迈克尔·莱文：异种智能与生物生命的隐秘现实

The following is a conversation with Michael Levin, his second time on the podcast.

以下是与迈克尔·莱文的对话，这是他第二次参加播客。

00:00 He is one of the most fascinating and brilliant biologists and scientists I’ve ever had the pleasure of speaking with.

他是我有幸交谈过的最迷人、最杰出的生物学家和科学家之一。

He and his labs at Tufts University study and build biological systems that help us understand the nature of intelligence, agency, memory, consciousness, and life in all of its forms here on Earth and beyond.

他和他在塔夫茨大学的实验室研究和构建生物系统，帮助我们理解地球内外所有形式的智力、能动性、记忆、意识和生命的本质。

This is the Lex Fridman Podcast.

这是莱克斯·弗里德曼播客。

To support it, please check out our sponsors in the description, where you can also find links to contact me, ask questions, give feedback, and so on.

为了支持它，请在描述中查看我们的赞助商，您还可以在其中找到联系我、提出问题、提供反馈等的链接。

And now, dear friends, here’s Michael Levin.

现在，亲爱的朋友们，这是迈克尔·莱文。

00:45 You write that the central question at the heart of your work, from biological systems to computational ones, is how do embodied minds arise in the physical world, and what determines the capabilities and properties of those minds?

您写道，从生物系统到计算系统，您工作的核心问题是具身思维如何在物理世界中出现，以及是什么决定了这些思维的能力和属性？

Can you unpack that question for us and maybe begin to answer it?

您能为我们解开这个问题并开始回答吗？

Well, the fundamental tension is in both the first-person, the second-person, and third-person descriptions of mind.

嗯，基本的张力存在于第一人称、第二人称和第三人称的心灵描述中。

01:04 So in third-person, we want to understand how do we recognize them, and how do we know looking out into the world what degree of agency there is, and how best to relate to the different systems that we find.

因此，在第三人称中，我们想要了解如何识别它们，我们如何知道观察世界的代理程度如何，以及如何最好地与我们发现的不同系统建立联系。

And are our intuitions any good when we look at something and it looks really stupid and mechanical, versus it really looks like there’s something cognitive going on there?

当我们看到某样东西时，它看起来真的很愚蠢和机械，而它看起来确实有一些认知因素，那么我们的直觉有用吗？

How do we get good at recognizing them?

我们如何才能善于识别它们？

Then there’s the second-person, which is the control, and that’s both for engineering but also for regenerative medicine, when you want to tell the system to do something.

然后是第二人称，即控制，当你想告诉系统做某事时，这既适用于工程，也适用于再生医学。

What kind of tools are you going to use?

您将使用什么样的工具？

01:45 And this is a major part of my framework, is that all of these kinds of things are operational claims.

这是我的框架的一个主要部分，所有这些东西都是操作声明。

Are you going to use the tools of hardware rewiring, of control theory and cybernetics, of behavior science, of psychoanalysis and love and friendship?

你会使用硬件重新布线、控制论和控制论、行为科学、精神分析以及爱情和友谊等工具吗？

Like, what are the interaction protocols that you bring?

比如，你带来了什么交互协议？

And then in first-person, it’s this notion of having an inner perspective and being a system that has valence and cares about the outcome of things.

然后在第一人称中，这是一种具有内在视角的概念，并且是一个具有效价并关心事物结果的系统。

Makes decisions and has memories and tells a story about itself and the outside world.

做出决定，拥有记忆，讲述一个关于自己和外部世界的故事。

And how can all of that exist and still be consistent with the laws of physics and chemistry and various other things that we see around us?

所有这些如何存在并且仍然符合物理和化学定律以及我们周围看到的各种其他事物？

02:20 So that I find to be maybe the most interesting and the most important mystery for all of us, both on the science and also on the personal level.

所以我发现这对我们所有人来说可能是最有趣和最重要的谜团，无论是在科学层面还是在个人层面。

So that’s what I’m interested in.

这就是我感兴趣的。

So your work is focused on starting at the physics, going all the way to friendship and love and psychoanalysis.

所以你的工作重点是从物理学开始，一直到友谊、爱情和精神分析。

Yeah, although actually I would turn that upside down.

