生命的物理，第2集：我们如何识别生命？

我认为Assembly所提供的这种哲学非常深刻、极具启发性，并为思考生命的物理本质开辟了一个全新的创造空间。

I think that philosophy that Assembly offers is deeply interesting, very provocative, and allows this entirely new creative space for thinking about the physics of life.

来自圣塔菲研究所，这里是复杂性。

From the Santa Fe Institute, this is Complexity.

我是克里斯·肯佩斯。

I'm Chris Kempes.

我是阿巴·伊莉·菲博。

And I'm Abha Eli Phoboo.

所以，克里斯，上周我们探讨了物理学与生命之间的深刻联系，并采访了两位原本是物理学家、却避开了生物学领域，最终深深投身于其中的人。

So Chris, last week we looked at how physics and life are deeply connected, and we talked to two people who started out as physicists who avoided the field of biology but ended up quite deeply entrenched in it.

是的，我认为我们开始看到物理学、化学和生物学之间的界限其实是非常任意的。

Yes, and I think what we're starting to see is how arbitrary the divides between physics, chemistry and biology really are.

当我们开始将这些不同学科融合在一起时，就能回答更宏大的问题。

We see that as we start to bring these different disciplines together, we can answer bigger questions.

我同意。

I agree.

今天，我们将更进一步，探讨生命是如何在地球上起源的，将那些并不总在一起合作的学科的思想和工具结合起来，同时也探讨生命在宇宙中可能存在于何处。

And today we're going to take a step further to look at how life originated here on Earth, bringing together ideas and tools from disciplines that don't necessarily always work together, and also where else life might be in the universe.

作为一名天体生物学家，这正是我的专长。

As an astrobiologist, this is right up my alley.

这又像是一场太空中的恐龙盛宴。

It's dinosaurs in space all over again.

确实如此。

It is.

你对这个话题其实也有很多见解，对吧？

And you actually have a lot to say about this topic too, right?

是的，我确实对这个话题有一些想法。

Yeah, I definitely have some thoughts on the topic.

过去二十年里，这一直是我研究的核心重点。

It's been the main focus of my research for the last twenty years.

今天，我非常高兴能邀请到我最欣赏的两位科学家——沃克和里卡德·索利斯。

And today I'm thrilled that we get to host two of my favorite scientists, Walker and Ricard Solis.

里卡德·索利斯是巴塞罗那庞培法布拉大学的研究员。

Ricard Solis is a researcher at the Universitat Pompeu Fabra in Barcelona.

他正在寻找导致复杂性基本组成部分出现的组织原则，这些组成部分包括软件的产生、开发、生命周期、计算过程和多细胞性。

He's searching for the principles of organization responsible for the emergence of fundamental components of complexity, which include the origins of software production, development, life cycles, computational processes, and multicellularity.

或者简单来说，他正在研究这一切是如何开始的。

Or to put it simply, he's studying how it all started.

我小时候非常幸运。

I was very lucky as a kid.

家里虽然没什么钱，但我们有一大图书馆。

At home we didn't have much money, we have a big library.

所以我很早就对生命系统产生了兴趣。

So I was interested in living systems very early.

我原本想当一名生物学家，但高中时有一位物理老师教我们物理。

I wanted to be a biologist, but I have this teacher in high school, a physicist, that taught us physics.

我爱上了物理学。

I fell in love with physics.

同时，还有一位数学老师，他对当时非常奇怪的事情感兴趣，比如如何构建大脑的模型。

And at the same time, have this teacher in mathematics that was interested in something as strange then as how to make models of brains.

当里卡德年轻时，他看到了一部改变他一生的电影，《科学怪人》。

When Ricard was young, he saw something that changed his life, the film Frankenstein.

当时，我和一位密友一起做了一个骨架，给它穿上衣服，就像在建造一个怪物。

And with a close friend at that time, we kind of built a skeleton which we dressed with some clothes, like building a monster.

当然，当一切完成后，并没有发生什么特别的事情。

Of course, when everything was done, not much happened.

但那正是神秘与可能性交织的魔力。

But it was like all the magic of the mystery, but the potential of that for happening.

对我来说，《科学怪人》长期以来一直是我思考生命、生物与非生物、生与死可能性的重要动力。

And actually for me, Frankenstein has been a kind of a big motivation over time to think about what's possible about life and the living and non living and life and death also.

小时候，我觉得这些奇妙、奇幻的故事世界，与科学可能也是这些奇妙想法的一部分，之间并没有什么明确的界限。

And to me as a kid, there was not much distinction about this universe of amazing, fantastic stories and the fact that science might be part of these kind of amazing ideas.

那么，究竟是什么让《科学怪人》中的生物，从一堆冰冷无用的躯体部件变成了有生命的存在？

So what was that thing that made the creature in Frankenstein turn from a heap of cold, useless body parts into something that was alive?

活着怎么可能呢？

How was being alive even possible?

为什么我们的世界有树木、人类、鸟类和真菌，而不仅仅是岩石、气体和化学汤？

Why is it that our world has trees and humans and birds and fungi, and not just rocks and gas and chemical soup?

如果我们发现宇宙其他地方的生命，我们能认出那是生命吗？

And if we found life in other parts of the universe, would we even know that we were looking at it?

第一部分：地球上的生命。

Part one, life here on Earth.

它是如何开始的？

How did it begin?

宇宙始于大爆炸，我们都听说过。

So the universe begins with the Big Bang, which we've all heard of.

现在，让我们快进到138亿年后。

Now, let's fast forward to 13,800,000,000 later.

从那次爆炸中产生的所有物质都冷却成了今天我们熟悉的物质形态。

Everything from that explosion has cooled down to the types of matter we're used to seeing today.

这些物质凝聚成了太阳系和恒星。

And that matter is spun down into solar systems and stars.

而在这里，是我们小小的太阳系。

And over here, we have our little solar system.

在这个太阳系中，是我们称之为地球的家园，围绕着太阳运转。

And inside that solar system is our home that we call planet Earth, floating around the sun.

在第一部分中，我们将短暂登陆地球，观察生命在这里演化的一些关键特征。

For part one, we're going to touch down on Earth for a moment, and we're going to look at some of the key characteristics of how life evolved here.

在这一时期，如果你观察这颗行星，可能会觉得上面没有任何生命。

At this point in time, if you look at the planet, you might think there's nothing living on it.

