个’。归根结底，你必须经历这个过程才能知道结果。我认为这既是——感觉上更好，因为通过这一过程确实有所成就。

In other words, one of the good things about what our civilization has gone through and what we humans go through is that there's a certain computational irreducibility to it, in the sense that it isn't the case that you can look from the outside and just say, The answer is going to be this. At the end of the day, this is what's going to happen. You actually have to go through the process to find out. And I think that's both. That feels better in the sense it's not a something is achieved by going through all of this process.

但这同时也意味着，当我们告诉AI去推算出最佳结果时，遗憾的是，它很可能会反馈说这几乎是无法决定的。我们需要运行所有可能的情景才能看到结果。而如果我们想要预测无限未来的话，就立刻会陷入无限计算这类标准问题之中。

But it also means that telling the AI, go figure out what will be the best outcome, well, unfortunately, it's going to come back and say, it's kind of undecidable what to do. We'd have to run all of those scenarios to see what happens. And if we want it for the infinite future, we're thrown immediately into sort of standard issues of kind of infinite computation and so on.

所以，即便你得知宇宙和万物的答案是42，你仍然需要实际运行整个宇宙才能验证。是的。

So, yeah, even if you get that the answer to the universe and everything is 42, you still have to actually run the universe Yes. To

推算。是的。

figure Yes. Out

是的。我想问题或者说旅程本身就是意义所在，对吧。

Yes. Like, question, I guess, or the the, you know, the the journey is is the point. Right.

我认为这是在总结性地说明：这就是宇宙运行的结果。如果这确实可能，那么它告诉我们——关于计算的整个思维框架，以及事物运作的方式——如果能断言答案是某个特定值，就等于说存在超越宇宙的认知方式。这会让你陷入某种悖论，因为这意味着答案的可认知性建立在超越宇宙提供的认知维度之上。但如果我们能知晓这个答案，那么我们面对的某种东西就已经超越了宇宙本身。

Well, I think it's saying, to summarize, this is the result of the universe. Yeah. That's if that is possible, it tells us, I mean, the whole sort of structure of thinking about computation and so on, and thinking about how stuff works, if it's possible to say, and the answer is such and such, you're basically saying there's a way of going outside the universe. And you're getting yourself into something of a paradox, because you're saying, if it's knowable what the answer is, then there's a way to know it that is beyond what the universe provides. But if we can know it, then something that we're dealing with is beyond the universe.

那么严格来说，这个宇宙就不再是完整的宇宙了。

So then the universe isn't the universe, so to speak.

所以总的来说，至少对于我们渺小的人类大脑而言，要展示足够复杂计算的结果是困难的——我的意思是这很可能是不可能的，就像不可判定性问题。嗯。而宇宙至少在诗人眼中足够复杂，使得我们永远无法...

So And in general, as as as we'll talk about, at least for small human brains, it's hard to show the the result of a sufficiently complex computation. It's hard I mean, it's probably impossible, right, undecidability. So Uh-huh. And the universe appears by at least the poets to be sufficiently complex that we won't be able

去

to

预测这一切究竟会走向何方。

predict what the heck it's all going to.

嗯，我们最好做不到这一点，因为如果我们能预测，某种程度上就否定了——我是说，要知道，我们也是宇宙的一部分。是啊。那么对我们来说预测意味着什么？意味着我们这个小部分宇宙能超越整个宇宙的进程。这很快就会陷入悖论。

Well, we better not be able to, because if we can, it kind of denies I mean, it's you know, we're part of the universe. Yeah. So what does it mean for us to predict? It means that we that our little part of the universe is able to jump ahead of the whole universe. And this quickly winds up.

我的意思是，虽然可以想象。我们唯一能预测的可能性是，如果我们在宇宙中如此特殊，我们是宇宙中唯一拥有比其他任何存在都更特殊、更复杂计算能力的地方。只有这样我们才可能具备这种近乎神学的能力，可以这么说，去预测宇宙中发生的事情，这等于是说我们比宇宙中其他一切都优越，而我认为事实并非如此。

I mean, it is conceivable. The only way we would be able to predict is if we are so special in the universe, we are the one place where there is computation more special, more sophisticated than anything else that exists in the universe. That's the only way we would have the ability to the almost theological ability, so to speak, to predict what happens in the universe, is to say somehow we're better than everything else in the universe, which I don't think is the case.

是啊。也许我们能检测到大量在宇宙中反复出现的循环模式并完整描述它们，但即便如此，要理解这些模式如何相互作用以及会产生何种复杂性仍然异常困难。嗯，这...

Yeah. Perhaps we can detect a large number of looping patterns that reoccur throughout the universe and fully describe them, and therefore but then it's it's still becomes exceptionally difficult to see how those patterns interact and what kind of complexity Well, it

听着，宇宙最非凡之处在于它居然存在规律性。本来可能并非如此。

look, the most remarkable thing about the universe is that it has regularity at all. Might not be the case.

它真的存在规律性吗？

Does it have regularity?

确实如此。物理学是成功的。它充满了各种定律，详细告诉我们宇宙如何运作。理论上，宇宙中10的90次方个粒子可能各行其是，但它们并非如此。

Absolutely. Physics is successful. It's full of laws that tell us a lot of detail about how the universe works. It could be the case that the 10 to the ninetieth particles in the universe, they all do their own thing. But they don't.

它们都遵循我们已经知晓的规律。基本上都遵循相同的物理定律，这是关于宇宙的一个非常深刻的事实。你从中得出什么结论尚不明确。早期的神学家们将此视为上帝存在的首要证据。如今人们对此有不同的解读，但事实是，目前我恰好对此很感兴趣。

They all follow we already know. They all follow basically the same physical laws, and that's a very profound fact about the universe. What conclusion you draw from that is unclear. I mean, in the early theologians, that was exhibit number one for the existence of God. Now, people have different conclusions about it, but the fact is, right now, I happen to be interested, actually.

我最近重新燃起了对基础物理学的长期兴趣。我正在开展一项探索——即将公开更多细节——试图寻找物理学的根本理论。

I've just restarted a long running kind of interest of mine about fundamental physics. I'm on a bit of a quest, which I'm about to make more public, to see if I can actually find the fundamental theory of physics.

太棒了。我们会谈到这个，我刚与量子力学领域的专家们进行了大量对话，所以特别期待你的见解。因为我认为你对现实本质的物理学视角有着迷人见解，尤其是关于当下物理学认知背后可能存在的深层原理。好的，让我们退一步思考。

Excellent. We'll come to that, and I just had a lot of conversations with quantum mechanics folks with so I'm really excited on your take, because I think you have a fascinating take on the the fundamental nature of our reality from a physics perspective. So and what might be underlying the kind of physics as we think of it today. Okay. Let's take a step back.

什么是计算？

What is computation?

这是个好问题。从操作层面说，计算就是遵循规则。大致如此。计算是结果，是系统性地遵循规则的过程，当你

It's a good question. Operationally, computation is following rules. That's kind of it. I mean, computation is the result, is the process of systematically following rules, and it is the thing that happens when you

执行这个过程时。即获取初始条件和输入数据后遵循规则。但规则是作用于什么的？所以必须存在某些数据，某些

do that. So taking initial conditions and taking inputs and following rules. I mean, what are you following rules on? So there has to be some data, some

未必如此。可以存在一种情况，输入极其简单，你只需遵循这些规则，你会说这里并没有太多数据输入。实际上，你完全可以将初始条件打包到规则中。所以我认为问题在于，是否存在一个稳健的计算概念？这里的‘稳健’究竟意味着什么？

Not necessarily. It can be something where there's very simple input, and then you're following these rules, and you'd say there's not really much data going into this. You could actually pack the initial conditions into the rule if you want to. So I think the the question is, is there a robust notion of computation? That is What does robust mean?

我指的是类似这样的概念。在物理学领域，比如能量这个概念。明白吗？能量有不同形式，但能量本身是一个稳健的概念，并不专属于动能、核能或其他特定类型。

What I mean by that is something like this. So so one of the things in a different in the area of physics, something like energy. Okay? There are different forms of energy. But somehow energy is a robust concept that isn't particular to kinetic energy or nuclear energy or whatever else.

能量存在一个稳健的核心定义。因此你可能要问：计算是否也存在这样的稳健概念？或者说，这个计算是在图灵机中运行，在CMOS硅基CPU中运行，还是在天气系统的流体中运行——这些具体载体是否重要？

There's a robust idea of energy. So one of the things you might ask is, does the robust idea of computation? Or does it matter that this computation is running in a Turing machine? This computation is running in a CMOS silicon CPU. This computation is running in fluid system in the weather, those kinds of things.

还是说存在一种超越具体运行框架的、更本质的计算概念？确实如此。要知道这个概念并非显而易见，因此有必要了解我们如何发展到当前认知。因为承认这种稳健概念的存在，某种程度上也是对我们宇宙本质的阐述。

Or is there a robust idea of computation that transcends the sort of detailed framework that it's running in? Is that? Yes. I mean, it wasn't obvious that there was, so it's worth understanding the history and how we got to where we are right now. Because to say that there is is a statement in part about our universe.

这并非关于数学可能性的陈述

It's not a statement about what is

而是关于我们实际能观测到的存在。或许你也可以谈谈：能量作为概念是稳健的，但它与物质、质量之间错综复杂的关系非常有趣——传递力的粒子与具有质量的粒子，这些概念在数学层面上似乎存在对应关系。那么计算与能量、质量之间是否存在关联？还是说它们完全是独立的概念？

mathematically conceivable. It's about what actually can exist for us. Maybe you can also comment because energy as a concept is robust, but there's also its intricate complicated relationship with matter, with mass, is is very interesting, of particles that carry force and particles that sort of particles that carry force and particles that have mass. These kinds of ideas, they seem to map to each other, at least in the in the mathematical sense. Is there a connection between energy and mass and computation, or are these completely disjoint ideas?

目前尚未可知。

We don't know yet.

我目前在基础物理学领域的探索很可能会导向这种关联，但目前尚未发现已知的联系。

The things that I'm trying to do about fundamental physics may well lead to such a connection, but there is no known connection at this time.

那么能否请您详细阐述一下您对计算的看法？计算究竟是什么？

So can you elaborate a little bit more on what how do you think about computation? What is computation?

好的。让我们先回顾一段历史。大约一百五十年前，人们制造了各种机械计算器。

Yeah. So, I mean, let's let's tell a little bit of a historical story. Yes. Okay? So, you know, back go back one hundred and fifty years, people were making mechanical calculators of various kinds.

典型的情况是：你需要加法机？就去加法机专卖店。需要乘法机？就去乘法机专卖店。这些都是不同的硬件设备。

And the typical thing was, you want an adding machine? You go to the adding machine store, basically. You want a multiplying machine? You go to the multiplying machine store. There are different pieces of hardware.

这意味着至少在那种计算层次和硬件类型上，并不存在统一的计算概念。加法机有加法机的计算方式，乘法机有乘法机的计算方式，它们彼此割裂。到了1900年左右，人们开始设想——特别是在数理逻辑领域——能否创造一种能表示任何合理函数的东西？他们提出了一些构想，原始递归就是早期概念之一，但并未成功。

And so that means that, at least at the level of that kind of computation and those kinds of pieces of hardware, there isn't a robust notion of computation. There's the adding machine kind of computation, there's the multiplying machine notion of computation, and they're disjoint. So what happened in around 1900, people started imagining, particularly in the context of mathematical logic, could you have something which would represent any reasonable function? They came up with things. This idea of primitive recursion was one of the early ideas, and it didn't work.

当时人们能构想出一些无法用原始递归基本要素表示的合理函数。随后1931年哥德尔定理问世。回溯来看，在证明哥德尔定理的过程中，哥德尔实质上展示了如何将算术编译化——如何将'这个命题不可证'之类的逻辑陈述编译成算术表达式。他本质上证明了算术可以成为某种意义上的计算机，能够表征各类其他事物。

There were reasonable functions that people could come up with that were not represented using the primitives of primitive recursion. Okay? So then along comes 1931 and Godel's theorem and so on. And looking back, one can see that as part of the process of establishing Godel's theorem, Godel basically showed how you could compile arithmetic, how you could basically compile logical statements like this statement is unprovable into arithmetic. So what he essentially did was to show that arithmetic can be a computer in a sense that's capable of representing all kinds of other things.

接着图灵登场。1936年他提出图灵机概念，同时阿隆佐·邱奇创立了λ演算。很快人们惊讶地发现，图灵机对计算的界定与λ演算的计算概念完全等价。之后又陆续出现了寄存器机等其他计算表征形式。

And then Turing came along. 1936 came up with Turing machines. Meanwhile, Alonso Church had come up with lambda calculus. And the surprising thing that was established very quickly is the Turing machine idea about what computation might be is exactly the same as the lambda calculus idea of what computation might be. And then there started to be other ideas, register machines, other representations kinds of computation.

而最大的惊喜是它们全都被证明是等价的。换句话说，原本可能像那些老式加法机和乘法机一样，图灵有他对计算的理解，丘奇有他对计算的理解，它们只是不同而已。但事实并非如此。它们实际上是等价的。因此到了大约20世纪70年代，计算机科学、计算理论领域的人们开始认为，图灵机某种程度上定义了计算的本质。

And the big surprise was they all turned out to be equivalent. So in other words, it might have been the case, like those old adding machines and multiplying machines, that Turing had his idea of computation, Church had his idea of computation, and they were just different. But it isn't true. They're actually all equivalent. So then by, I would say, the 1970s or so, sort of the computer science, computation theory area, people had sort of said, oh, Turing machines are kind of what computation is.

物理学家们仍持反对意见，声称不，不，宇宙根本不是这样运作的。我们有这些微分方程。我们有这些拥有无限位数的实数。是的，宇宙不是一台图灵机。对吧。

Physicists were still holding out, saying, no, no, that's just not how the universe works. We've got all these differential equations. We've got all these real numbers that have infinite numbers of digits. Yeah, the universe is not a Turing machine. Right.