是的，尽管实际上我会把它颠倒过来。

02:37 I think that pyramid is backwards, and I think it’s behavior science at the bottom.

我认为金字塔是倒退的，我认为底层是行为科学。

I think it’s behavior science all the way.

我认为这始终是行为科学。

I think in certain ways, even math is the behavior of a certain kind of being that lives in a latent space, and physics is what we call systems that at least look to be amenable to a very simple, low-agency kind of model, and so on.

我认为在某些方面，甚至数学也是生活在潜在空间中的某种存在的行为，而物理学就是我们所说的系统，至少看起来适合一种非常简单的、低代理类型的模型，等等。

But that’s what I’m interested in, is understanding that and developing applications.

但这就是我感兴趣的，那就是理解并开发应用程序。

03:05 Because it’s very important to me that what we do is transition deep ideas and philosophy into actual practical applications that not only make it clear whether we’re making any progress or not, but also allow us to relieve suffering and make life better for all sentient beings, and enable us and others to reach their full potential.

因为对我来说非常重要的是，我们所做的就是将深刻的思想和哲学转化为实际的实际应用，这不仅能让我们清楚地知道我们是否取得了任何进步，而且让我们能够减轻痛苦，让所有众生的生活变得更好，让我们和其他人充分发挥他们的潜力。

So these are very practical things, I think.

所以我认为这些都是非常实际的事情。

Behavioral science, I suppose, is more subjective, and mathematics and physics is more objective?

我认为行为科学更主观，而数学和物理更客观？

03:28 Would that be the clear difference?

这就是明显的区别吗？

The idea basically is that where something is on that spectrum, and I’ve called it the spectrum of persuadability.

这个想法基本上是指某个东西在这个范围内，我将其称为说服力范围。

03:35 You could call it the spectrum of intelligence or agency or something like that.

你可以称之为情报范围或代理或类似的东西。

I like the notion of the spectrum of persuadability, because it’s an engineering approach.

我喜欢说服力范围的概念，因为它是一种工程方法。

It means that these are not things you can decide or have feelings about from a philosophical armchair.

这意味着这些不是你可以坐在哲学扶手椅上决定或有感觉的事情。

You have to make a hypothesis about which tools, which interaction protocols you’re going to bring to a given system, and then we all get to find out how that worked out for you, right?

您必须假设您要将哪些工具、哪些交互协议引入给定系统，然后我们都会知道这对您来说效果如何，对吗？

So you could be wrong in many ways, in both directions.

所以你可能在很多方面都错了，在两个方向上。

You can guess too high or too low, or wrong in various ways, and then we can all find out how that’s working out.

你可能会以各种方式猜测过高或过低，或者错误，然后我们都可以找出结果如何。

04:14 And so I do think that the behavior of certain objects is well-described by specific formal rules, and we call those things the subject of mathematics.

因此，我确实认为某些对象的行为可以通过特定的形式规则很好地描述，我们将这些事物称为数学主题。

And then there are some other things whose behavior really requires the kinds of tools that we use in behavioral cognitive neuroscience, and those are other kinds of minds that we think we study in biology or in psychology or other sciences.

还有一些其他事物的行为确实需要我们在行为认知神经科学中使用的工具，而这些是我们认为在生物学、心理学或其他科学中研究的其他类型的思维。

Why are you using the term persuadability?

您为什么使用“说服力”一词？

04:39 Who are you persuading, and of what?

你在说服谁，说服什么？

Well-

嗯-

In this context.

在此背景下。

Yeah, the beginning of my work is very much in regenerative medicine, in bioengineering, things like that.

是的，我的工作主要是在再生医学、生物工程等领域。

04:45 So for those kinds of systems, the question is always, how do you get the system to do what you want it to do?

因此，对于这些类型的系统，问题始终是，如何让系统执行您希望它执行的操作？

So there are cells, there are molecular networks, there are materials, there are organs and tissues and synthetic beings and biobots and whatever.

所以有细胞、有分子网络、有材料、有器官和组织、合成生物和生物机器人等等。

And so the idea is, if I want your cells to regrow a limb, for example, if you’re injured and I want your cells to regrow a limb, I have many options.