此刻，它只是一片炽热的液态物质。

Right now, it's just a bunch of hot liquid.

但这些炽热的液体中，简单的有机化合物已经结合在一起，形成了聚合物。

But that hot liquid has simple organic compounds that have clung together to form polymers.

如今，这种化学汤如何演化出复杂生命，仍然存在争议。

Now, how exactly this chemical soup gives rise to complex life is still up for debate.

但一旦形成了细胞，随着时间的推移，一些惊人的事情发生了。

But once you get cells, and as time continues to pass, something wild happens.

这里有一个小细胞，那里有一个小细胞，那边还有一群细胞，突然间，各种更复杂的形态到处出现。

There's a little cell here and a little cell there, a colony of cells over there, and then suddenly, more complex forms are showing up all over the place.

能够游泳、扭动、进食的生物，长有触角、消化道，有前后端之分。

Organisms that can swim and wiggle and eat, that have antennae and digestive tracts and a front end and a back end.

最初，这些生物根本不存在。

At first, there were none.

而现在，它们无处不在。

And now they're everywhere.

这一时期，即寒武纪大爆发，是主要动物门类出现的时候。

This period, the Cambrian Explosion, is when major animal phyla emerge.

节肢动物、蠕虫、脊索动物。

Arthropods, worms, chordates.

再过五亿二千万年左右，我们就来到了今天。

It will take another five twenty million years, give or take, to get to the present day.

但在我们星球的历史中，寒武纪大爆发是一个进化速度极快的时期。

But in the history of our planet, the Cambrian Explosion is a period of incredibly fast evolution.

那么，为什么这些生物会如此突然且迅速地出现呢？

So why do these organisms emerge so suddenly and so quickly?

以下是里卡德的再次发言。

Here's Ricard again.

它们的出现源于新物种之间的军备竞赛。

And they emerged in an arms race between new kinds of creatures.

猎物和捕食者开始同时存在。

Prey and predators started to be there.

我的意思是，对环境做出反应需要记忆。

I mean, reacting to the environment required memory.

记忆。

Memory.

信息和记忆至关重要。

Information and memory are key.

人们普遍认为，联想学习——这种神经网络能够连接外部输入并理解世界的能力——是推动大脑演化的重要革命之一。

And there's a consensus that associative learning, this kind of idea that you have a neural network that is able to connect external inputs and make sense of your world, was part of the big revolution that probably paved the way into brains.

然后，如果你往上追溯，可以看看人类记忆的例子。

And then if you go up, you like the example of memory in humans.

人类当然远离生命起源的早期阶段。

Humans, of course, are far away from the origins of life.

但有趣的是，人类之所以如此成功，很可能是因为记忆成为了未来的引擎。

But it's very interesting to see that in fact, probably were so successful because memory became the engine of the future.

我们能够创造出机制，利用存储记忆的同一套系统，不仅想象未来的下一刻，还能构想出完整的未来图景。

We were able to create mechanisms to use the same systems that are used to store memory, to actually imagine not only the next moment in the future, but imagine entire futures.

记忆使生物体能够适应其环境。

Memory allows an organism to adapt to its environment.

它不仅仅是从周围环境中获取信息。

It doesn't just take in information from its surroundings.

它还会存储信息，以备将来使用。

It stores information that can be used later.

一个经常让人惊讶的事实是，细菌的记忆能力竟然如此强大。

One thing that often surprises people is just how much memory bacteria have.

我们通常认为细菌是微小而简单的生物，但它们拥有非常丰富且令人印象深刻的基因组，这些基因组存储了应对不同环境所需的各种功能信息。

So we often think of bacteria as these tiny little very simple organisms, but they have these really rich and impressive genomes that carry around memory of all these different functions that are useful for responding to different environments.

你可以将这看作一本查找手册：当某种环境条件出现时，我过去曾遇到过，于是我翻阅我的查找手册，心想：哦，对了，这就是我对这种情况的反应。

And so you could almost look at that like a lookup book where I say, this environmental condition is happening, I've seen this in the past, and I just sort of scan through my lookup book and say, oh right, this is the response I have for that.

这就像一个非常简单的聊天机器人，它只知道如何回应它过去见过的句子，而这些句子来自环境，回应则是针对该环境有效的应对方式。

You know, it's almost like a very simple chatbot that just knows how to respond to sentences that it's seen in the past where the sentence is something from the environment and the response is the thing that works in that environment.

确实如此。

Definitely.

能够存储信息，为你适应未来的变化提供了安全的途径。

The fact that you can store information provides you safe ways of actually adapting to future changes.

因此，一旦记忆被建立起来，哪怕是非常短暂、简单的记忆——比如存储在单个分子中、记录环境基本信息的机制——很可能就迅速得到了进化推动。

So probably as soon as memory was in place, even a very short, simple memory, perhaps in a short single molecule that was kind of storing basic information out the environment, that was probably propelled quickly.

根据里卡德的说法，生命的另一个基本组成部分是计算。

According to Ricard, another basic component of life is computation.

你可以将生命定义为一种能够理解环境并做出适应性反应的能力，即感知环境并作出响应。

You can define life as something that is able to manage understanding the environment, so capturing the environment and reacting in adaptive ways.

你可以说这是一种计算。

And you could say that this is a computation.

毫无疑问，一旦记忆成为这一过程的一部分，许多革命便随之发生。

And for sure, as soon as memory came as being part of the story, probably a lot of revolutions happened.

但事实上，我认为我们可以将计算简化为输入、操作和输出。

But really, I think we can reduce computation to say input, operation, output.

在这一框架下，许多事物都算作计算，包括最简单生命形式中的大部分活动。

And then under that umbrella, lots of things count, including much of what's going on in the simplest life forms.

拥有记忆的这一优势，推动了进化从化学汤中漂浮的小团块，一路发展到人类大脑、大象和鲸鱼。

This advantage of having memory pushes evolution down the path from little blobs hanging out in chemical soup all the way to human brains and elephants and whales.

最初非常简单的输入和输出，逐渐演变为极其复杂的行为和抽象能力，造就了今天我们所生活的这个无比多样的星球。

And what starts out as very simple inputs and outputs turn into very sophisticated behavior and abstraction, this incredibly diverse planet we live on today.