图灵机只是我们在微处理器和工程结构中制造的事物中的一小部分。因此，实际上通过我在20世纪80年代关于计算与物理模型关系的研究，物理学中可能发生的事物与图灵机之类的事物之间存在巨大二分法的观点变得不那么明确了。我想现在大多数人会认为，顺便提一下，大脑也是这一问题的另一个要素。哥德尔不认为他的计算概念或相当于他的计算概念能涵盖大脑。图灵对此也不确定。

The Turing machines are a small subset of the things that we make in microprocessors and engineering structures and so on. So probably, actually through my work in the 1980s about the relationship between computation and models of physics, it became a little less clear that there would be that there was this big dichotomy between what can happen in physics and what happens in things like Turing machines. And I think probably by now, people would mostly think by the way, brains were another kind of element of this. Godel didn't think that his notion of computation or what amounted to his notion of computation would cover brains. And Turing wasn't sure either.

尽管他逐渐有点被说服它应该涵盖大脑。但我想说，大约在20世纪80年代的某个时候，开始有一种普遍的信念认为，是的，这种可以被图灵机等事物捕捉的计算概念是相当稳健的。现在，下一个问题是，好吧，你可以有一台通用图灵机，它能被编程执行任何图灵机能做的事。这种通用计算的概念是一个重要的概念。这种你可以拥有一件硬件并通过不同的软件来编程它的想法，某种程度上是催生大多数现代技术的理念。

Although he got to be a little bit more convinced that it should cover brains. But I would say by probably sometime in the 1980s, there was beginning to be a general belief that, yes, this notion of computation that could be captured by things like Turing machines was reasonably robust. Now, the next question is, okay, you can have a universal Turing machine that's capable of being programmed to do anything that any Turing machine can do. And this idea of universal computation, it's an important idea. This idea that you can have one piece of hardware and program it with different pieces of software, that's kind of the idea that launched most modern technology.

我的意思是，那是引发计算机革命、软件等的理念。所以是个重要的理念。但这个理念中仍有些坚持的是，好吧，有这种通用计算的东西，但似乎很难达到。看起来如果你想制造一台通用计算机，你必须有一个包含百万个门的微处理器，你必须费很大劲才能制造出达到那种计算复杂程度的东西。好吧，所以对我来说的惊喜是我在80年代初研究这些被称为细胞自动机的非常简单的计算系统时发现的，对我来说最大的惊喜是，即使它们的规则非常非常简单，它们所做的事情与规则复杂得多时一样复杂。

I mean, that's the idea that launched computer revolution software, etcetera. So important idea. But the thing that's still kind of holding out from that idea is, Okay, there is this universal computation thing, but it seems hard to get to. It seems like you want to make a universal computer, you have to kind of have a microprocessor with a million gates in it, and you have to go to a lot of trouble to make something that achieves that level of computational sophistication. Okay, so the surprise for me was the stuff that I discovered in the early '80s, looking at these things called cellular automata, which are really simple computational systems, the thing that was a big surprise to me was that even when their rules were very, very simple, they were doing things that were as sophisticated as they did when their rules were much more complicated.

所以看起来这种想法，哦，要获得复杂的计算，你必须构建具有非常复杂规则的东西，这种想法似乎没有实现。相反，情况似乎是复杂的计算无处不在，即使在规则极其简单的系统中也是如此。因此，这导致了我称之为计算等价原理的东西，它基本上是说，当你有一个遵循任何规则的系统时，只要系统不是在某种意义上明显简单的事情，那么系统行为对应的计算就具有同等的复杂性。这意味着当你从你能想象的最最简单的事物开始时，很快你就会达到一个阈值，超过这个阈值，一切在计算复杂性上都是等价的。并不明显情况会是这样的。

So it didn't look like this idea, oh, to get sophisticated computation, you have to build something with very sophisticated rules, that idea didn't seem to pan out. And instead, it seemed to be the case that sophisticated computation was completely ubiquitous, even in systems with incredibly simple rules. And so that led to this thing that I call the principle of computational equivalence, which basically says, when you have a system that follows rules of any kind, then whenever the system isn't doing things that are in some sense obviously simple, then the computation that the behavior of the system corresponds to is of equivalent sophistication. So that means that when you go from the very, very, very simplest things you can imagine, then quite quickly you hit this kind of threshold above which everything is equivalent in its computational sophistication. Not obvious that would be the case.

我的意思是，这是一个科学事实。好吧

I mean, that's a a science fact. Well

不，不，不。等一下。你这样做是开启了一种新的科学。

No. No. No. Hold on a second. You so this you've opened with a new kind of science.

我是说，我记得这是一个巨大的启示，如此简单的事物能创造出如此复杂的现象。是的，存在等价性，但这并非事实。它只是看起来像——我的意思是，就像这些理论如此优雅，以至于似乎这就是事物的本质。但让我问问你刚才提到的，比如计算机科学家群体与他们的图灵机，物理学家与他们的宇宙，还有那些——也许是研究大脑的神经科学家。你对这种等价性有何看法？通过你的工作，你已经展示了简单规则可以创造出同等复杂的图灵机系统。

I I mean, I remember it was a huge eye opener that such simple things can create such complexity, and, yes, there's an equivalent, but it's not a fact. It just appears to I mean, as much as a fact as sort of these theories are so elegant that it it seems to be the way things are. But let me ask sort of you just brought up previously kinda like the communities of computer scientists with their Turing machines, the physicists with their universe, and the the whoever the heck, maybe neuroscientists looking at the brain. What's your sense in the equivalence? So you you've shown through your work that simple rules can create equivalently complex Turing machine systems.

对吧？宇宙是否等同于图灵机？人类大脑是否是一种图灵机？你是否认为这些事物本质上正在融合，还是它们之间仍存在某种神秘的分歧？

Right? Is the universe equivalent to the kinds of to Turing machines? Is the human brain a kind of Turing machine? Do you see those things basically blending together, or is there still a mystery about how disjoint they are?

嗯，我的猜测是它们都会融合在一起。但我们还不能确定。我是说，我应该说明，我之前轻率地说计算等价原理有点像科学事实。我用‘科学事实’这个词时是加了引号的。因为当你——我的意思是，稍微讨论一下这个，我们就会明白，它具有复杂的认识论特征，类似于热力学第二定律，即熵增定律。

Well, my guess is that they all blend together. But we don't know that for sure yet. I mean, I should say, I said rather glibly that the principle of computational equivalence is sort of a science fact. I was using air for the science fact. Because when you it is I mean, just to talk about that for a second, then we'll we'll the thing is that it is it has a complicated epistemological character, similar to things like the second law of thermodynamics, the law of entropy increase.

热力学第二定律是什么？是自然法则吗？是物理世界真实存在的东西吗？是数学上可证明的吗？还是恰好适用于我们在世界上看到的系统？

What is the second law of thermodynamics? Is a law of nature? Is it a thing that is true of the physical world? Is something which is mathematically provable? Is it something which happens to be true of the systems that we see in the world?

在某种意义上，它是否可能是热的定义？好吧，它是这些因素的结合。计算等价原理也是如此。在某种意义上，计算等价原理是计算定义的核心，因为它告诉你存在一个东西，一个在所有系统中都等价且不依赖于单个系统细节的稳健概念。这就是为什么我们可以有意义地谈论‘计算’这个东西。

Is it, in some sense, a definition of heat, perhaps? Well, it's a combination of those things. And it's the same thing with the principle of computational equivalence. And in some sense, the principle of computational equivalence is at the heart of the definition of computation, because it's telling you there is a thing, there is a robust notion that is equivalent across all these systems and doesn't depend on the details of each individual system. And that's why we can meaningfully talk about a thing called computation.

我们不会陷入讨论‘哦，在图灵机第3,785号中存在计算’等等。这就是为什么存在这样一个稳健的概念。另一方面，我们能证明计算等价原理吗？能把它作为一个数学结果来证明吗？实际上，我们已经在这方面取得了一些不错的成果，表明随便给我一个规则非常简单的随机系统。

And we're not stuck talking about, oh, there's computation in Turing machine number 3,785 and etcetera, etcetera, etcetera. That's why there is a robust notion like that. Now, on the other hand, can we prove the principle of computational equivalence? Can we prove it as a mathematical result? Well, the answer is, actually, we've got some nice results along those lines that say, throw me a random system with very simple rules.

好吧，在几个案例中，我们现在知道，即便是我们能想到的某类最简单的规则也具有通用性，某种程度上遵循了计算等价原理的预期。这是对计算等价原理的一个很好的数学证据。

Well, in a couple of cases, we now know that even the very simplest rules we can imagine of a certain type are universal and do sort of follow what you would expect from the principle of computational equivalence. So that's a nice piece of mathematical evidence for the principle of computational equivalence.

就这一点来说，简单的规则产生了这些复杂行为。但是否有数学方法可以证明这种行为是复杂的？你提到过你跨越了一个阈值。

Just to link on that point, the simple rules creating sort of these complex behaviors. But is there a way to mathematically say that this behavior is complex? That you've you mentioned that you cross a threshold.

对。有多种指标。比如，一个标准是它是否具备通用计算能力？也就是说，给定这个系统，是否存在可以设置的初始条件，本质上能代表程序执行任何你想要的操作：计算质数、计算圆周率，做任何你想做的事。这就是一个指标。

Right. Is there There are various indicators. So, for example, one thing would be, is it capable of universal computation? That is, given the system, do there exist initial conditions for the system that can be set up to essentially represent programs to do anything you want: to compute primes, to compute pi, to do whatever you want. So that's an indicator.

我们在几个例子中了解到，是的，那些可能具备该属性的最简单候选者确实拥有该属性。这正是计算等价原理可能暗示的。但关于这个原理的一个问题是：它对于物理世界是否成立？它可能对我们构想的所有事物都成立：图灵机、细胞自动机等等。但它对我们的实际物理世界成立吗？

So we know in a couple of examples that, yes, the simplest candidates that could conceivably have that property do have that property. And that's what the principle of computational equivalence might suggest. But this principle of computational equivalence, one question about it is: is it true for the physical world? It might be true for all these things we come up with: the Turing machines, the cellular automata, whatever else. Is it true for our actual physical world?

它对于作为物理世界一部分的大脑成立吗？我们并不确定，这不是那种会有明确答案的问题，因为存在一种科学归纳的问题。你可以说，好吧，它对所有这些大脑都成立，但这边这个人非常特别，对他们不成立。唯一能避免这种情况的方式是，如果我们最终确定并真正获得物理学的基本理论，并且它对应于，比如说，一个简单的程序。如果是这样，那么我们基本上已将物理学简化为数学的一个分支，因为我们现在对物理学的理解是，这是适用于这里的规则。

Is it true for the brains, which are an element of the physical world? We don't know for sure, and that's not the type of question that we will have a definitive answer to, because there's a sort of scientific induction issue. You can say, well, it's true for all these brains, but this person over here is really special, and it's not true for them. And you can't the only way that that cannot be what happens is if we finally nail it and actually get a fundamental theory for physics and it turns out to correspond to, let's say, a simple program. If that is the case, then we will basically have reduced physics to a branch of mathematics in the sense that we will not be right now with physics, we're like, well, this is the theory that this is the rules that apply here.

但在那中间，就在那个黑洞旁边，也许这些规则不适用，而是其他规则适用，可能还有另一层洋葱皮需要我们剥开。但如果我们能达到这一点，即我们实际上拥有物理学的基本理论，就是这个程序，运行这个程序，你将得到我们的宇宙，那么我们已将物理学中探索事物的问题简化为解决一些非常困难、本质上难以解决的数学问题。但不再有人能进来并说，哎呀，你对图灵机的这些看法是对的，但对物理宇宙的看法是错的。我们知道物理宇宙中发生的事情有某种基本真相。现在，你问我的时机很有趣，因为我正开始重新启动我的物理学基本理论研究项目。

But in the middle of that, right by that black hole, maybe these rules don't apply and something else applies, and there may be another piece of the onion that we have to peel back. But if we can get to the point where we actually have this is the fundamental theory of physics, here it is, it's this program, run this program, and you will get our universe, then we've kind of reduced the problem of figuring out things in physics to a problem of doing some what turns out to be very difficult, irreducibly difficult mathematical problems. But it no longer is the case that we can say that somebody can come in and say, whoops, you were right about all these things about Turing machines, but you're wrong about the physical universe. We know there's sort of ground truth about what's happening in the physical universe. Now, I happen to think you asked me at an interesting time because I'm just in the middle of starting to reenergize my project to study the fundamental theory of physics.

截至目前，我非常乐观地认为我们实际上会发现一些东西，并且有可能看到宇宙在那种意义上是计算性的。但我不知道，因为可以说，我们是在与宇宙对赌。这不像我一生中大部分时间都在构建技术，然后我知道里面有什么。它可能有意外行为，可能有错误等等，但根本上，我知道里面有什么。

As of today, I'm very optimistic that we're actually going to find something and that it's going to be possible to see that the universe really is computational in that sense. But I don't know, because we're betting against the universe, so to speak. And it's not like, you know, when I spend a lot of my life building technology, and then I know what's in there. Right? And it's there may be it may have unexpected behavior, it may have bugs, things like that, but fundamentally, I know what's in there.

就宇宙而言，可以说我并未处于那样的立场。

For the universe, I'm not in that position, so to speak.

你认为物理学基本定律可能源自何种计算？为了澄清这一点，你在离散计算领域做了大量引人入胜的工作，比如细胞自动机——我们稍后会讨论——它们具有非常清晰的结构。这是展示简单规则能创造巨大复杂性的绝佳范例。但问题是，细胞自动机是否足够普适，能够描述可能生成物理定律的那类计算？能否请你概述一下，你认为什么样的计算会创造出

What kind of computation do you think the fundamental laws of physics might emerge from? So just to clarify, so there's you've you've done a lot of fascinating work with kind of discrete kinds of computation that, you know, the because cellular automata, and we'll talk about it, have this very clean structure. It's such a nice way to demonstrate that simple rules can create immense complexity. But what know, is that actually are cellular autonomous sufficiently general to describe the kinds of computation that might create the laws of physics? Just to give can you give a sense of what kind of computation do you think would create

物理定律？这是个稍显复杂的问题，因为一旦具备通用计算能力，原则上任何事物都能模拟任何事物。但这并非自然发生的过程。如果你问的是：若要在所有可能程序构成的计算宇宙中寻找对应我们物理宇宙的程序，这些程序是否足够短小简单，使得我们通过搜索计算宇宙就能发现它们？我们必须拥有正确的基准，可以这么说。

the laws of physics? This is a slightly complicated issue, because as soon as you have universal computation, you can, in principle, simulate anything with anything. But it is not a natural thing to do. And if you're asking, were you to try to find our physical universe by looking at possible programs in the computational universe of all possible programs, would the ones that correspond to our universe be small and simple enough that we might find them by searching that computational universe? We've got to have the right basis, so to speak.

实际上，我们需要合适的语言来描述计算，才能实现这一目标。因此我长期关注的问题是：通过计算能构建的最具结构性的结构是什么？例如，细胞自动机由排列在网格上的众多单元构成，每个单元都在时钟滴答声（可以这么说）中同步更新——所有单元同时发生变化。这是非常特定且严格的形式。但我猜测，当我们观察物理现象，审视时空等概念时，时空底层应该是尽可能无结构的。

We've got to have the right language, in effect, for describing computation for that to be feasible. So the thing that I've been interested in for a long time is, what are the most structuralist structures that we can create with computation? So in other words, if you say a cellular automaton has a bunch of cells that are arrayed on a grid, and every cell is updated in synchrony at a particular when there's a click of a clock, so to speak, it goes, a tick of a clock, and every cell gets updated at the same time. That's a very specific, very rigid kind of thing. But my guess is that when we look at physics and we look at things like space and time, that what's underneath space and time is something as structureless as possible.

我们所见到的物理空间等涌现现象，其实源自底层某种近乎任意无结构的基质。所以我长期探索的问题是：我们能建立的最具结构性的结构是什么？实际上我多年来的思考是使用图论中的网络结构——以空间为例，空间究竟是什么？这是个值得探讨的问题。

That what we see, what emerges for us as physical space, for example, comes from something that is sort of arbitrarily unstructured underneath. And so I've been, for a long time, interested in what are the most structuralist structures that we can set up. And actually, what I had thought about for ages is using graphs, networks, where essentially so let's talk about space, for example. So what is space? Is a of a question one might ask.

比如在量子力学早期，人们断言空间必然是离散的，因为他们发现的其他事物都是离散的。但这在物理学中从未得到验证。如今物理学始终将空间视为连续存在，就像欧几里得构想的那样——他在《几何原本》开篇就定义：点是没有部分的东西。换言之，存在任意小的点，点的位置构成连续统。但问题是：这真的正确吗？

Back in the early days of quantum mechanics, for example, people said, oh, for sure, space is going to be discrete because all these other things we're finding are discrete. But that never worked out in physics. And so space and physics today is always treated as this continuous thing, just like Euclid imagined I mean, the very first thing Euclid says in his common notions is, a point is something which has no part. In other words, there are points that are arbitrarily small, and there's a continuum of possible positions of points. And the question is, is that true?

例如观察空气或水这类流体时，我们可能认为它们是连续介质——可以倾倒，能进行各种连续操作。但实际上根据物理学认知，它们由大量离散分子碰撞组成，仅在宏观层面表现出连续性。因此空间很可能同样如此。

And so for example, if we look at, I don't know, fluid like air or water, we might say, oh, it's a continuous fluid. We can pour it. We can do all kinds of things continuously. But actually, we know, because we know the physics of it, that it consists of a bunch of discrete molecules bouncing around, and only in the aggregate is it behaving like a continuum. And so the possibility exists that that's true of space, too.

人们尚未能在现有框架和物理定律下实现这一点，但我一直好奇，是否可想象在空间与时间之下存在某种更无结构性的基础。问题在于：它是否具有计算性质？这里存在几种可能性。它可能是计算性的，在根本上等同于图灵机；亦或本质上并非如此。

People haven't managed to make that work with existing frameworks and physics, But I've been interested in whether one can imagine that underneath space and also underneath time is something more structureless. And the question is, is it computational? So there are a couple of possibilities. It could be computational, somehow fundamentally equivalent to a Turing machine. Or it could be fundamentally not.

那么它如何可能不具备计算性？图灵机本质上处理的是整数层面的问题，它能执行诸如给数字加一之类的操作。

So how could it not be? It could not be so a Turing machine essentially deals with integers, whole numbers, at some level. And it can do things like it can add one to a number. It can do things like this.

它还能存储所有执行过的操作。

And it can also store whatever the heck it did.

是的，拥有无限存储能力。但当思考物理学或理想化的数学时，我们需要处理实数——那些拥有无限位数、绝对精确的数字。比如我们可以取一个数并让它自乘。

Yes. Has an infinite storage. But when one thinks about doing physics or sort of idealized physics or idealized mathematics, one can deal with real numbers, numbers with an infinite number of digits. Numbers which are absolutely precise, and one can say, we can take this number and we can multiply it by itself.

在这个语境下，你对'无限'这个概念感到自在吗？在计算的语境中呢？

Are you comfortable with infinity in this context? Are you comfortable in in the context of computation?

你认为无限性起作用吗？我认为无限的作用很复杂。它在概念化事物时很有用，但无法被实际实现——几乎从定义上就决定了这一点。

Do you think infinity plays a part? I think that the role of infinity is complicated. Infinity is useful in conceptualizing things. It's not actualizable. Almost by definition, it's not actualizable.

但你认为无限性可能是物理定律底层基础的一部分吗？

But do you think infinity is part of the thing that might underlie the laws of physics?

我认为不是。我觉得你提出的许多问题，比如关于物理学的，不可避免地会涉及无限性。比如当你问，超光速旅行是否可能？你可以说，根据物理定律，能否制造出任意大甚至无限大的装置来实现超光速旅行？这时你就不得不将无限性作为理论问题来处理。

I think that no. I think there are many questions that you ask about, you might ask about physics, which inevitably involve infinity. Like, when you say, is faster than light travel possible? You could say, given the laws of physics, can you make something even arbitrarily large, even infinitely large, that will make faster than light travel possible? Then you're thrown into dealing with infinity as theoretical question.

但谈到时空之下的本质以及如何构建计算基础设施，一种可能性是我们无法以图灵机的意义构建计算基础设施，而必须处理精确的实数。我们面对的是偏微分方程，它们在任意接近的点上都有精确的实数值。万物皆连续。或许现实就是如此——万物皆以连续统形式存在，所有事物都由精确实数描述，那么我的想法就错了。研究自然规律就要承担这种风险，你可能会犯错。

But talking about what's underneath space and time and how one can make a computational infrastructure, one possibility is that you can't make a computational infrastructure in a Turing machine sense, that you really have to be dealing with precise real numbers. You're dealing with partial differential equations, which have precise real numbers at arbitrarily closely separated points. You have a continuum for everything. Could be that that's what happens, that there's sort of a continuum for everything and precise real numbers for everything, and then the things I'm thinking about are wrong. And that's the risk you take if you're trying to do things about nature, is you might just be wrong.

对我个人而言，这是些奇特的事。我大半生都在研发技术，你可以做出无人问津的东西，但从某种意义上你不会出错——技术造出来就能实现既定功能。但关于宇宙潜在计算基础设施的问题，它必然相当抽象。因为如果宇宙模型是简单的，你不可能为三维空间、电子、μ子、夸克等每个现象都编写一行代码，不可能为μ子、τ轻子等每个案例单独编程。

For me personally, it's kind of strange things. I've spent a lot of my life building technology where you can do something that nobody cares about, but you can't be sort of wrong in that sense, in the sense you build your technology and it does what it does. But I think this question of what the sort of underlying computational infrastructure of the universe might be, So it's sort of inevitable it's gonna be fairly abstract. Because if you're gonna get all these things like there are three dimensions of space, there are electrons, there are muons, there are quarks, there are this, You don't get to if the if the model for the universe is simple, you don't get to have sort of a line of code for each of those things. You don't get to have sort of the the the muon case, the tau lepton case, and so on.

所有这些现象都必须是某种更深层机制的涌现结果。对吧。所以需要更本质的东西。这意味着我们很难具体讨论这个潜在的底层结构究竟是什么。

All of those are have to be emergent somehow. Right. So Something deeper. Right. So so that means it's sort of inevitable that it's a little hard to talk about what the sort of underlying structuralist structure actually is.

你觉得

Do you

我们人类是否具备认知能力去理解——假如真被我们发现的话——那些能涌现出物理定律的简单结构？比如，你认为

think our human beings have the cognitive capacity to understand, if we're to discover it, to understand the kinds of simple structure from which these laws can emerge? Like, do you

这是个好问题吗？探索嘛。我是这么想的：此刻我正深陷其中研究这个问题。所以我告诉你...你认为你会

think that's a good question? Pursuit. Well, here's what I think. I think that, I mean, I'm right in the middle of this right now. So I'm telling you that I You think you will

建一堵墙。

get a wall.

是的。我的意思是，这个人类很难理解正在发生的许多事情。但在理解过程中，我们会建立路标。比如，如果你说要理解从五万年前计数发明开始的现代二十一世纪数学，那会非常困难。但我们通过建立路标，让自己能够达到更高层次的理解。

Yeah. I mean, this human has a hard time understanding, you know, a bunch of the things that are going on. But what happens in understanding is one builds waypoints. I mean, if you said, understand modern twenty first century mathematics starting from counting back in whenever counting was invented fifty thousand years ago, whatever it was, that would be really difficult. But what happens is we build waypoints that allow us to get to higher levels of understanding.

我们在语言中也看到同样的情况。当我们为某物发明一个词时，它就提供了一个认知锚点，就像播客这样的路标。你可以解释说，它是这样或那样运作的东西。但一旦有了'播客'这个词且社会普遍理解它，你就能在此基础上继续构建。这实际上也是科学发展的故事。

And we see the same thing happening in language. When we invent a word for something, it provides a cognitive anchor, a waypoint that lets us like a podcast or something. You could be explaining, well, it's a thing which works this way, that way, the other way. But as soon as you have the word podcast and people societally understand it, you start to be able to build on top of that. That's the story of science, actually, too.

科学就是关于建立这些路标——当我们找到理解某事的认知机制后，就能在此基础上发展。比如微分方程的概念，我们可以基于它继续发展。所以我的希望是，如果必须从沙子直接到计算机而没有中间路标，那我们就完了。我们做不到这一点。

Science is about building these waypoints where we find this cognitive mechanism for understanding something, then we can build on top of it. We have the idea of, I don't know, differential equations we can build on top of that. We have this idea or that idea. So my hope is that if it is the case that we have to go all the way from the sand to the computer and there's no waypoints in between, then we're toast. We won't be able to do that.

嗯，最终或许可以。如果我们这些聪明的猿类足够擅长构建那些抽象之上的抽象，最终就能从沙子造出计算机。对吧？只是这条路可能会更长些。

Well, eventually, might. So if we're if we're us clever apes are good enough at building those abstract abstractions, eventually, from sand, we'll get to the computer. Right? And it just might be a longer journey

问题在于，这是否是人类大脑能够'理解'的事情。这是个不同的问题。因为这需要我们能构建人类可理解的叙事步骤。对此我持一定希望，尽管就今天而言，我仍面临许多难以理解的事物。

than The question is whether it is something that you ask whether our human brains will will, quotes, understand what's going on. And that's a different question. Because for that, it requires steps that are are from which we can construct a human understandable narrative. And that's something that I think I am somewhat hopeful that that will be possible. Although, as of literally today, if you ask me, I'm confronted with things that I don't understand very well.

所以这就是

So this is

计算中试图理解其运行规则的一个小模式。这是一个有趣的可能性，即这类计算中的生物能否理解自身。

a small pattern in a computation trying to understand the rules under which the computation functions. It's an interesting possibility under which kinds of computations such a creature can understand itself.

我的猜想是，虽然我们没怎么讨论计算不可约性，但这是计算等价原理的必然结果。我认为这是必须理解的核心概念：问题在于，当你进行一项计算时，你可以通过逐步运行计算来观察结果，或者说尝试跳步预测——用更聪明的方式预判未来走向。传统科学很大程度上依赖于这种计算可约性行为，比如我们通过解方程就能预知结果。

My guess is that within so we didn't talk much about computational irreducibility, but it's a consequence of this principle of computational equivalence. And it's sort of a core idea that one has to understand, I think, which is: the question is, you're doing a computation, you can figure out what happens in the computation just by running every step in the computation and seeing what happens. Or you can say, let me jump ahead and figure out, have something smarter that figures out what's going to happen before it actually happens. And a lot of traditional science has been about that act of computational reducibility. It's like we've got these equations, and we can just solve them, and we can figure out what's going to happen.

我们不必追踪所有步骤，解方程就能直达答案。但计算等价原理带来的启示是：你并非总能如此。绝大多数系统都具有计算不可约性——唯有逐步执行才能知晓其行为。原因何在？

We don't have to trace all of those steps. We just jump ahead because we solve these equations. So one of the things that is a consequence of the principle of computational equivalence is you don't always get to do that. Many, many systems will be computationally irreducible in the sense that the only way to find out what they do is just follow each step and see what happens. Why is that?