在这颗星球上，我们见证了极其复杂的化学反应在细胞中被选择并延续了数十亿年，最终构建并支撑起所有更复杂的结构，直至发展出城市和卫星。

On this planet, we've seen some very complex chemistry get selected in cells and persist over billions of years and then eventually scaffold and build all of these other more complex architectures on top of it, leading all the way up to cities and satellites.

那是萨拉·沃克。

That's Sara Walker.

当然，我是萨拉·沃克。

Sure, I'm Sara Walker.

我是亚利桑那州立大学的教授，同时也是圣塔菲研究所的外部教员。

I'm a professor at Arizona State University and also an external faculty at SFI.

我主要是一位物理学家。

And I am a physicist primarily.

我想这就是我看待世界的方式。

I guess that's how I think about the world.

萨拉对物理学的热爱始于她在大学期间。

Sara's love of physics started when she was in college.

我大学前两年在社区学院就读，因为我还不知道自己该做什么。

I went to community college for my first two years of college because I didn't know what to do.

而且，我的家人也没有人上过大学。

And also, my family hadn't gotten to university.

于是我第一学期选了我能选的所有科学课程。

And so I took my first semester just all the science classes I could.

我记得自己去上了物理课。

And I just remember going to physics.

那位教授非常随和。

And the professor there was super casual.

他手里拿着茶讲课，谈论磁单极子，说科学家们预测了它们的存在，但没人知道它们是否真的存在，而我们可以出去寻找它们。

He was lecturing with tea in his hand and he was talking about magnetic monopoles and how scientists had predicted them and nobody knew if they existed, but we could go out and look for them.

我被这个想法深深吸引：人类的思维能够提出这些尚不确定对错的理论，然后真正去用现实检验它们，这让我觉得太有趣了。

And I was just so deeply fascinated by this idea that human minds could come up with these theories that we didn't know if they were right or not, and then actually go test them against reality was so interesting to me.

我立刻放弃了之前所有想过要做的事，决定一定要成为物理学家。

I just dropped everything I thought I wanted to do before that and immediately decided I wanted to be a physicist.

但和她的其他嘉宾一样，她最终突破了物理学的界限，开始研究生命。

But like her other guests, she eventually branched out beyond the confines of physics to study life.

但我研究工作所关注的问题，主要是关于生命是什么，我们如何理解生命的涌现，以及宇宙中可能存在的其他形式的生命。

But the problems I'm interested in addressing with my work are primarily about what life is and how we can understand how life emerges and what other kinds of life might exist in the universe.

和里卡德一样，萨拉也认为记忆对进化很重要，但更准确地说，是时间和信息的积累。

And like Ricard, Sara also thinks memory is important for evolution, but to be more precise, the accumulation of time and information.

你和李·克罗宁最近在《自然》杂志上发表了一篇关于组装理论的论文。

You and Lee Cronin recently published a paper in Nature on Assembly theory.

我依稀记得还有一些其他贡献者。

I vaguely recall other contributors.

是的，我应该说，你、李·克罗宁、迈克尔·洛克曼——他就在圣塔菲研究所——还有两位非常出色的博士后，刚刚共同发表了这篇关于组装理论的论文。

Yeah, I should say you and Lee Cronin and Michael Lockman, who's at the Santa Fe Institute myself, and two really wonderful postdocs just published this paper on Assembly theory.

这两位出色的博士后是阿布哈·艾莉·菲博和丹尼尔·奇格尔。

Those two wonderful postdocs are Abha Eli Phoboo and Daniel Chigel.

李、萨拉、克里斯和迈克尔在疫情期间每周都通过Zoom开会。

Lee, Sara, Chris, and Michael met every week over Zoom during the pandemic.

他们一连几个小时讨论和争论组装理论，偶尔才停下来吃点零食或伸展一下身体。

They discussed and argued about Assembly theory for hours at a time, only stopping every so often to eat a snack or stretch their legs.

因此，根据组装理论，

So according to Assembly theory,

对于任何生物体来说，构建一个物体也需要时间。

for any living being It also takes time to build the object.

就像进化发生所需的时间一样。

As in time for evolution to happen.

因此，我对‘组装’有一种解释，将其视为一种真实的物理属性：进化产生的物体具有与其形成所需信息量相关的尺寸和时间。

And so I have an interpretation of assembly as an actual physical property where evolved objects have a size and time that's associated with how much information is necessary for them to come into existence.

我认为，组装理论为理解生命的物理学提供了一种深刻的哲学视角，极具启发性，并为思考生命的物理学、生命的时序性以及生命与信息的关系开辟了全新的创造空间。

And I think that philosophy that Assembly offers for understanding the physics of life is deeply interesting, very provocative, and allows this entirely new creative space for thinking about the physics of life and the temporality of life and how life relates to information.

因此，在组装理论中，信息、时间和物质本质上是同一回事，它们体现在那些深度进化的产物中。

And so information and time and matter are all kind of the same thing in assembly, and they're manifest in objects that are deep products of evolution.

如果没有此前发生的所有进化步骤，地球上今天存在的所有植物和动物都不可能诞生。

We couldn't have all the plants and animals that exist on Earth today without all of the evolutionary steps that happened before we got here.

萨拉认为，这些步骤并非偶然自发发生。

And Sara argues that those steps didn't just spontaneously happen.

我曾被教导说，事物有可能因量子涨落而自发出现，因为这与我们当前的物理学理论——无论是热力学还是量子力学——是一致的。

I was taught that it's possible for things to spontaneously fluctuate into existence because that's consistent with our current theories of physics, whether it's thermodynamics or quantum mechanics.

因此，这种观念渗透了大量科学文化，人们认为可以免费获得复杂性，而无需通过进化过程来生成它。

So this permeates a lot of scientific culture where people think you can get complexity for free and you don't need an evolutionary process to generate it.

但组装理论提出了一个非常具体的论断：在化学空间中，存在一个边界，当组装一个分子所需的步骤超过这个边界时，如果没有选择和进化，你就绝不可能期望该物体自然出现。

But assembly theory makes a really concrete statement that in chemical space, is a boundary that exists at a certain number of steps for assembling a molecule above which you should never expect the object to exist without selection and evolution.

因此，不存在自发的波动。

And so there is no spontaneous fluctuation.

要达到这些物体并观察到它们大量存在，唯一途径就是通过选择和进化的过程。

The only way to get to these objects and observe them in any abundance is via the process of selection and evolution.