假设你认为人类大脑更聪明，不必像元胞自动机那样逐个更新细胞状态，可以直接跃迁思考。但如果计算等价原理成立，这种认知就是错误的——因为人脑运算与元胞自动机运算本质等价。这意味着我们并不比元胞自动机更聪明，两者的计算复杂度处于同一层级。

Well, if you're saying, well, we, with our brains, we're a lot smarter. We don't have to mess around like the little cellular automaton going through and updating all those cells. We can just use the power of our brains to jump ahead. But if the principle of computational equivalence is right, that's not going to be correct, because it means that there's us doing our computation in our brains, there's a little cellular automaton doing its computation, and the principle of computational equivalence says these two computations are fundamentally equivalent. So that means we don't get to say we're a lot smarter than the cellular automaton and jump ahead, cause we're just doing computation that's of the same sophistication as the cellular automaton itself.

这就是计算可约性。这个强大概念既令人沮丧又发人深省——我们与元胞自动机本质相同。但当前讨论的物理基本法则，其实是反向命题。

That's computational reducibility. It's fascinating. And that's a really powerful idea. I think that's both depressing and humbling and so on, that we're all we in the cellular automata are the same. But the question we're talking about, the fundamental laws of physics, is kind of the reverse question.

你不是在预测未来（那需要运行整个宇宙），而是在追问：能否理解生成自我的潜在规则？

You're not predicting what's going to happen, you have to run the universe for that, But saying, can I understand what rules likely generated me?

我明白。但问题在于：要验证正确性就需要计算可约性，因为我们嵌在宇宙中。若验证宇宙规律的唯一方法是重演宇宙历程——这显然不可能，毕竟宇宙已运行146亿年。因此我们必须寄望于存在足够的计算可约性区域，让我们能断言'那里确实是电子'。我认为这正是计算不可约性的特征。

I I understand. But the problem is, to know whether you're right, you have to have some computational reducibility, because we are embedded in the universe. If the only way to know whether we get the universe is just to run the universe, we don't get to do that because it just ran for fourteen point six billion years or whatever, and we can't rerun it, so to speak. So we have to hope that there are pockets of computational reducibility sufficient to be able to say, yes, I can recognize those are electrons there. And I think that it's a feature of computational irreducibility.

从数学特性来看，总存在无数个可简化的小区域。关键在于这些小区域是否能落在正确位置，以及我们能否基于它们构建理论，目前尚不明确。但关于我们作为宇宙中的观察者，由宇宙相同物质构成，能否理解宇宙这一问题，正依赖于这些可简化的小区域。没有这些可简化区域，这一机制就无法运作。我认为，关于观察者如何运作的问题，尤其是过去百年科学发展的特征之一在于：每次我们对观察者的认知更趋实际，就能对科学多一分理解。

It's sort of a mathematical feature that there are always an infinite collection of pockets of reducibility. The question of whether they land in the right place and whether we can sort of build a theory based on them is unclear. But to this point about whether we, as observers in the universe built out of the same stuff as the universe, can figure out the universe, so to speak, that relies on these pockets of reducibility. Without the pockets of reducibility, it won't work, can't work. But I think this question about how observers operate, it's one of the features of science over the last hundred years particularly, has been that every time we get more realistic about observers, we learn a bit more about science.

例如，相对论的核心在于观察者无法断言事件的绝对同时性——他们必须等待光信号到达才能判定。又如在热力学中，观察者无法确定气体中每个分子的具体位置，只能观测宏观特征，这正是热力学第二定律（熵增定律等）成立的原因。若能观测每个独立分子，反而无法得出热力学结论。

So for example, relativity was all about observers don't get to say what's simultaneous with what. They have to just wait for the light signal to arrive to decide what's simultaneous. Or, for example, in thermodynamics, observers don't get to say the position of every single molecule in a gas. They can only see the kind of large scale features, and that's why the second law of thermodynamics, law of entropy increase, and so on works. If you could see every individual molecule, you wouldn't conclude something about thermodynamics.

你只会看到分子在做特定运动，无法察觉宏观规律。因此我强烈认为——事实上在我的理论中也体现——必须更实际地考虑观察者的计算能力等维度，才能真正建立与我们体验的对应关系。目前我和团队正在研究量子力学可能的工作机制，这是个极其奇妙的构想：人类意识线索如何与宇宙观测现象相关联。不过这需要分步骤解释。

You would conclude, oh, these molecules are just all doing these particular things. You wouldn't be able to see this aggregate fact. So I strongly expect that, and in fact, in the theories that I have, that one has to be more realistic about the computation and other aspects of observers in order to actually make a correspondence between what we experience. In fact, my little team and I have a little theory right now about how quantum mechanics may work, which is a very wonderfully bizarre idea about how the sort of thread of human consciousness relates to what we observe in the universe. But there's several steps to explain what that's about.

你如何看待量子力学底层观察者概念的混乱？教科书式的量子力学定义似乎暗示存在两个世界：一个是真实存在的世界，另一个是被观测的世界。你如何理解这种...

What do you make of the mess of the observer at the lower level of quantum mechanics? Sort of the textbook definition with quantum mechanics kind of says that there's some there's two worlds. One is the world that actually is, and the other is that's observed. Do what do you make sense of that kind

实际上，我们近期的想法可能为此提供突破口——虽然尚不确定。我认为现状确实混乱。有趣的是，当人们审视我三十年前提出的那些模型时，总会说'这不可能正确，量子力学怎么办？'

I of think, actually, the ideas we've recently had might actually give away into this. And that's I don't know yet. I think it's a mess. The fact is, there is a one of the things that's interesting, and when people look at these models that I started talking about thirty years ago now, they say, oh, no, that can't possibly be right. What about quantum mechanics?

这时我会问：请告诉我量子力学的本质是什么？你们希望我重现什么特征来证明我掌握了量子力学？这个问题在量子计算实践中尤为突出——当我们对接那些宣称拥有量子计算机的企业API并尝试运行时...

You say, Okay, tell me what is the essence of quantum mechanics? What do you want me to be able to reproduce to know that I've got quantum mechanics, so to speak? Well, and that question comes up very operationally, actually, because we've been doing a bunch of stuff with quantum computing. And there are all these companies that say, we have a quantum computer. And we say, let's connect to your API, and let's actually run it.

他们往往回应'暂时不要操作，我们尚未准备就绪'。我始终好奇的是：若给我五分钟操作量子计算机，如何判断它是真量子计算机还是远端模拟器？事实证明极难区分——就像界定'何为智能''何为生命'这类命题一样困难。

And they're like, well, maybe you shouldn't do that yet. We're not quite ready yet. And one of the questions that I've been curious about is, if I have five minutes with a quantum computer, how can I tell if it's really a quantum computer or whether it's a simulator at the other end? And turns out it's really hard. It turns out there isn't it's like a lot of these questions about what is intelligence, what's life.

这是对量子计算机的Doring测试。

That's a Doring test for a quantum computer.

没错，没错。就像在问，你真的是量子计算机吗？我是说，只是模拟。对，正是如此。

That's right. That's right. It's like, are you really a quantum computer? I mean, just simulation. Yes, exactly.

这仅仅是模拟，还是真正的量子计算机？老问题又来了。所以这整个关于量子力学数学结构的问题，以及与之完全分离的、我们经验中认为确定事件发生的层面——而量子力学从未断言有确定事件发生。量子力学全是关于不同事件发生的振幅。然而，我们的意识流却仿佛确定事件正在发生般运作。

Is it just a simulation, or is it really a quantum computer? Same issue all over again. So this whole issue about the mathematical structure of quantum mechanics and the completely separate thing that is our experience in which we think definite things happen, whereas quantum mechanics doesn't say definite things ever happen. Quantum mechanics is all about the amplitudes for different things to happen. But yet, our thread of consciousness operates as if definite things are happening.

联系到你提到的观点，你提到了可能作为万物基础的结构，以及它可能具有类似图结构的想法。嗯。能否详细说明为何你的直觉认为存在节点与边的图结构，以及它可能代表什么？

To link on the point, you've kind of mentioned the structure that could underlie everything and this idea that it could perhaps have something like a structure of a graph. Mhmm. Can you elaborate why your intuition is that there's a graph structure of nodes and edges and what it might represent?

好的。那么问题是，从某种意义上说，你能想象的最具结构主义特征的结构是什么？对吧？实际上，我最近一年左右意识到，我有了新的最结构主义的结构。

Right. Okay. So the question is, what is, in a sense, the most structuralist structure you can imagine? Right? So and in fact, what I've recently realized in the last year or so, I have a new most structuralist structure.

顺便说，这个问题本身就很美且极具力量。即便没有答案，单是这个问题就非常深刻。

By the way, the question itself is a beautiful one and a powerful one in itself. So even without an answer, just the question is a really strong question.

对，对。

Right. Right.

但你的新想法是什么？

But what's your new idea?

嗯，它与超图有关。本质上，我现在这个模型的有趣之处有点像计算领域发生的情况。每当我想到，哦，也许模型是这样，结果发现它们是等价的。这相当令人鼓舞，因为就像我可以说，好吧，我要看每个节点有三条边的三价图等等。或者我可以看这种特殊的图。

Well, it has to do with hypergraphs. Essentially, what what is interesting about the sort of model I have now is a little bit like what happened with computation. Everything that I think of as, oh, well, maybe the model is this, I discover it's equivalent. And that's quite encouraging, because it's like I could say, well, I'm gonna look at trivalent graphs with three edges for each node and so on. Or I could look at this special kind of graph.

或者我可以看这种代数结构。结果发现，我现在研究的东西，所有我能想象到的、看似合理的结构主义结构，都与这个等价。那么它是什么？通常的思考方式是，你可能有一些元组的集合，比如数字的集合。比如你有1、3、5、2、3、4，就是数字的集合，三元组、四元组、二元组等等。

Or I could look at this kind of algebraic structure. And turns out that the things I'm now looking at, everything that I've imagined that is a plausible type of structuralist structure is equivalent to this. So what is it? Well, a typical way to think about it is, well, so you might have some collection of tuples, collection of, let's say, numbers. So you might have one, three, five, two, three, four, just collections of numbers, triples of numbers, let's say, quadruples of numbers, pairs of numbers, whatever.

你有所有这些漂浮的小元组。它们没有特定的顺序。这种漂浮的元组集合，我告诉过你这是抽象的，代表了整个宇宙。唯一将它们联系起来的是当符号相同时，它们就是相同的，可以这么说。所以如果你有两个元组，它们包含相同的符号，比如元组的相同位置，元组的第一个元素，那就代表了一种关系。

And you have all these floating little tuples. They're not in any particular order. And that sort of floating collection of tuples and I told you this was abstract represents the whole universe. The only thing that relates them is when a symbol is the same, it's the same, so to speak. So if you have two tuples and they contain the same symbol, let's say, the same position of the tuple, the first element of the tuple, then that represents a relation.

好的。让我——

Okay. So let me let

我来试着拆解一下。哇。好吧。这真是——

me try and peel this back. Wow. Okay. It's just

我告诉过你这是抽象的，但这就是——这就是——所以

I told you it's abstract, but this is this is the this is So

这种关系是由某些相同方面的相似性形成的。

the relationship is formed by the same some aspect of sameness.

对。但是，用图的概念来思考这个问题。一个图由许多节点组成，假设我们给每个节点编号，明白吗？

Right. But but so think about it in terms of a graph. So a graph, a bunch of nodes. Let's say you number each node. Okay?

那么图是什么？图是一组表示这个节点与另一个节点有边连接的配对集合。所以图就是这些表示节点间连接关系的配对的集合。而这个概念是对图的泛化，用任意的n元组替代了简单的配对。就是这样。

Then what is a graph? A graph is a set of pairs that say this node has an edge connecting it to this other node. So that's the that's and a graph is just a a collection of those pairs that say this node connects to this other node. So this is a generalization of that, in which instead of having pairs, you have arbitrary n tuples. That's it.

这就是全部内容。现在的问题是，这如何表示宇宙的状态？宇宙如何演化？宇宙在做什么？答案是我正在研究这些超图上的转换规则。

That's the whole story. And now the question is, okay, so that represent the state of the universe. How does the universe evolve? What does the universe do? And so the answer is that what I'm looking at is transformation rules on these hypergraphs.

换句话说，当你看到超图中某部分呈现特定形态时，就将其转换为另一种形态的超图。在普通图中，可能是当你看到某个特定连接方式的子图时，就将其重写为另一个图。这就是全部原理。那么问题在于，正如我所说，这相当抽象。其中一个问题是：这些更新发生在哪里？

In other words, you say, whenever you see a piece of this hypergraph that looks like this, turn it into a piece of a hypergraph that looks like this. So on a graph, it might be when you see the subgraph, when you see this thing with a bunch of edges hanging out in this particular way, then rewrite it as this other graph. And so that's the whole story. So the question is, what so now you say I mean, as I say, this is quite abstract. And one of the questions is, where do you do those updating?

你拥有这个巨大的图。

So you've got this giant graph.

是什么触发了更新？比如，它的连锁效应是什么？是的。而且我怀疑即使在时间上一切也都是离散的。好吧。

What triggers the updating? Like, what's the what's the ripple effect of it? Is it Yes. And I I suspect everything is discrete even in time. So Okay.

那么问题在于，你在哪里进行更新？

So the question is, where do you do the updates?

是的。答案是，规则是，你在它们适用的任何地方进行更新。而且你进行更新的顺序是未定义的。也就是说，你可以以多种可能的顺序进行这些更新。关键在于，想象你是这个宇宙中的一个观察者。

Yes. And the answer is, the rule is, you do them wherever they apply. And you do them you do them the order in which the updates is done is not defined. That is, you can do them so there may be many possible orderings for these updates. Now, the point is, imagine you're an observer in this universe.

你会问，有什么被更新了吗？实际上，在你自己被更新之前，你无法以任何方式知道。因此，你所能感知的本质上只是事件之间如何相互影响的因果网络。这甚至不像是观察，更像是某种别的东西。

And you say, did something get updated? Well, you don't in any sense know until you yourself have been updated. So in fact, all that you can be sensitive to is essentially the causal network of how an event over there affects an event that's in you. That doesn't even feel like observation. That's like, that's something else.

你只是整个系统的一部分。是的，你是其中的一部分。但最终结果是，你所能感知的只是这个因果网络，即一个事件如何影响另一个事件。我并不是在做一个关于观察者结构的宏大陈述。

You're just part of the whole thing. Yes. You're part of it. But but even to have so the the end result of that is all you're sensitive to is this causal network of what event affects what other event. I'm not making a big statement about the structure of the observer.

我只是在说，这些重写的微观顺序，是这个宇宙中任何观察者、任何可想象的观察者都无法感知的。因为观察者唯一能感知的是这个因果网络，即宇宙中其他事件如何影响观察者内部的事件。所以你只需要关注因果网络，而不必关注这些微观的重写过程。这些重写可以在任何它们想发生的地方发生。

Simply saying, I'm simply making the argument that what happens, the microscopic order of these rewrites, is not something that any observer, any conceivable observer in this universe can be affected by. Because the only thing the observer can be affected by is this causal network of how the events in the observer are affected by other events that happen in the universe. So the only thing you have to look at is the causal network. You don't really have to look at this microscopic rewriting that's happening. So these rewrites are happening wherever they they happen wherever they feel like.

因果网络，你说过实际上没有一个明确的定义，比如什么被更新，事件的顺序是未定义的。是的，这就是你所说的因果网络的意思。但然后...

Causal network, is there you you said that there's not really so the idea would be an undefined, like, what gets updated, the the sequence of things is undefined. It's a Yes. That's what you mean by the causal network. But then the

不。因果网络是指，给定一个更新已经发生，那是一个事件。那么问题是，那个事件是否因果相关？如果那个事件没有发生，那么某些未来的事件也无法发生。这样你就建立起了这个关于什么影响什么的网络。

No. The causal network is, given that an update has happened, that's an event. Then the question is, is that event causally related to? Does that event if that event didn't happen, then some future event couldn't happen yet. And so you build up this network of what affects what.

因此，当你构建起那个网络时，在某种意义上，它就成了宇宙可观测层面的体现。明白了。然后你就可以提出诸如‘这个反映宇宙运行状态的可观测网络有多稳固？’之类的问题。好的，接下来就开始变得有趣了。

And so what that does, so when you build up that network, that's kind of the observable aspect of the universe in some sense. Gotcha. And so then you can ask questions about, you know, how robust is that observable network of the what's happening in the universe? Okay. So here's where it starts getting kind of interesting.

对于某些微观重写规则而言，重写顺序并不影响因果网络。这在数学逻辑上被称为丘奇-罗瑟性质或重写规则的合流性。就像简化代数表达式时，你可以先展开某些项再分解，顺序并不影响最终结果。

So for certain kinds of microscopic rewriting rules, the order of rewrites does not matter to the causal network. And so this is, okay, mathematical logic, moment. This is equivalent to the Church Rossa property or the confluence property of rewrite rules. And it's the same reason that if you are simplifying an algebraic expression, for example, you can say, oh, let me expand those terms out, let me factor those pieces. It doesn't matter what order you do that in.

你总会得到相同的答案。正是这个根本现象使得特定微观重写规则下的因果网络不受微观重写顺序影响。这个性质为何重要？因为它暗含了狭义相对论——该性质的重要性在于，狭义相对论允许我们从不同参考系观察现象。

You'll always get the same answer. And it's the same fundamental phenomenon that causes, for certain kinds of microscopic rewrite rules, that causes the causal network to be independent of the microscopic order of rewritings. Why is that property important? Because it implies special relativity. I mean, the the reason what the reason it's important is that that property special relativity says you can look at these sort of can look at different reference frames.

你对空间和时间的认知会因运动状态而改变，但物理定律始终保持不变。这正是狭义相对论的核心：物理定律与参考系无关。而微观重写顺序的改变本质上等同于参考系的转换，至少部分机制与之对应。令人惊讶的是，这是首次有基础微观理论能够推导出狭义相对论。

You can be looking at your notion of what space and what time can be different, depending on whether you're traveling at a certain speed, depending on whether you're doing this, that, and the other. But nevertheless, the laws of physics are the same. That's what the principle of special relativity says, is the laws of physics are the same independent of your reference frame. Well, turns out this change of the microscopic rewriting order is essentially equivalent to a change of reference frame, or at least there's a sub part of how that works that's equivalent to a change of reference frame. Somewhat surprisingly, and sort of for the first time in forever, it's possible for an underlying microscopic theory to imply special relativity, to be able to derive it.

这不是人为预设的，而是因果不变性这一自然属性的结果——正是这个属性确保了宇宙中存在唯一的时间线。若非如此，观察者将无法确定哪些事件真实发生。但有了因果不变性，我们就有了明确的时间序列概念。

It's not something you put in as a this is a it's something where this other property, causal invariance, which is also the property that implies that there's a single thread of time in the universe. It might not be the case. That's what would lead to the possibility of an observer thinking that definite stuff happens. Otherwise, you've got all these possible rewriting orders, and who's to say which one occurred? But with this causal invariance property, there's a notion of a definite threat of time.

听起来连时间和空间都是这个系统涌现的产物。

Sounds like that kind of idea of time, even space, would be emergent from the system.

没错。

Oh, yeah.

意思是它并非系统的根本组成部分。不，在

Mean So it's not a fundamental part of the system. No, At

基础层面上，你所拥有的只是一堆通过超边或其他方式连接的节点。

a fundamental level, all you've got is a bunch of nodes connected by hyper edges or whatever.

所以既没有时间，也没有空间。

So there's no time, there's no space.

没错。但关键在于，就像想象你正在处理一个图。假设你有一个类似蜂窝的图，或一堆六边形。在微观层面，那个图只是一堆相互连接的节点。但在微观层面，你会说，那看起来像一个蜂窝晶格。

That's right. But the thing is that it's just like imagining imagine you're just dealing with a graph. And imagine you have something like a honeycomb graph, or you have a bunch of hexagons. That graph, at a microscopic level, is just a bunch of nodes connected to other nodes. But at a microscopic level, you say, that looks like a honeycomb lattice.

它看起来像是某种二维流形，一个二维的东西。如果你以不同的方式连接，比如将所有节点以链表式结构相互连接，那么你会说，那看起来像一维空间。但在微观层面，这些都只是带有节点的网络。在微观层面，它们看起来像我们熟悉的某种空间。

It looks like a two dimensional manifold of some kind. It looks like a two dimensional thing. If you connect it differently, if you just connect all the nodes one to another in kind of a sort of linked list type structure, then you'd say, well, that looks like a one dimensional space. But at the microscopic level, all these are just networks with nodes. The microscopic level, they look like something that's like one of our familiar kinds of space.

这些超图也是同样的情况。现在，如果你问我是否找到了能产生三维空间的超图？答案是目前还没有。所以我们还不知道。这是其中一个问题。

And it's the same thing with these hypergraphs. Now, if you ask me, have I found one that gives me three-dimensional space? The answer is not yet. So we don't know. This is one of these things.

可以说，我们某种程度上是在与自然对赌。我无从得知。实际上，这类系统还有许多其他非常美妙且具有启发性的特性。如果这被证明是正确的，那将非常优雅，因为它非常简洁。你从无开始，一切逐步构建。

We're kind of betting against nature, so to speak. And I have no way to know. So there are many other properties of this kind of system that are very beautiful, actually, and very suggestive. And it will be very elegant if this turns out to be right, because it's very clean. You start with nothing, and everything gets built up.

关于空间的一切，关于时间的一切，关于物质的一切，都只是从这个极其底层系统的特性中涌现出来的。如果我们的宇宙就是这样运作的，那将非常酷。另一方面，让我感到非常困惑的是，假设我们成功了。假设我们能说这种特定的超图重写规则造就了宇宙。只需运行这个超图重写规则足够多次，你就会得到一切。

Everything about space, everything about time, everything about matter, it's all just emergent from the properties of this extremely low level system. And that will be pretty cool if that's the way our universe works. Now, on the other hand, the thing that I find very confusing is, let's say we succeed. Let's say we can say this particular sort of hypergraph rewriting rule gives the universe. Just run that hypergraph rewriting rule for enough times, and you'll get everything.

你会得到我们正在进行的这段对话。你会得到一切。关键在于，如果我们达到那个阶段，并审视这个规则——正是它给了我们整个宇宙——我们该如何理解它？假设最终发现这个模型的最小版本，对于像我这样的语言设计者来说很酷的是，它实际上只是孤儿语言的一行代码。我原本不确定会是这样，但事实就是如此。

You'll get this conversation we're having. You'll get everything. It's that if we get to that point and we look at what is this thing, what is this rule that we just have that is giving us that whole universe, how do we think about that thing? Let's say, turns out the minimal version of this, and this is kind of a cool thing for a language designer like me, the minimal version of this model is actually a single line of orphan language code. That's Which I wasn't sure was gonna happen that way, but it's it's a it's kind of no.

我们不知道我们不知道什么。这只是框架。要了解实际的特定超图，可能需要更长的规则描述。

We don't know what we don't know what. That's that's just the framework. To know the actual particular hypergraph, it might be a longer the specification of the rules might

可能会稍长一些。这如何帮助你接受并惊叹于创造宇宙的简洁之美与优雅？这能帮助我们预测什么吗？其实并不能，因为

be slightly longer. How does that help you accept marveling in the beauty and the elegance of the simplicity that creates the universe? Does that help us predict anything? Not really, because of

不可约性。没错，确实如此。但真正让我感到奇怪且尚未想通的是，我们不断意识到自己并不特殊——我们不在宇宙中心，没有特权等等。然而，如果我们为宇宙制定了一条相当简单的规则，用几行代码就能写下，这感觉又非常特别。

the irreducibility. That's correct. That's correct. But so the thing that is really strange to me, and I haven't wrapped my brain around this yet, is one keeps on realizing that we're not special in the sense that we don't live at the center of the universe, we don't blah blah blah. And yet, if we produce a rule for the universe and it's quite simple and we can write it down in a couple of lines or something, that feels very special.

当许多可能的宇宙都极其复杂（比如需要万亿字符描述）时，为何我们恰好得到一个简单的？我还没想明白这个问题。如果宇宙真是由如此简单的规则构成，是否存在某种超越这个框架的存在？我们是否处于某种

How did we come to get a simple universe when many of the available universes, so to speak, are incredibly complicated? Might be, you know, a quintillion characters long. Why did we get one of the ones that's simple? And so I haven't wrapped my brain around that issue yet. If indeed we are in such a simp the universe is such a simple rule, Is it possible that there is something outside of this, that we are in a kind of

人们所说的模拟之中？对吧？我们可能只是某个平行宇宙里研究生正在探索的计算程序的一部分。

what people call us to the simulation? Right? That we're just part of a computation that's being explored by a graduate student in an alternate universe.

嗯，你知道，问题在于我们无法过多谈论宇宙之外的事物，因为根据定义，我们的宇宙就是我们存在的空间。是的。那么，我们能否从了解我们这个特定宇宙的运行方式中得出某种近乎神学的结论呢？这是个有趣的问题。我不认为如果你提出这个问题——我们能否做到，这又回到了关于外星智慧的问题，我们已经掌握了宇宙的规律。

Well, you know, the problem is we don't get to say much about what's outside our universe, because by definition, our universe is what we exist within. Yeah. Now, can we make a sort of almost theological conclusion from being able to know how our particular universe works? Interesting question. I don't think that if you ask the question, could we and it relates again to this question about the extraterrestrial intelligence we've got the rule for the universe.

它是被有意建造的吗？很难说。这就像我们看到从某颗随机恒星接收到的信号，那是一系列脉冲。而且，你知道，这是一组周期性的脉冲序列。

Was it built on purpose? Hard to say. That's the same thing as saying we see a signal that we're receiving from some random star somewhere, and it's a series of pulses. And, you know, it's a periodic series

比如说。这是有意为之的吗？我们能从这一系列脉冲中推断出什么关于其起源的信息吗？仅仅因为它很优雅，并不一定意味着有人创造了它，甚至我们能否理解它。

of pulses, let's say. Was that done on purpose? Can we conclude something about the origin of that series of pulses? Just because it's elegant does not necessarily mean that somebody created it or that we can even comprehend

是的。我认为这是技术特征识别问题的终极版本。也就是说，我们的宇宙是否可以说是一件技术产品，而我们又如何能知道呢？在那种疯狂的科学幻想中，你可能会说，哦，那里会有个签名。它会是由某某制造的。

Yeah. What we I think it's the ultimate version of the sort of identification of the technosignature question. It's the ultimate version of that is, was our universe a piece of technology, so to speak, and how on earth would we know? In the kind of crazy science fiction thing you could imagine, you could say, oh, there's gonna be a signature there. It's gonna be, you know, made by so and so.

但我们无法理解这一点，可以说，而且不清楚那意味着什么。因为宇宙，你知道，如果我们找到了宇宙的规律，我们只是在说那个规律代表了我们的宇宙的行为。我们并不是说那个规律是在某台大计算机上运行并创造了我们的宇宙。这只是表示那个规律代表了我们的宇宙的行为，就像经典力学定律、微分方程等代表了机械系统的行为一样。并不是说机械系统在某种程度上在解那些微分方程。

But there's no way we could understand that, so to speak, and it's not clear what that would mean. Because the universe simply you know, this if we find a rule for the universe, we're simply saying that rule represents what our universe does. We're not saying that that rule is something running on a big computer and making our universe. It's just saying that represents what our universe does, in the same sense that laws of classical mechanics, differential equations, whatever they are, represent what mechanical systems do. It's not that the mechanical systems are somehow running solutions to those differential equations.