为了说明这一点，让我们假设生命的所有化学构建模块都只是乐高积木，而你拥有一套哈利·波特中霍格沃茨城堡的乐高套装。

To illustrate, let's pretend that all the chemical building blocks for life are simply LEGO bricks, and you have a LEGO set for Hogwarts, the castle in Harry Potter.

乐高积木有特定的拼接方式。

LEGO bricks have certain ways that they can fit together.

因此，在乐高世界中，你可以构建出某些特定结构。

And so there's certain structures you can build in the LEGO universe.

而有些结构，比如乐高霍格沃茨城堡，需要非常具体的说明书才能搭建出来。

And some structures, like the LEGO Hogwarts Castle, require very specific instructions for you to build them.

如果我现在把所有零件都放在桌上给你，你很难把它拼出来。

If I just gave you all the pieces on the table right now, you'd probably be very hard to build it.

即使你心里有城堡的概念，或许还记得电影里霍格沃茨城堡的样子，你也几乎不可能准确地重现它。

Even with the idea of a castle in your mind and maybe having some memories of what the Hogwarts Castle looks like from the movies, you probably wouldn't exactly be able to reproduce it.

但如果我说，别自己动手拼了，只管摇晃桌子，你认为这些乐高积木会自发地组装成霍格沃茨城堡吗？

But if I said, Forget about building it yourself, just shake the table, do you think it's likely that the Lego Hogwarts castle is gonna spontaneously assemble out of those Lego building blocks.

直觉上，这几乎不可能发生。

It's very intuitive that that's probably not going to happen.

即使摇晃整个宇宙寿命那么久，也不会发生，实际上我认为这根本不可能发生。

Not in the lifetime of the universe of shaking that table would it happen, and I actually think it would be impossible for that to happen.

那么，像乐高霍格沃茨城堡这样的结构究竟是如何出现的呢？

So how do you actually get a structure like Lego Hogwarts emerging?

你需要有具体的信息来指定这种结构以及建造它的特定路径。

Well, you need to actually have the information to specify that specific structure and the specific pathway to build it.

因此，这可以说是组装理论的核心概念之一。

And so this is sort of one of the key concepts of assembly theory.

如果你有一个非常简单的乐高物件，你可能能够自己拼出来。

If you had a really simple Lego object, you might be able to build it.

但如果你要拼的是像乐高霍格沃茨这样复杂的结构，那就需要大量的信息约束才能达到这个特定的物件。

But if you had something complex like Lego Hogwarts, it really requires a lot of informational constraints to get to that specific object.

因此，可能的乐高城堡组合空间是巨大的。

And so the space of possible Lego castles is huge.

用同一套积木能拼出的所有乐高物件的可能性空间甚至更加庞大。

The possible space of Lego objects you could build out of the same set of building blocks is even vaster.

所以你需要思考，在这个空间中需要多少约束才能达成这个特定结构，从而真正理解这正是进化选择过程留下的、该结构得以存在的特征。

And so you have to think about how many constraints in the space to get to that specific structure to really think about how it's a signature of this evolutionary process of selection for this specific structure to exist.

这展示了组装理论的几个特点。

And so this shows a few features of assembly theory.

一是我们构建任何物件都基于某种递归过程——你只能在已经拼好零件的基础上，才能构建出更复杂的整体。

One is we build objects always based on some recursive process, so you can only build up to an object if you've built the parts already.

因此，这在某种程度上体现了历史偶然性与记忆的特性，我们感觉每个物件都蕴含着宇宙构建它的途径。

And so this is sort of part of the historical contingency in memory that we feel like is embedded in every object, that every object contains the ways that the universe could build it.

而且，一个对象被选中的难度有多大，也通过生成该对象所需的最小深度被嵌入在对象本身中。

And also the idea that how hard it is for an object to be selected is embedded in the object by this sort of minimal depth to generate the object.

这些乐高积木有无数种组合方式，但最终产品之所以是霍格沃茨城堡，而不是一堆随机的附属物，是有原因的。

There are so many different ways those LEGOs could come together, and there's a reason the final product is a Hogwarts castle and not a bunch of random appendages.

组装理论认为，尽管用这些乐高积木可以组装出无数种不同的形状，但它们并不会全部出现，只有这座城堡在极长的时间中被构建出来。

Assembly theory says that although there are many, many possibilities for assembling different shapes with those LEGOs, they don't all come into existence, Just that castle over a very, very long time.

当你仔细想想，这是一件相当了不起的事。

And when you think about it, that's a pretty spectacular thing.

它告诉我们，某种东西正在被选择。

It tells us that something is being selected.

在第一部分中，我们探讨了地球上生命演化的一些关键因素。

In part one, we looked at some of the crucial factors of a life evolving here on Earth.

信息与记忆的积累、计算能力，以及进化的所需时间。

The accumulation of information and memory, the ability to compute, and time for evolution.

现在我们将时间快进到20世纪40年代末的美国。

We're now going to speed up to the late 1940s here in The United States.

没错。

That's right.

我们来到了二十世纪中期，数学家和物理学家约翰·冯·诺伊曼正试图设计一台机器。

We've landed in the middle of the twentieth century, and the mathematician and physicist John von Neumann is trying to design a machine.

他想要一种能够自主生长和进化的装置，本质上是二十世纪版本的人工智能。

He wants something that would grow and evolve on its own, basically like a twentieth century version of artificial intelligence.

因此，在他推演过程中，他提出一个理论：这种自我复制的机器必须在某个地方存储指令。

So as he's working this out, he comes up with a theory that this self replicating machine must store instructions somewhere.

为了进行复制，它会读取这些指令。

And in order to reproduce, it reads the instructions.

但在复制过程中，这些指令也会被一同复制。

But during the process of replication, these instructions are also replicated.

在试图回答机器自我复制所需条件的问题时，他最终构建了一个包含指令、复制器及各种组件的逻辑体系。

In trying to answer the question of what is needed for a machine to self replicate, he ended up in a logic organisation that had instructions, a replicator, all kinds of things.

几年后，时间来到二十世纪五十年代初，伦敦正下着雨。

A few years later, it's the early 1950s in rainy London.

国王学院的科学家们能够使用X射线衍射技术，深入观察细胞核内部及其中物质的结构。

Scientists at King's College are able to use X-ray diffraction to look way down into the nucleus of the cell and at the structure of the material inside.

他们发现了什么？

And what do they find?