那些微分方程只是代表了那些系统的行为。那么，在你看来，差距在哪里？让我们继续这个迷人的、或许有点科幻的问题，差距是什么——

Those differential equations are just representing the behavior of those systems. So what's the gap, in your sense, to linger on the fascinating, perhaps slightly sci fi question, what's the

理解创造宇宙的基本规律与设计一个系统、实际自己创造一个模拟之间的差距。你提到了一些纳米工程的想法，这些想法相当令人兴奋，实际上是在物理空间中创造一些计算的概念。一旦你知道了创造宇宙的规律，作为一个工程问题，创造宇宙有多难？

gap between understanding the fundamental rules that create a universe and engineering a system, actually creating a simulation ourselves. So you've talked about sort of you've talked about, you know, nanoengineering kind of ideas that are kind of exciting, actually creating some ideas of computation in the physical space. How hard is is it as an engineering problem to create the universe once you know the rules that create it?

嗯，这是个有趣的问题。我认为宇宙运行的基底并非我们所能触及的那种基底。我的意思是，我们唯一拥有的基底就是宇宙自身运作的同一基底。如果宇宙是一系列正在被重写的超图，那么我们得以依附于这些同样被重写的超图。我们无法

Well, that's an interesting question. I think the substrate on which the universe is operating is not a substrate that we have access to. I mean, the only substrate we have is that same substrate that the universe is operating in. So if the universe is a bunch of hypergraphs being rewritten, then we get to attach ourselves to those same hypergraphs being rewritten. We don't get to And

如果

if

你问这个问题：代码是否简洁？我们能否编写出优雅高效算法的漂亮代码？这确实是个有趣的问题。关键在于——你如何判断系统中有多少计算可约性存在。

you ask the question, is the code clean? Can we write nice, elegant code with efficient algorithms and so on? Well, that's an interesting question. How how you know, that's this question of how much computational reducibility there is in the system.

但我见过一些美妙的细胞自动机，它们基本上能在自身内部创建自身的副本，对吧？嗯哼。所以问题在于是否可能创造出——究竟需要理解基底还是可以...是的，没错，我是说

But so I've seen some beautiful cellular automata that basically create copies of itself within itself. Right? Uh-huh. So that's the question whether it's possible to create like, whether you need to understand the substrate or whether you can just Yeah, well, right. I mean,

关于未来，我有种略带科幻色彩的想法：当下如果你调查普通人是否认为找到物理学基础理论很重要——我确实做过这种非正式调查——结果很有趣，相当比例的人会说'哦，那会很有意思'。

so one of the things that is sort of one of my slightly sci fi thoughts about the future, so to speak, is, you know, right now, if you poll typical people who say, do you think it's important to find the fundamental theory of physics? You get because I've done this poll, informally at least it's curious, actually. You get a decent fraction of people saying, oh, yeah, that would be pretty interesting.

出乎意料的是，这种关注度正在上升。很多人以一种不求甚解的方式关注物理学，就像旁观极少数科学家努力理解现实本质的挣扎过程。

I think that's becoming, surprisingly enough, more I mean, a lot of people are interested in physics in a way that, like, without understanding it, just kind of watching scientists, a very small number of them, struggle to understand the nature of our reality.

没错。某种程度上确实如此。事实上，在我即将开展的寻找物理学基础理论项目中，我会将其作为公开项目推进——全程直播等等。虽然结果尚未可知。

Right. I mean, I I think that's somewhat true. And in fact, in this project that I'm launching into to try and find fundamental theory of physics, I'm going to do it as a very public project. It's going to be livestreamed and all this kind of stuff. I don't know what will happen.

这会有点意思。我认为它是这个项目通向世界的接口。我想到这个项目的一个特点是，不同于那些本质即呈现的技术项目，这个项目可能会彻底失败，因为它可能产生各种优雅的数学理论，却与我们恰好居住的物理宇宙毫无关联。好吧。那么我们正在讨论的是寻找物理学基本理论的探索。

It'll be kind of fun. I think that it's the interface to the world of this project. I figure one feature of this project is, unlike technology projects that basically are what they are, this is a project that might simply fail, because it might be the case that it generates all kinds of elegant mathematics that has absolutely nothing to do with the physical universe that we happen to live in. Okay. So we're talking about the quest to find the fundamental theory of physics.

第一点是，事实证明寻找物理学基本理论相当困难。人们原本并不确定会如此。回溯到数学应用于科学的早期，比如17世纪左右，人们曾认为，一百年内我们就能洞悉宇宙运行的所有奥秘。结果比那困难得多。某种程度上人们变得谦卑起来，因为每次我们研究宇宙更微观的层面时，数学似乎变得更复杂，一切都更加棘手。

First point is, it's turned out it's kind of hard to find the fundamental theory of physics. People weren't sure that that would be the case. Back in the early days of applying mathematics to science, 1600s and so on, people were like, oh, in one hundred years, we'll know everything there is to know about how the universe works. Turned out to be harder than that. And people got kind of humble at some level, because every time we got to a greater level of smallness in studying the universe, it seemed like the math got more complicated and everything got harder.

我小时候基本上就开始研究粒子物理。那时我总觉得寻找物理学最基础的理论是件荒唐事，我们永远做不到。但我们可以在已构建的框架内工作，比如量子场论、广义相对论这些，效果不错，我们能弄明白很多东西

When I was a kid, basically, I started doing particle physics. And when I was doing particle physics, I always thought finding the fundamental, fundamental theory of physics, that's a kooky business, we'll never be able to do that. But we can operate within these frameworks that we built for doing quantum field theory and general relativity and things like this, and it's all good, and we can figure out a lot

。即便在那时，你是否隐约感觉到背后还有更深层的东西存在？

of stuff. Did you even at that time have a sense that there's something behind that too?

当然。只是没想到我当时抱持着某种近乎...现在回想起来其实挺疯狂的观念，就像文明史上曾有过漫长时期，人们认为古人已掌握全部真理，后人再难有新发现。某种程度上，当我沉浸于物理学研究时也有类似感受——我们有了量子场论，这是我们工作的基础。是的，底下可能还有东西，但我们恐怕永远无法真正发现它。

Sure. I just didn't expect that I thought in some rather un it's actually kind of crazy thinking back on it, because it's kinda like there was this long period in civilization where people thought the ancients had it all figured out and will never figure out anything new. And to some extent, that's the way I felt about physics when I was in the middle of doing it, so to speak, was we've got quantum field theory. It's the foundation of what we're doing. And yes, there's probably something underneath this, but we'll sort of never figure it out.

但后来我开始研究计算宇宙中的简单程序，比如元胞自动机之类。我发现它们展现的各种行为完全颠覆了我的既有认知。当你目睹这些微小程序产生令人惊叹的复杂现象后，就会对物理学产生更大野心，想着或许我们也能在这方面取得突破。这让我多年前开始思考：我们真能找到支撑量子场论、广义相对论等所有框架的基础吗？人们或许没有充分意识到，当前物理学的两大支柱——描述微观世界的量子场论与描述引力及宏观世界的广义相对论——

But then I started studying simple programs in the computational universe, things like cellular automata and so on. And I discovered that they do all kinds of things that were completely at odds with the intuition that I had had. And so after that, after you see this tiny little program that does all this amazingly complicated stuff, then you start feeling a bit more ambitious about physics and saying, maybe we could do this for physics too. And so that got me started years ago now in this kind of idea of could we actually find what's underneath all of these frameworks, like quantum field theory and general relativity and so on. And people perhaps don't realize as clearly as they might that the frameworks we're using for physics, which is basically these two things: quantum field theory, the theory of small stuff and general relativity, theory of gravitation and large stuff.

这两个基础理论都已存在百年。广义相对论诞生于1915年，量子场论则是1920年代。基本上都是百年前的理论了。这段历程成果丰硕，我们已经弄懂了许多东西。

Those are the two basic theories, and they're 100 years old. General relativity was 1915 quantum field theory, well, 1920s. So basically 100 years old. And it's been a good run. There's a lot of stuff been figured out.

但有趣的是，在这整个时期里，基础理论并未改变。尽管在那之前的二百年间，基础理论已经历过多次变革。而我认为，基于对计算和计算宇宙的思考，我所探讨的是一种不同的基础，一套全新的理论根基。或许我是错的，但至少我们有机会尝试。

But what's interesting is the foundations haven't changed in all that period of time. Even though the foundations had changed several times before that in the two hundred years earlier than that. And I think the kinds of things that I'm thinking about, which are really informed by thinking about computation and the computational universe, it's a different foundation. It's a different set of foundations. And I might be wrong, but it is at least we have a shot.

对我个人而言，我的考量是：如果发现物理学基本理论其实是唾手可得的成果（打个比方），而我们却因思维局限未能实现，那将是巨大的遗憾。如果人们总说'你永远搞不懂这些'，导致又耗费两百年才有人着手研究。我不确定这个成果究竟有多容易获取，也许这个世纪根本不适合开展这项研究。这让我想起技术领域那些过早尝试的警示案例——

And I think to me, my personal calculation for myself is if it turns out that finding the fundamental theory of physics is kind of low hanging fruit, so to speak, it'd be a shame if we just didn't think to do it. If people just said, oh, you'll never figure that stuff out, and it takes another two hundred years before anybody gets around to doing it. I don't know how low hanging this fruit actually is. It may be that it's kind of the wrong century to do this project. I think the cautionary tale for me, I think about things that I've tried to do in technology where people thought about doing them a lot earlier.

我最喜欢的例子大概是莱布尼茨，他在17世纪末就试图用计算形式封装世界知识，并为此付出诸多努力。而我们最终实现这个构想时，他早了整整三百年。从人生规划角度来说，这就像要避免在本世纪无法完成的事业。

My favorite example is probably Leibniz, who thought about making essentially encapsulating the world's knowledge in a computational form in the late 1600s and did a lot of things towards that. And basically, we finally managed to do this, but he was three hundred years too early. And that's kind of the in terms of life planning, it's kind of like avoid things that can't be done in your century, so to speak.

是啊，时机决定一切。那么你认为，如果我们找出能让量子场论和广义相对论共同涌现的底层规则，是否有助于在抽象层面实现理论统一？

Yeah, timing is everything. So you think if we kind of figure out the underlying rules it can create from which quantum field theory and general relativity can emerge, do you think that'll help us unify it at that level of abstraction?

噢，我们将彻底理解它。毫无疑问，我们会明白这一切如何严丝合缝。甚至基于我已完成的成果，各种要素的契合方式实际上非常精妙。但问题是——它正确吗？

Oh, we'll know it completely. We'll know how that all fits together. Yes, without a question. And even the things I've already done, it's very elegant, actually, how things seem to be fitting together. Now, is it right?

目前还无法确定，但极具启发性。如果这个理论不正确，那么宇宙的设计者真该感到难为情（这么说吧），因为这确实是个绝妙的构建方式。

I don't know yet. It's awfully suggestive. If it isn't right, then the designer of the universe should feel embarrassed, so to speak, because it's a really good way to do it.

关于宇宙设计，你的直觉是——上帝会掷骰子吗？这个体系中存在随机性，还是完全确定性的？就是那种...

And your intuition in terms of designing universe, does God play dice? Is there is there randomness in this thing, or is it deterministic? So the kind of

这个问题有点复杂，因为当你处理这些涉及重写的内容时，它们本身就已经够让人头疼了。

That's a little bit of a complicated question, because when you're dealing with these things that involve these rewrites that have okay.

或许连随机性也是一种涌现现象。是的。

Even randomness is an emergent phenomenon, perhaps. Yes.

我是说，确实如此。在许多这类系统中，伪随机性和真正的随机性很难区分。就量子力学中的测量而言，我们目前的想法非常奇特且抽象，不借助专业术语恐怕难以解释清楚——虽然最终我能做到。如果这个理论正确，它将以一种前所未有的方式在决定论与随机性之间划出界限，可以说相当诡异。

Mean, it's a yeah. Well, randomness in many of these systems, pseudorandomness and randomness are hard to distinguish. In this particular case, the current idea that we have about measurement in quantum mechanics is something very bizarre and very abstract, and I don't think I can yet explain it without yakking about very technical things. Eventually, I will be able to. But if that's if that's right, it's kind of a it's a weird thing because it slices between determinism and randomness in a weird way that hasn't been sliced before, so to speak.

就像科学中常出现的问题：是A还是B？结果发现正确答案其实是C——某种完全不同的、超越原有分类的存在。这就是本周我们对这个问题的阶段性认知，未来还需持续观察。

So like many of these questions that come up in science, where it's like, is it this or is it that? Turns out the real answer is it's neither of those things. It's something kind of different and sort of orthogonal to those categories. And so that's the current, this week's idea about how that might work. But we'll see how that unfolds.

关于物理学这类追求基础理论的领域，既存在科学层面的探索，也涉及社会层面的演进。作为可能已是第四代或第五代的物理学者（我自己就是其中一员），我们面对的基础理论就像金字塔般古老而稳固。

There's this question about a field like physics and the quest for fundamental theory and so on. And there's both the science of what happens and there's the social aspect of what happens. Because in a field that is basically as old as physics, we're at, I don't know what it is, fourth generation, I don't know fifth generation, I don't know what generation it is of physicists. And I was one of these, so to speak. And for me, the foundations were like the pyramids, so to speak.

传统认知根深蒂固。在古老学科中重构基础理论远比新兴领域困难得多——后者往往还由开创者主导。科学发展的典型模式总是：首先出现方法论突破，

It was that way, and it was always that way. It is difficult in an old field to go back to the foundations and think about rewriting them. It's a lot easier in young fields, where you're still dealing with the first generation of people who invented the field. And it tends to be the case. The nature of what happens in science tends to be you'll get typically, the pattern is some methodological advance occurs.

随后五年、十年或更长时间里，这项突破（无论是望远镜还是数学工具）会催生大量成果。当这些容易摘取的果实被采撷殆尽后，接下来几十年甚至上百年都将是为下一个突破点而艰苦跋涉的过程——这种阶段虽非巡航模式（因为仍需艰辛努力），但进展往往极其缓慢。

And then there's a period of five years, ten years, maybe a little bit longer than that, where there's lots of things that are now made possible by that methodological advance, whether it's telescopes or whether that's some mathematical method or something. Something happens, a tool gets built, and then you can do a bunch of stuff. And there's a bunch of low hanging fruit to be picked, and that takes a certain amount of time. After all that low hanging fruit is picked, then it's a hard slog for the next however many decades or century or more to get to the next level at which one can do something. And it tends to be the case that in fields that are in that kind of, I wouldn't say cruise mode because it's really hard work, but it's very hard work for very incremental progress.

在你的职业生涯和承担的一些事务中，感觉你并不畏惧艰苦的奋斗。

And in your career and some of the things you've taken on, it feels like you're not you haven't been afraid of the hard slog.

是的，确实如此。

Yeah. That's true.

这很有趣，尤其是在工程方面。稍微岔开话题，你在加州理工学院时，是否与理查德·费曼有过交集？有什么回忆吗？

So it's quite interesting, especially on the engineering side. On a small tangent, when you were at Caltech, did you get to interact with Richard Feynman at all? You have any memories Oh,

有的。实际上我们共事过不少时间。无论是在加州理工期间还是离开后，我们都曾担任一家名为'思维机器公司'的顾问，这家公司就在离这儿不远的街上。虽然它最终命运多舛，但我当时常说，按他们的策略这公司行不通。

yeah. Of We worked together quite a bit, actually. In fact, and in fact, both when I was at Caltech and after I left Caltech, we were both consultants at this company called Thinking Machines Corporation, which was just down the street from here, actually. It was an ultimately ill fated company. But I used to say, this company is not going to work with the strategy they have.

而迪克·费曼总说：'我们对经营公司懂什么？让他们自己折腾吧。'他向来对这类事不感兴趣，认为我热衷创办公司之类的事——这么说吧——是种分心。但对我来说，这是建立更有效机制来解决问题、推动事情实现的方式。

And Dick Feynman always used to say, What do we know about running companies? Just let them run their company. But anyway, he was not into that kind of thing. He always thought that my interest in doing things like running companies was a distraction, so to speak. And for me, it's a mechanism to have a more effective machine for actually figuring things out and getting things to happen.

他是否理解你通过公司所做的事——不知你是否这么想过——你是在创造工具来赋能大学的研究探索？

Did he think of it because essentially what you used you did with the company, I don't know if you were thinking of it that way, but you're creating tools to empower your to empower the exploration of of the university. Do you

你觉得...他理解这个观点吗？

think did he Did he understand that point?

工具之于我的意义

The point of tools of I

认为他本可以做得更好。我是说，虽然这么想，但他确实是我的第一家公司合伙人，那家公司还涉及——更准确地说，主要从事数学计算类工作。他对我们技术路线的选择等方面提供了大量建议。你呢

think not as well as he might have done. I mean, I think that but, you know, he was actually my first company, which was also involved with well, was involved with more mathematical computation kinds of things, he had lots of advice about the technical side of what we should do and so on. Do you

能举例说明那些记忆中的想法吗？哦，当然当然。

have examples of memories of thoughts that Oh, yeah, yeah.

他掌握着各种方法——你看，在数学领域最困难的事情之一就是求解积分等等对吧？所以他自创了一套复杂的积分求解方法。他还有自己独特的理解数学运作原理的直觉方式。他的核心理念就是：让计算机遵循这些直觉方法。但事实证明，大多数情况下，当我们处理积分问题时，实际构建的是某种怪异的工业机器——它把所有积分都转化为梅耶尔G函数的乘积，生成极其复杂的结果。

He had all kinds of look, in the business of doing sort of one of the hard things in math is doing integrals and so on, right? And so he had his own elaborate ways to do integrals and so on. He had his own ways of thinking about getting intuition about how math works. And so his meta idea was take those intuitional methods and make a computer follow those intuitional methods. Now, turns out, for the most part, like when we do integrals and things, what we do is we build this kind of bizarre industrial machine that turns every integral into products of Meyer G functions and generates this very elaborate thing.

实际上最大的难题在于将结果转化为人类能理解的形态，而非所谓的'求解积分'。费曼在某种程度上确实理解这点。说来惭愧，他曾给过我一大摞他在50年代研究的粒子物理计算方法手稿，还说'这些对你比对我更有用'之类的话。我本打算研读后归还，结果至今还躺在我的档案堆里。

And actually, the big problem is turning the results into something a human will understand. It's not, quote, doing the integral. And actually, Feynman did understand that to some extent. And I'm embarrassed to say he once gave me this big pile of calculational methods for particle physics that he worked out in the '50s, and he said, yeah, it's more used to you than to me type thing. And I was like, I intended to look at it and give it back, and I'm still in my files now.

这就是人类寿命有限导致的遗憾。要是他能多活二十年，我或许记得归还。但我想那是他试图系统化处理粒子物理学中常见积分方法的尝试。而事实证明，我们实际采用的方法与他的思路大相径庭。

That's what happens when it's finiteness of human lives. Maybe if he'd lived another twenty years, I have remembered to give it back. But I think that was his attempt to systematize the ways that one does integrals that show up in particle physics and so on. Turns out, the way we've actually done it is very different from that way.

你如何看待这种差异，泽钦？费曼确实非凡地擅长构建直觉体系——就像直接潜入问题核心那样，为复杂概念建立直观的理解框架。（我正发笑呢，因为关于他的趣事在于：他真正、真正、真正擅长的其实是具体计算。）

What do you make of that difference, Zechin? So Feynman was actually quite remarkable at creating sort of intuitive, like diving in, you know, creating intuitive frameworks for understanding difficult concepts is I'm smiling because the funny thing about him was that the thing he was really, really, really good at is calculating stuff.

但他认为这很简单，因为他确实很擅长。所以他常会做一些事情，比如在量子场论中进行复杂的计算，得出结果。他不会告诉任何人这个复杂的计算过程，因为他觉得那很简单。他认为真正令人印象深刻的是对事物运作方式有这种简单的直觉。所以最后他发明了这种方法。

But he thought that was easy because he was really good at it. And so he would do these things where he would do some complicated calculation in quantum field theory, for example, come out with a result. Wouldn't tell anybody about the complicated calculation because he thought that was easy. He thought the really impressive thing was to have this simple intuition about how everything works. So he invented that at the end.

因为他已经做了这些计算并知道它是如何运作的，所以这要容易得多。当你知道答案是什么时，拥有好的直觉会容易得多。然后他就不会告诉任何人这些计算。他并不是恶意这样做，可以这么说。他只是认为那很简单。

And because he'd done this calculation and knew how it worked, it was a lot easier. It's a lot easier to have good intuition when you know what the answer is. And then he would just not tell anybody about these calculations. And he wasn't meaning that maliciously, so to speak. It's just he thought that was easy.

这导致了一些领域，人们完全感到困惑，他们某种程度上跟随他的直觉，但没有人能解释为什么这行得通。因为实际上，它之所以行得通是因为他已经做了所有这些计算，他知道它会行得通。而且，你知道，我和他实际上在1980年、81年就研究过量子计算机，那时还没有人听说过这些东西。典型的模式是，他总是说，我现在想起这个是因为我差不多到了当年和他一起工作时他的年龄，我看到人们差不多是我年龄的三分之一，可以这么说。他总是抱怨我是他年龄的三分之一，因此有各种事情。

And that led to areas where people were just completely mystified, they kind of followed his intuition, but nobody could tell why it worked. Because actually, the reason it worked was because he'd done all these calculations and he knew that it would work. And, you know, I, he and I, worked a bit on quantum computers actually back in nineteen eighty, eighty one, before anybody had heard of those things. And the typical mode of I mean, he always used to say, and I now think about this because I'm about the age that he was when I worked with him, and I see that people are one third my age, so to speak. And he was always complaining that I was one third his age, therefore various things.

但他会用手做一些计算，你知道，黑板之类的，得出一些答案。我会说，我不明白这个。我用电脑做一些事情，他会说，我不明白这个。所以就会有一些关于发生了什么的大争论。但总是有一些……而且我认为，实际上，我们关于量子计算实现的许多事情，特别是与测量过程相关的问题，某种程度上今天仍然是问题。

But he would do some calculation by hand, you know, Blackboard and things, come up with some answer. I'd say, I don't understand this. I do something with a computer, and he'd say, I don't understand this. So there'd be some big argument about what was going on. But it was always some And I think, actually, many of the things that we realized about quantum computing that were issues that have to do particularly with the measurement process are kind of still issues today.

我觉得这有点有趣。科学中有件有趣的事情，技术中也有——历史会以一种显著的方式重复发生。最终，事情真的会被确定下来。但这通常需要一段时间，而且往往几十年后事情会再次出现。嗯，举个例子，我可以讲个故事。

And I kind of find it interesting. It's a funny thing in science, there's a remarkable it happens in technology, too there's a remarkable sort of repetition of history that ends up occurring. Eventually, things really get nailed down. But it often takes a while, and often things come back decades later. Well, for example, I could tell a story.

这实际上就发生在这条街附近。当我们都在Thinking Machines公司时，我一直在研究这个特定的称为规则30的细胞自动机，它具有从非常简单的初始条件产生极其复杂行为的特性。实际上，在所有愚蠢的物理事物中，使用这家公司制造的那台名为Connection Machine的大型并行计算机，我生成了规则30的巨大打印输出，实际上，用的是人们用来制作微处理器布局的同一种打印机，所以是一台大型、高分辨率的大幅面打印机等等。好吧，我们打印出来，很多非常小的单元格。所以关于这个模式的一些特征如何的问题就出现了。

It actually happened right down the street from here. When we were both at Thinking Machines, I had been working on this particular cellular automaton called Rule 30 that has this feature that from very simple initial conditions, it makes really complicated behavior. And actually, of all silly physical things, using this big parallel computer called the Connection Machine that that company was making, I generated this giant printout of Rule 30, actually, the same kind of printer that people use to make layouts for microprocessors, so one of these big, large format printers with high resolution and so on. So Okay, so we print this out, lots of very tiny cells. And so there was sort of a question of how some features of that pattern.

所以这非常物理化，我们趴在地上用米尺试图测量不同的东西。费曼把我拉到一边。我们已经这样做了一会儿。他把我拉到一边说，我只想知道一件事。他说，我想知道，你是怎么知道这个规则30会产生所有这些如此复杂的行为，以至于我们要围着这个大打印输出转来转去？

And so it was very much a physical, on the floor with meter rules trying to measure different things. Feynman kind of takes me aside. We've been doing that for a little while. And he takes me aside and he says, just want to know this one thing. He says, I want to know, how did you know that this Rule 30 thing would produce all this really complicated behavior that is so complicated that we're going around with this big printout and so on?

我说，其实我也不知道。我只是列举了所有可能的规则，然后观察到事情就这么发生了。他说，哦，我感觉好多了。我还以为你有什么他无法理解的直觉。我说，不不不。

And I said, well, I didn't know. I just enumerated all the possible rules and then observed that that's what happened. He said, oh, I feel a lot better. I thought you had some intuition that he didn't have that would let one. I said, no, no, no.

没有直觉。只有实验科学。

No intuition. Just experimental science.

啊，这真是个绝妙的二分法——你展示的正是这一点：对于不可简化的事物确实无法凭直觉理解，我的意思是，你必须实际运行它。

Oh, that's such a beautiful sort of dichotomy there of that's exactly what you showed is you really can't have an intuition about an irreducible, I mean, you have to run it.

是的，没错。

Yes, that's right.

这对我们人类来说太难接受了，尤其是像费曼这样杰出的物理学家，要承认你无法对整个系统形成简洁的直觉理解

That's so hard for us humans, and especially brilliant physicists like Feynman, to say that you can't have a compressed, clean intuition about how the whole thing

运作机制。确实。他当时——我认为他几乎就要理解计算的那个关键点了。而且我觉得他始终对计算很感兴趣，这大概就是他当时隐约触及的方向。我是说，那种直觉，发现事物规律的困难，就像你说的'哦，只要枚举所有情况然后找出有趣的那个'。

works. No. He was I mean, I think he was sort of on the edge of understanding that point about computation. And I think he found that I think he always found computation interesting, and I think that was sort of what he was a little bit poking at. I mean, that intuition, the difficulty of discovering things, like even you say, oh, you just enumerate all the cases and you just find one that does something interesting.

听起来很简单。但结果呢，我第一次看到时错过了，因为某种直觉告诉我它不应该存在。所以我当时找了些理由，比如'我要忽略那个情况因为...'之类的借口。而你是怎么...

Sounds very easy. Turns out, I missed it when I first saw it because I had kind of an intuition that said it shouldn't be there. So I had kind of arguments, oh, I'm gonna ignore that case because whatever. And How did you have

足够开放的心态吗？因为你本质上和罗舒亚是同一类人，拥有相似的物理学思维方式。你是如何发现自己具备足够开放的心态，愿意去观察规则并发现其中的复杂性的？

an open mind enough? Because you're essentially the same person as Roshua like, the same kind of physics type of thinking. How did you find yourself having a sufficiently open mind to be open to watching rules and them revealing complexity?

是的，我认为这是个有趣的问题。我自己也思考过这个问题，因为这有点像，你知道，你经历了这些事情，然后你会问，历史的真相是什么？有时候事后你意识到的历史故事与你实际经历的并不完全一致。所以我意识到，我认为发生的是，我从事的是还原论的物理学研究，就像把宇宙交给你，然后被告知去弄清楚里面发生了什么。

Yeah. I think that's an interesting question. I've wondered about that myself because it's kind of like, you know, you live through these things, and then you say, what was the historical story? And sometimes the historical story that you realize after the fact was not what you lived through, so to speak. And so what I realized is I think what happened is I did physics kind of like reductionistic physics, where you're throwing the universe and you're told, go figure out what's going on inside it.