指令、复制器，还有各种各样的东西。

Instructions, a replicator, all kinds of things.

是DNA。

It's DNA.

记住，冯·诺依曼在提出复制理论时，只是想将其应用于机器，而当时还没有人知道它对人类自身存在至关重要。

Remember, von Neumann came up with a theory of replication when he was just trying to apply it to a machine, before anyone knew it was central to our own human existence.

事实证明，冯·诺依曼的理论或许对生命在各处的复制具有根本性意义。

It turns out, maybe von Neumann's theory is pretty fundamental to life replicating everywhere.

是的，我的意思是，这确实值得我们停下来好好思考和欣赏：计算机科学早期采纳的理论，比如图灵机，它严重依赖于线性磁带，而这正是我们建模大多数计算系统的方式。

Yeah, I mean, that's something I think is worth stepping back and really appreciating, that the way that computer science took on early theories, you know, the Turing machine, which is heavily reliant on this linear tape, which is really the way that we model most computational systems.

这是大多数计算机科学理论的基础。

It's the foundation of most computer science theory.

正如你提到的，冯·诺依曼设想的计算方式，包括我们为早期计算机构建的各种磁带，令人惊讶的是，当我们最终弄清楚细胞内遗传系统的工作原理时，竟然也涉及到了这些磁带。

And then the way, as you mentioned, that von Neumann envisioned computation, all the different sorts of tapes that we built for early computers, it is sort of amazing that then when we finally figured out what was happening inside cells with the genetic system, it involved all these tapes.

于是你有了这条DNA磁带，它被聚合酶读取，然后将另一组磁带传递给核糖体，核糖体再由此生成各种功能蛋白。

So you have you have this DNA tape that gets read off by these polymerases, and then that passes another set of tapes into the ribosome, which then creates all these functional proteins.

因此，这实际上是一个多磁带系统，你不断地通过各种装置读取这些线性磁带。

And so it's actually a multi tape system where you're, you keep reading these linear tapes through devices.

当然，与抽象计算机相比，这里可能多了些步骤。

And sure, there's maybe more steps there than you would need for an abstract computer.

你知道，需要经过更多步骤，将一种磁带传递给另一种机器，最终产生功能。

You know, there's more steps of passing one type of tape to another type of machine and using that eventually to produce function.

而这一部分可能有些任意性。

And that part might be a little bit arbitrary.

多步骤的过程可能并不会被保留。

The multi step part might not be preserved.

但你对线性聚合物——也就是这些线性磁带——作为生命中信息与记忆系统的基本组成部分，是相当坚定的。

But you're pretty committed to linear polymers, you know, these linear tapes as a fundamental aspect of life anywhere, at least for the information and memory system.

是的，当然。

Yeah, yeah, definitely.

这些线性聚合物是信息携带分子复杂性的一种基本限制。

These linear polymers are kind of a fundamental constraint to the complexity of information carrying molecules.

这可能对限制宇宙或我们在其他地方发现的事物有深远影响。

Then this probably has a lot of implications in constraining the universe or what we can find out somewhere else.

存在能够编码生命与繁殖指令的线性聚合物，这可能是生命本身的一项基本法则，就像信息、记忆、计算和时间一样。

The fact that there could be instructional tapes linear polymers that map out the codes for life and reproduction is a possible law of life itself, just like information, memory, computation, and time.

这将我们带入我们探索的下一阶段。

And this brings us to the next phase of our journey.

如果我们要在宇宙中寻找其他生命，那种生命是否也基于线性指令构建？

If we were to look for other life out there in the Universe, would that life be built on linear instructions too?

我们的世界还向我们揭示了其他地方可能存在的什么可能性？

What else does our world tell us about what might be possible elsewhere?

这是宇宙中的生命。

This is Life in the Universe.

如果我们到别处寻找生命，我们能知道如何找到它吗？

If we look for life elsewhere, would we know how to find it?

在生物学中，我们经常提到一个叫做保守性的概念。

In biology, we frequently refer to a concept called conservation.

简单来说，保守性是指我们在截然不同的生物体之间看到的共同特征。

Conservation, to put it simply, is when we see shared characteristics across very different organisms.

例如，你和我与你阁楼里的蜘蛛或大白鲨就非常不同。

For example, you and I are very different from, say, a spider in your attic or a great white shark.

但我们都有含有DNA的细胞和能够看见的眼睛。

But we all have cells with DNA and eyes that see.

这些共同的特征指向了我们在前两集中探讨的生命的基本规律。

And these shared traits point back to underlying laws of life that we've been exploring in the past two episodes.

在许多情况下，针对特定问题的具体解决方案——比如大脑的连接方式或眼睛的结构——在进化历史中多次被独立发现。

In many cases, the specific solutions to particular problems, like the way brains are wired or the way our eyes are structured, have been found again and again independently all over the history of evolution.

这些解决方案似乎都相同，仿佛存在一种无法回避的基本逻辑。

And the solutions seem to be the same, As if there was kind of a fundamental logic that is inescapable.

这正是我们的梦想——能否真正建立一个理论框架。

And that's kind of the dream we have, whether we could actually build some theoretical framework.

但在逻辑层面，我认为什么可能、什么不可能，存在着非常根本的限制。

But in terms of the logic, I do think there are very, very fundamental constraints on what is possible.

我把宇宙中的进化想象成一条保龄球道，但不是成人用的，而是儿童保龄球道，两边都装了挡板。

I think of evolution across the universe like a bowling alley, but a kid's bowling alley where the bumpers have been put up.

这些挡板，如果你还记得的话，就是人们在保龄球道两侧设置的，用来防止球掉进排水沟的东西。

So these bumpers, if you remember, are sort of the things that people put up on the side of the bowling alley to keep the ball from going into the gutter.

对我来说，进化就像一个不太会打保龄球的孩子扔出的球，在这条有挡板的球道上漫无目的地滚动。

So for me, evolution is sort of a wandering path of a bowling ball thrown maybe by a kid who's not so good at bowling down one of these alleys.

但这条球道两侧的挡板，就是物理学定律、化学定律，以及最近发现的一些信息与计算规律。

But the bumpers on that alley are the laws of physics or the laws of chemistry or certain sorts informational computational laws that have recently been discovered.

进化创造了巨大的多样性，也产生了许多独特的解决方案，但始终被限制在这条球道之内。

Evolution creates all this diversity and creates a lot of unique solutions, but always in this constrained alley.

因此，我认为要理解生命的普遍规律，关键在于思考塑造球道两侧挡板的因素，而不是过分关注保龄球在球道上那条杂乱无章的具体轨迹。

And so I think the way we get to the universals of life are to think about what's shaping the two sides of the bowling alley and less about the sort of detailed messy path that the bowling ball follows down that alley.

所以当我思考任何一颗行星时，我首先想的是那些物理限制。

So when I'm thinking about any planet, the things I want to think about first are sort of the physical constraints.

你知道，那里的压力如何？

You know, what's the pressure like?

那颗行星的重力如何？

What's the gravity of the planet like?

流体的粘度如何？

What's the viscosity of the fluid?

这些允许生命形成的保龄球球道挡板，导致了保守性——无论生命在何处出现，都会反复出现相同的特征和动态。

These bowling alley bumpers that allow life to form result in conservation, the same characteristics and dynamics showing up again and again, no matter where life arises.

我最喜欢的一个例子来自人工生命。

And one of my favorite examples comes from artificial life.

这个领域在三十年前兴起，本质上是试图看看我们是否能在计算机中真正再现或模拟生命及其演化，这意味着我们不涉及DNA或生物物质。

This field that emerged three decades ago, essentially is trying to see whether we can actually reproduce or mimic life and evolution of life within computers, which means that we don't play with DNA or biological matter.

我们操作的是算法和程序。

We play with algorithms, programs.

我们模仿的是自然系统中观察到的现象，但原则上，在计算机模拟中可能会发生许多不同的情况。

We mimic things that we see in natural systems, but actually many different things could happen in principle because it's in silico.

它可能朝着完全不同的方向演化。

It's something that can evolve in totally different directions.

但事实上，当你尝试模拟一个随时间演化的生态系统时，你会发现令人惊叹的现象。

But the truth is that when you try to make a simulation, artificial life simulation of an ecosystem that evolves in time, it's amazing to see that.

随着时间推移，你会看到寄生虫、超寄生虫、捕食者与猎物、性行为、合作等现象不断出现，仿佛这些组织形式是不可避免的，这暗示着如果我们能回到过去重新运行演化过程，生物圈可能会不同，但依然会非常熟悉。

Over time you see emergence of parasites, hyperparasites, predators and prey, sex, cooperation, you see repeatedly the same logic of events, as if these kinds of forms of organisation were inevitable, suggesting that maybe if we were able to get back in time and rerun the type of evolution, the biosphere will be different, but clearly familiar.

既然计算机模拟会演化出寄生虫，而我们在生命树的各个分支中——从细菌到复杂的哺乳动物——都观察到了寄生虫，你是否愿意打赌宇宙中任何地方都存在寄生虫？

So because computer simulations evolve parasites, and we see parasites across the tree of life and for all sorts of different organisms ranging from bacteria up to very complicated things like mammals, are you willing to bet there are parasites everywhere in the universe?

只要有生命，就一定有寄生虫？

Anywhere there's life, there's parasites?

你是说

Is that

是的。

Yeah.

是的。

Yeah.

是的。

Yeah.

这是其中一件事。

That's one of the things.

我真想看到这方面的证明，因为它看起来如此普遍。

I would love to see a proof of that because it looks to be such a general thing.

你提到在生命中，从病毒到复杂生物，寄生实体似乎总是随时可能出现。

You mentioned in life and from viruses to complex organisms, parasitic entities are always apparently ripe to appear.

但即使是我也会打赌，我们在社会和经济组织中也能看到类似的寄生形式。

But even I will bet that we can see similar forms of parasitism in social and economic organisations.

所以对我来说，寄生可能是任何能够进化的复杂系统都无法避免的东西。

So to me, parasites are probably something that you cannot avoid when you have a complex system that can evolve.

好的，所以寄生、捕食者、猎物、合作。

Okay, so parasites, predators, prey, cooperation.

如果我们去宇宙中寻找生命，这些可能是我们常见的现象。

These are some of the common things that we might find if we were to go looking for life in the universe.

到目前为止，我们已经讨论了生命的许多特征，因此我们可以预测外星生命可能的样子和行为方式。

And so far, we've talked about many characteristics of life, so we can predict all kinds of things about what alien life might look like and how it would behave.

但有没有一种更简单、更根本的方法来定义什么是生命？

But is there a simpler, more fundamental way to determine what life is?

如果我们正在另一个星球上寻找生命，能否拿起一个物体，指着它明确地说：这个东西曾经是活的，它是进化的产物？

If we were searching for life on another planet, could we take one object, point at it, and definitively say, this thing was once alive, and it's a product of evolution?

让我们回到萨拉和我们关于组装理论的研究。

Let's return to Sara and our work on assembly theory.

我们认为，组装理论或许能够做到这一点，即测量一个物体的复杂程度，从而判断其进化程度。

We think it may be possible to use assembly theory to do just this, to measure how complex an object is, and therefore how evolved it is.

这可能是判断一个物体是否为活体生物或源自活体生物的关键线索。

And that could be the clue as to whether or not it's a living organism or from a living organism.

组装理论有两个可观测指标。

Assembly theory has two observables.

一个是组装指数。

One is the assembly index.

这是复杂性的度量。

That's the measure of complexity.

另一个是副本数量。

And the other is copy number.

也就是说，这种物体只有一个，还是有很多个。

So if only one of this object exists or if there are many.

因此，对于任何物体，你可以想象通过将两个基本部分粘合在一起，然后将过去构建出的任何东西递归地粘合起来，逐步构建出这个物体。

And so for any object, you can think about building it up from elementary parts by sticking two parts together and then taking any things that you've built in the past and sticking them together recursively to build up to your object.

而这个过程中最短的路径，就是我们所说的组装指数。

And the shortest path in that is what we call the assembly index.

然后我们还想考察一个物体有多少个副本。

And then we also want to look for how many copies of an object you have.

这与实验相关，因为对于分子来说，你可以使用一种叫做质谱仪的仪器来测量组装分子所需的最小路径，这种仪器基本上会将分子打碎。

And this is tied to experiments because it turns out for molecules, you can measure this minimal path to assemble the molecule using an instrument called a mass spectrometer, which basically fragments the molecules.

如果你统计质谱中的峰的数量，就可以将其与组装指数关联起来。

And if you count the number of peaks in the mass spec, you can correlate it with the assembly index.