然后我开始构建计算机工具，比如我开始构建我的第一种计算机语言。计算机语言在某种程度上类似于物理学，因为你必须理解人们想要进行的所有计算，深入挖掘并找到构成这些计算的基本元素。但随后你做的事情就完全不同了，因为你只是在说，好吧，这些是基本元素。现在，希望它们对人们有用。让我们从这里开始构建。

And then I started building computer tools, and I started building my first computer language, for example. And a computer language is not like it's sort of like physics in the sense that you have to take all those computations people want to do and drill down and find the primitives that they can all be made of. But then you do something that's really different, because you're just saying, Okay, these are the primitives. Now, hopefully, they'll be useful to people. Let's build up from there.

所以从某种意义上说，你实际上是在构建一个人工宇宙，你创造了这种语言，拥有了这些基本元素，你可以随心所欲地构建任何东西。这对我来说很有趣，因为从科学研究，即你只是接受宇宙本来的样子，到被告知你可以创造任何你想要的宇宙。因此，我认为这种创造计算机语言的经历，本质上就是在构建你自己的宇宙，可以说，这让我对可能的事物有了不同的态度。就像，让我们探索这些人工宇宙中可以做什么，而不是像自然科学那样被宇宙的实际样子所限制。是的。

So you're essentially building an artificial universe, in a sense, where you make this language, you've got these primitives, you're just building whatever you feel like building. And so it was sort of interesting for me, because from doing science where you're just throwing the universe as the universe is, to then just being told, you you can make up any universe you want. And so I think that experience of making a computer language, which is essentially building your own universe, so to speak, is you know, that's kind of the that's that's what gave me a somewhat different attitude towards what might be possible. It's like, let's just explore what can be done in these artificial universes rather than thinking the natural science way of let's be constrained by how the universe actually is. Yeah.

通过能够编程，本质上，你不再局限于你的大脑和一支笔，你现在基本上构建了另一个大脑，你可以

By being able to program, essentially, you've as opposed to being limited to just your mind and a pen, you you now have you've basically built another brain that you

用来探索宇宙。是的。计算机程序，你知道，是一种大脑。对吧。

can use to explore the universe by Yeah. A computer program, you know, is a kind of a brain. Right.

而且，它更像是望远镜，或者你知道，它是一种工具。它让你能够看到东西。

And it's well, it's it's or a telescope or, you know, it's a tool. It lets you lets you see stuff.

但计算机与望远镜存在本质区别。我是说，它确实...希望不会过度美化这个概念，但它更具普适性。计算机

But there's something fundamentally different between a computer and a telescope. I mean, it just Yeah. Hoping not to romanticize the notion, but it's more general. The computer

比望远镜更具普适性。我想说的是，人们常说某某事物几乎在某某时刻就被发现了。真正困难的是构建能让你理解事物或使人开放看待现象的范式。我很幸运一生中花费大量时间构建计算语言，这项活动本质上需要通过创建更高层次的抽象来接纳不同结构。但我完全清楚自己多次见证过'错过显而易见之事'有多么容易——至少这种认知让我努力不去忽视明显之事，尽管未必总能成功。

is more general than Telescope. I think I mean, this point about, you know, people say, oh, such and such a thing was almost discovered at such and such a time. The the distance between the building the paradigm that allows you to actually understand stuff or allows one to be open to seeing what's going on, that's really hard. And I think in I've been fortunate in my life that I've spent a lot of my time building computational language, and that's an activity that, in a sense, works by having to create another level of abstraction and be open to different kinds of structures. But I'm fully aware of, I suppose, the fact that I have seen it a bunch of times of how easy it is to miss the obvious, so to speak, that at least is factored into my attempt to not miss the obvious, although it may not succeed.

你认为自我在数学与科学史中扮演什么角色？比如像《一种新科学》这样的著作，你已取得巨大成就。实际上有人说牛顿没有自我，我查证后发现他自我意识极强。从外界角度看，也有人认为你有些自我意识过剩。

What do you think is the role of ego in the history of math and science? And more sort of, you know, a book titled something like A New Kind of Science, you've accomplished a huge amount. In fact, somebody said that Newton didn't have an ego, and I looked into it and he had a huge ego. Yeah. But from an outsider's perspective, some have said that you have a bit of an ego as well.

你如何看待这点？自我会成为阻碍吗？还是赋予力量？或是两者兼具？不。

Do you see it that way? Does ego get in the way? Is it empowering? Is it both sort No.

这个问题复杂且必然存在。我人生大半时间都在担任科技公司CEO。这个角色意味着自我意识绝非遥远之物。

It's it's complicated and necessary. I mean, you know, I've had look, I've spent more than half my life CEO ing a tech company. Right. Okay? And, you know, that is a I think it's actually very it means that one's ego is not a distant thing.

它与你每日相伴，因为与领导力和组织发展等事务紧密相连。若我是学者，或许可以把自我意识束之高阁，忽略其特性。

It's a thing that one encounters every day, so to speak, because it's all tied up with leadership and with how one develops an organization and all these kinds of things. So it may be that if I'd been an academic, for example, I could have sort of checked the ego, put it on a shelf somewhere, and ignored its characteristics.

在经营公司时，你会频繁被提醒这点。确实。

You're reminded of it quite often in the context of of running a company. Sure.

我是说，这就是关键所在。关键在于领导力。而领导力与自我意识密切相关。那么这意味着什么？对我来说，我很幸运地拥有合理的智力自信，可以这么说。

I mean, that's what it's about. It's it's about leadership. And, you know, leadership is intimately tied to ego. Now, what does it mean? I mean, what what is the you know, for me, I've been fortunate that I think I have reasonable intellectual confidence, so to speak.

也就是说，我是这样一种人——如果有人告诉我某事而我无法理解，我的结论不是自己愚笨，而是被告知的内容有问题。理查德·费曼也曾具有这种特质。他实际上比我更不迷信专家权威。

That is, I'm one of these people who at this point, if somebody tells me something and I just don't understand it, my conclusion isn't that means I'm dumb. My conclusion is there's something wrong with what I'm being told. That was actually Dick Feynman used to have that feature too. He never really believed in. He actually believed in experts much less than I believe in experts.

所以

So

哇。这真是自我意识根本性的强大特质——不是承认自己错了，而是认为世界错了。当面对与你深思熟虑的结论相悖的事实时，这种自我意识既有消极面也有积极面。你是否发现其消极面会阻碍认知？比如确信无疑时...

Wow. So that's a that's that's a fundamentally powerful property of ego, and saying, like, not that I am wrong, but that the the world is wrong and and tell me like, when confronted with the fact that doesn't fit the thing that you've really thought through, sort of both the negative and the positive of ego, Do you see the negative of that get in the way? Sort of being Sure. Confronted

我确实犯过因过度自信导致的错误。但关键在于，如果没有某种程度的智力自信，当看到前人长期尝试未果时，人们就会说：'这领域研究上百年了，我怎么可能突破？'我很幸运，年轻时在科学领域取得了一些成就，这培养了我原本可能不具备的智力自信。

are mistakes I've made that are the result of I'm pretty sure I'm right, and turns out I'm not. I mean, that's that's the, you know? But the thing is that the idea that one tries to do things that So for example, one question is, if people have tried hard to do something, and then one thinks, maybe I should try doing this myself, If one does not have a certain degree of intellectual confidence, one just says, well, people have been trying to do this for a hundred years. How am I going to be able to do this? And I was fortunate in the sense that I happened to start having some degree of success in science and things when I was really young, and so that developed a certain amount of intellectual confidence that I don't think I otherwise would have had.

某种程度上，我很幸运在粒子物理学的黄金时代从事研究。那段快速发展的时期给人强烈的成就感，因为就像采摘低垂果实般容易做出经得起时间检验的发现。

And in a sense, I was fortunate that I was working in the field, particle physics, during its sort of golden age of rapid progress. And that that kind of gives around a full sense of achievement, because it's kind of easy to discover stuff that's gonna survive if you happen to be picking the low hanging fruit of

一个快速扩张的领域。我完全理解《一种新科学》背后的自我意识驱动。要表达我的整体感受就是：若不允许这种自我意识存在，你永远不会写那本书。你会说'前人肯定尝试过了'，而不会持续深挖下去。

a rapidly expanding field. And the reason I totally I totally immediately understood the ego behind A New Kind of Science, to me, let me sort of just try to express my feelings on the whole thing, is that if you don't allow that kind of ego, then you would never write that book. That you would say, well, people must have done this. There's not You would not dig. You would not keep digging.

没错。我认为你必须带着那份自信，驾驭它，看看它能带你走多远。这确实如此。正是这样，你才能创造出非凡的作品。

That's right. And I think that was I think you have to take that ego and and ride it and see where it takes you. That that is Sure. And that's how you create exceptional work.

但我想那本书的另一点在于，它提出了一个非比寻常的问题：如何将一系列我认为相当宏大的理念整合起来。要知道，它们的重要性是由历史进程决定的。我们无法预知其重要性，只能大致判断它们的范畴。

But I think the other point about that book was it was a nontrivial question. How to take a bunch of ideas that are, I think, reasonably big ideas. They might you know, their importance is determined by what happens historically. One can't tell how important they are. One can tell sort of the scope of them.

这些理念的范畴相当广泛，且与此前的事物截然不同。问题在于，如何向人们解释这些东西？我曾有过这样的经历，比如我说，存在这些事物，有一种细胞自动机，它能做这个。

And the scope is fairly big, And they're very different from things that have come before. And the question is, how do you explain that stuff to people? And so I had had the experience of sort of saying, well, there are these things. There's a cellular automaton. It does this.

它能做那个。而人们的反应往往是，哦，它肯定就像这个，肯定就像那个。但其实不是，它是完全不同的东西。

It does that. And people are like, oh, it must be just like this. It must be just like that. So no, it isn't. It's something different.

对吧？所以

Right? And so

我本可以采取学术化的方式——虽然我非常高兴你做了你所做的——但你本可以继续零零散散地发表些小论文，然后不断遭遇类似的阻力。对吧？就像，与其直接抛出一个成果说‘这就是答案’，

I could have done sort of I'm really glad you did what you did, but you could have done sort of academically just publish keep publishing small papers here and there, and then you would just keep getting this kind of resistance. Right? You would get, like, as opposed to just dropping a thing that says, here it

是。

is.

这就是全部了。不。

Here's the full thing. No.

我的意思是，这是我的计算，基本上，你知道，你可以引入一些小片段。就像，一种可能性是它可以说是秘密武器。这是我不断在这些不同领域发现的东西。它们从何而来？没人知道。

I mean, that was my calculation, is that basically, you know, you could introduce little pieces. It's like, one possibility is like it's the secret weapon, so to speak. It's this I keep on discovering these things in all these different areas. Where did they come from? Nobody knows.

但我决定，考虑到一个人只有一次生命，而写那本书已经花了我十年时间，可以说没有太多回旋余地。一个人不能对所需时间估计错误三倍。我认为最好的做法，最能尊重知识内容的方式，可以说是尽可能有力地将其呈现出来。因为这不是一件……而且这是件有趣的事。你谈到自我，比如，我经营着一家以我名字命名的公司。

But I decided that in the interests of one only has one life to lead, and writing that book took me a decade anyway, there's not a lot of wiggle room, so to speak. One can't be wrong by a factor of three, so to speak, in how long it's going to take. I thought the best thing to do, the thing that most sort of that most respects the intellectual content, so to speak, is you just put it out with as much force as you can. Because it's not something where and it's an interesting thing. You talk about ego, and it's you know, for example, I run a company which has my name on it.

我曾想过为那些公司以自己名字命名的人成立一个俱乐部。这是个有趣的群体，因为我们不是一群自大狂。这不是重点，可以说是关于对自己所做的事情负责。从某种意义上说，任何你将自己置于风险中的事情都是动态的，因为从某种意义上说，我的公司只是碰巧以我的名字命名，但它某种程度上比我更重要，我在某种程度上只是它的吉祥物。

I thought about starting a club for people companies have their names on them. It's a funny group because we're not a bunch of egomaniacs. That's not what it's about, so to speak. It's about basically taking responsibility for what one's doing. And in a sense, any of these things where you're putting yourself on the line, dynamic because, in a sense, my company is sort of something that happens to have my name on it, but it's kind of bigger than me, and I'm kind of just its mascot at some level.

我的意思是，我恰好也是它相当强有力的领导者。

I mean, I also happen to be a pretty strong leader of it.

但这基本上显示了一种深刻且不可分割的投入。就像你的名字，史蒂夫·乔布斯的名字不在苹果公司上，但他就是苹果。是的。埃隆·马斯克的名字不在特斯拉上，所以这就像是情感上的意义。他的公司成功或失败，他会在情感上承受这些。

But But it's basically showing a deep inextricable sort of investment. The same your name, like Steve Jobs' name wasn't on Apple, but he was Apple. Yes. Elon Musk's name is not on Tesla, he So is it's like, meaning emotionally. His company succeeds or fails, he would just that emotionally would suffer through that.

是的。所以那就是

Yes. And so that's

是的，关键在于认识到这一事实，而我

Yeah, a good it's recognizing that fact, and I

而且，Wolfram是个相当不错的品牌名，所以效果很好。

And also, Wolfram is a pretty good branding name, so it works out.

对，没错，确实如此。我觉得史蒂夫在那笔交易上吃了亏。

Yeah, right, exactly. I think Steve had a bad deal there.

是的，你用姓氏弥补了这一点。好吧，那么在2002年2月，你出版了《一种新科学》，就个人层面而言，我

Yeah, you made up for it with the last name. Okay. So so in in 02/2002, you published a new kind of science to which sort of on a personal level, I

可以将我对细胞自动机和广义计算的热爱归功于它。我想很多人

can credit my love for cellular automata and computation in general. I think a lot