事实上，测量分子的这一特性并不依赖于质谱仪。

And in fact, it's not dependent on a mass spec to measure this property of molecules.

你可以用核磁共振和红外光谱测量来实现。

You can do it with NMR and infrared measurements.

但在最初的实验中，只使用了质谱仪。

But in the initial experiments, it was just done with mass spec.

此外，为了检测进化，你必须检测高丰度的物质，这样才能排除它们可能是随机形成的这一假设。

And then also in order to detect evolution, you have to detect objects in high abundance, which allows you to talk about ruling out the hypothesis that they could have been formed randomly.

因为在一个指数级的空间中，某种特定步骤的随机事件可能只在宇宙的生命周期中发生一次，但再也不会重复。

Because a random event of a certain number of steps in an exponential space might happen, I don't know, once in a lifetime of the universe, but never again.

因此，这正是我们之所以认为应该存在一个阈值的原因之一：如果你在进行这种逐步构建——比如连接原子、形成化学键——当步骤达到大约15步时，产生某个特定分子的概率大约是每摩尔一个。

And so actually, this was part of the reason that we had some sense that there should be a threshold because if you're doing these building up of steps, say you're attaching atoms and making bonds and building up, if you go about 15 steps, the likelihood of producing a particular molecule is about one in a mole.

一摩尔是10的23次方个分子，也就是阿伏伽德罗常数个分子，你可能只拥有一个特定构型的分子。

A mole is 10 to the 23, so Avogadro's number of molecules, you might have one of a particular configuration.

因此，李的实验室就是这样做的。

And so that's what Lee's lab did.

他们进入实验室，采集了大量样本，尝试测量不同非生命和生命样本的组装情况，其中一些样本由NASA提供但做了盲处理，以确定是否存在一个阈值，只有生命体才会产生具有很高组装指数的分子。

They went in the lab and took a whole bunch of samples and tried to measure the assembly of different non living and living samples, and some of them were provided by NASA but blinded, and to determine if there actually was a threshold above which molecules were only found in life with very high assembly index.

事实上，实验确实验证了这一点。

And indeed, that's what the experiments actually verified.

如果你观察所有这些多样的样本，只有生命体才会产生超过15步的分子。

If you look at all these diverse samples, living things are the only things that produce molecules with more than 15 steps.

如果组装理论是正确的，那将是革命性的。

If assembly theory is true, it's groundbreaking.

它彻底改变了我们对物理实体、时间和信息的思考方式。

It reshapes the way we think about physical beings, time and information altogether.

如果我们去宇宙其他地方寻找生命，该理论告诉我们，应该寻找组装指数为15的分子。

If we went looking for life in other parts of the universe, the theory tells us that we'd want to look for molecules with an assembly index of 15.

这就能确保是生命。

That guarantees life.

但如果我们真的在其他地方发现了生命，谁知道它会不会看起来和地球上的生命有任何相似之处呢？

But if we did find life elsewhere, who knows if it would appear to be anything close to what life looks like here on Earth?

很难想象我们不知道的东西。

It's hard to imagine what we don't know.

这让我想起，你知道的，你走进厨房，想着要发明一种前所未有的革命性新饼干。

It sort of reminds me of thinking about, you know, you go into the kitchen and you say, want to build a revolutionary new type of cookie that's unlike any cookie anyone's ever eaten before.

你坐下来，第一个蹦进脑海的却是你祖母的饼干食谱。

And you sit down and the first thing that comes to mind is your grandmother's cookie recipe.

那饼干太棒了，你对它了如指掌。

And it's so good and you know everything about it.

真的很难不去受这些知识影响，不去想到祖母的巧克力豆饼干食谱，对吧？

And it's really hard to not let that knowledge seep in to think of grandma's chocolate chip cookie recipe, right?

重要的是要保持开放的心态，认识到我们自以为知道的东西并不总是确定无疑的。

It's important to be open to the idea that what we think we know isn't always guaranteed to be fact.

对里卡德来说，这甚至延伸到了自然选择本身。

For Ricard, this even extends to natural selection itself.

自然选择创造了复杂性的强大原则，以至于很难跳出这个特定的思维框架。

There are so powerful principles of creating complexity that are tied to natural selection that it's difficult to think outside of that particular box.

我一直在想，在不同的背景下，是否可能存在与自然选择完全不同的规律，从而引发复杂性的涌现？

I always wondered, in a different context, could it be possible to actually have laws different distinct from natural selection that can trigger the emergent of complexity?

我很难想象这种情况，但我保持开放的心态。

I have a hard time to imagine that, but I do have an open mind.

事实上，理解生命何时以及如何起源，甚至什么是生命本身，仍然是一个持续进行的讨论。

The reality is understanding when and how life originates and what even constitutes life is an ongoing conversation.

我们可以找到跨物种的守恒概念或组装理论的证据，但重要的是要记住，科学和生命一样，也在不断演化。

We can find evidence for concepts like conservation across species or assembly theory, but it's important to remember that science, like life, evolves too.

今天我们一开始便向两位受过物理学训练的研究者提问，探讨地球生命的起源以及生命的普遍特性。

We started off today's conversation by asking two researchers, both trained in physics, about the origin of life on Earth and the universal qualities of life.

但当我问萨拉物理学能告诉我们关于寻找生命的信息时，她对将物理学视为一种已完成的体系持保留态度。

But when I asked Sara what physics can tell us about the search for life, she was hesitant to talk about physics as something that is complete.

人们通常将物理学理解为已知的理论，而不是进行物理学研究的过程，我认为这两者是不同的。

People usually have this sort of connotation of known physics and not the act of doing physics, and I think those are different things.

物理学作为一门学科，在大学里教授时有其特定的方法和研究问题，人们确实试图运用这些知识体系来理解宇宙中的生命。

So there's physics as a discipline that's taught in universities that has a of approaches it uses and a set of problems it addresses, and people do try to use those bodies of knowledge to try to apply to understanding life in the universe.

但我用物理学研究宇宙中生命的方式，是更多地思考我们用来描述世界行为的抽象概念，以及我们是否需要提出新的理论、新的抽象原则或想法来解释生命是什么。

But the way I approach using physics to study life in the universe is to think much more about the nature of the abstractions that we use to describe how the world behaves and whether we need to come up with new theories or new abstract principles or ideas that could explain what life is.

这某种程度上就是从事物理学的真正行为，但更接近于该领域的前沿或边界，因为我们还不知道那些抽象概念或类似规律是什么，正是通过这种从事物理学的艺术来创造新的工具。

And that's sort of the act of doing physics, but in a much more sort of existing at the frontier of the field or the boundary of the field because it's physics that we don't know yet because we haven't discovered what those abstractions are or what those law like regularities are that's using the sort of art of doing physics to come up with new tools.

在与里卡德和萨拉的对话之后，克里斯和我坐下来讨论了他对组装理论的看法。

After our conversations with Ricard and Sara, Chris and I sat down to talk about his perspective on Assembly theory.

你是最近发表在《自然》杂志上关于组装理论论文的合著者之一，与萨拉和李·克罗宁共同署名，这篇论文在科学界引发了巨大讨论。

You are one of the co authors, along with Sara and Lee Cronin, on the recent paper published in Nature about assembly theory, and it stirred up a huge discussion in the scientific community.

各方的反应如何？你对此怎么看？

What's the reaction been like, and what do you think about it?

目前科学界和组装理论的发展状况如何？

Where's the science and assembly theory now?

是的，我认为各方的反应非常有趣。

Yeah, so I think the reaction has been really interesting.

实际上，我认为大部分的反应都源于修辞问题。

And I actually think most of the reaction comes down to rhetoric.

我认为核心在于我们所说的‘进化’到底是什么意思。

And I think it centers around what do we mean by evolution?

我们所说的‘选择’又是什么意思？

What do we mean by selection?

因此，我们在论文中提到‘选择’，其实指的是广义的选择，但人们由于历史原因，自然会联想到达尔文进化论中基于遗传的自然选择。

So we say selection in this paper, and we really meant generalized selection, but people are naturally because of the history, thinking about natural selection by Darwinian evolution using genetics.

而我们的观点是，当你开始谈论遗传时，你已经走在生命起源轨迹的很远之后了。

And our point really is when you get to talking about genetics, you're already very far down the origin of life trajectory.

我们需要新的理论、新的描述方式，以便能够讨论生命进化史中最初始的时刻。

We need new types of theories, new types of descriptions that allows one to talk about the very earliest moments in the evolutionary history of life.

组装理论就是实现这一点的一种方式。

Assembly theory is one way to do that.

组装理论是捕捉早期进化的一种方式。

Assembly theory is one way to capture early evolution.

当时有很多批评，我认为其中最突出的一点是，这并不是一个新观点。

There was a lot of criticism, and I think one of the criticisms that came to the fore was the fact that this was not a new idea.

所以我是一个极端的多元主义者，在某种程度上，我不认为存在什么真正的新观点。

So I'm sort of an extreme pluralist in that I, at some level, don't think there's any such thing as a new idea.

我认为所有观点都是建立在过去的基础之上的，几乎每一个想法都有漫长的思想史和演变过程。

I think all ideas build on the past, and there's a long history and evolution of thought for almost any idea.

但据说是爱因斯坦说过，天才就是隐藏你的出处。

But I think Einstein was, it's at least attributed to him that, you know, genius is disguising your references.

我认为，如果他真的说过这句话——虽然这可能只是传说——这是一种巧妙的说法，意思是所有知识都建立在其他知识之上。

And I think that's a clever way of him, if he said it, I think it's apocryphal, of saying that every knowledge builds on some other knowledge.

你总是在汲取过去的思想，并将其重塑为未来的形态。

You're always taking ideas from the past and reshaping them into the future.

那关于定量方面的批评呢？

What about the quantitative critiques?

有趣的是，关于组装理论已经出现了许多断言。

So it's interesting that there have been many assertions made about assembly theory.

我们实际上正在撰写另一篇论文，以证明这些说法中的一些在我们看来根本就是不正确的。

And we're actually working on another paper to show that some of these assertions are are simply not true as far as we can tell.

撰写一篇回应公众讨论的论文，感觉如何？

How does it feel to be writing a paper in response to public debate?

我认为组装理论引发了如此多的讨论，这非常好。

I think it's great that assembly theory has generated so much debate.

事实上，我认为在科学的某些领域，讨论还不够充分，这确实限制了科学的发展。

In fact, I think in some parts of the sciences, don't have enough debate, and that really limits science.

我认为物理学的本质始终是：让我们认真对待一切，并尝试驳斥一切。

I would argue that the nature of physics was always to say, let's take everything seriously and let's try to disprove everything.

如果有人提出了一个全新的理论，那很好，让我们看看它能否经受住我们已知所有知识的检验。

If someone has a brand new theory, that's great, let's see if it holds up against all the things we know.

因此，我们对一个理论所能说的是：到目前为止，它还没有被证伪。

And so all we can say for a theory is so far it hasn't been disproven.

这就是物理学的过程。

That's what the process of physics is.

因此，我认为萨拉所谈论的很多内容，以及我自己的观点，都是把物理学看作一个过程，而不是把物理学看作知识。

And so I think a lot of what Sara was talking about and a lot of my perspective is seeing physics as process rather than physics as knowledge.

所以我很高兴关于组装理论的这场辩论。

So I'm happy about the debate with Assembly theory.

我认为，对于每一个新提出的理论，我们都应该认真地质疑它，这是好事。

I think it's good for us to rigorously question every new theory that is proposed.

接下来在《复杂性》节目中，我们将探讨为什么我们的生物圈如此多样？

Coming up on Complexity, we'll ask why is our biosphere so diverse?

在不同的气候变化情景、不同的土地利用情景、不同的灭绝情景下，生物圈会发生什么变化？

Under different climate change scenarios, under different human land use scenarios, under different extinction scenarios, what's going to happen to the biosphere?

敬请期待下一期《复杂性》。

That's next time on Complexity.

《复杂性》是圣塔菲研究所的官方播客。

Complexity is the official podcast of the Santa Fe Institute.

本集由凯瑟琳·蒙库尔制作，主题曲由米奇·米尼亚诺创作。

This episode was produced by Katherine Moncure, and a theme song is by Mitch Mignano.

更多音乐来自 Blue Dot Sessions，本集的其他音效鸣谢详见节目说明。

Additional music from Blue Dot Sessions and the rest of our sound credits are in the show notes for this episode.

我是阿巴。

I'm Abha.

我们下期再见。

We'll see you next time.