所以我的想法是，如果我想让你的细胞重新长出肢体，例如，如果你受伤了，我想让你的细胞重新长出肢体，我有很多选择。

Some of those options are, I’m going to micromanage all of the molecular events that have to happen, right?

其中一些选择是，我将对所有必须发生的分子事件进行微观管理，对吧？

And there’s an incredible number of those.

其中的数量多得令人难以置信。

Or maybe I just have to micromanage the cells and the stem cell kinds of signaling factors.

或者也许我只需要对细胞和干细胞类型的信号因子进行微观管理。

05:28 Or maybe actually I can give the cells a very high-level prompt that says, “You really should build a limb,” and convince them to do it, right?

或者实际上我可以给细胞一个非常高级的提示，说“你真的应该建造一个肢体”，并说服它们这样做，对吧？

And so which of those is possible?

那么其中哪一个是可能的呢？

I mean, clearly people have a lot of intuitions about that.

我的意思是，显然人们对此有很多直觉。

If you ask standard people in regenerative medicine and molecular biology, they’re going to say, “Well, that convincing thing is crazy.

如果你问再生医学和分子生物学领域的标准人士，他们会说：“嗯，这个令人信服的东西太疯狂了。

What we really should be doing is talking to the cells, or better yet, the molecular networks.” And in fact, all the excitement of the biological sciences today are at single molecule approaches and big data and genomics and all of that.

我们真正应该做的是与细胞对话，或者更好的是与分子网络对话。”事实上，当今生物科学的所有令人兴奋的地方都在于单分子方法、大数据和基因组学等等。

06:00 The assumption is that going down is where the action’s going to be, going down in scale.

我们的假设是，行动将会发生，规模会缩小。

And I think that’s wrong.

我认为这是错误的。

But the thing that we can say for sure is that you can’t guess that.

但我们可以肯定的是，你猜不到这一点。

You have to do experiments and you have to see, because you don’t know where any given system is on that spectrum of persuadability.

你必须做实验，你必须看看，因为你不知道任何给定的系统在说服力范围内处于什么位置。

And it turns out that every time we look and we take tools from behavioral science, so learning different kinds of training, different kinds of models that are used in active inference and surprise minimization and perceptual multi-stability and visual illusions and all these kinds of interesting things, you know, stress perception and active memory reconstruction, all these interesting things.

事实证明，每次我们观察时，我们都会使用行为科学的工具，因此学习不同类型的训练，不同类型的模型，用于主动推理和惊喜最小化，感知多稳定性和视觉错觉以及所有这些有趣的事情，你知道，压力感知和主动记忆重建，所有这些有趣的事情。

06:41 When we apply them outside the brain to other kinds of living systems, we find novel discoveries and novel capabilities, actually being able to get the material to do new things that nobody had ever found before.

当我们将它们应用到大脑之外的其他类型的生命系统时，我们会发现新的发现和新的能力，实际上能够获得材料来做以前从未发现过的新事情。

And precisely because I think that people didn’t look at it from those perspectives, they assumed that it was a low-level kind of thing.

正是因为我认为人们没有从这些角度来看待它，所以他们认为这是一种低层次的东西。

So when I say persuadability, I mean different types of approaches, right?

所以当我说说服力时，我指的是不同类型的方法，对吧？

And we all know if you want to persuade your wind-up clock to do something, you’re not going to argue with it or make it feel guilty or anything.

我们都知道，如果你想说服你的发条时钟做某事，你不会与它争论或让它感到内疚或其他什么。

You’re going to have to get in there with a wrench and you’re going to have to, you know, tune it up and do whatever.

你将不得不用扳手进入那里，你将不得不，你知道，调整它并做任何事情。

07:15 If you want to do that same thing to a cell or a thermostat or an animal or a human, you’re going to be using other sets of tools that we’ve given other names to.

如果你想对细胞、恒温器、动物或人类做同样的事情，你将使用我们赋予其他名称的其他工具集。

And so that’s…

所以那就是……

Now, of course, that spectrum, the important thing is that as you get to the right of that spectrum, whereas the agency of the system goes up, it is no longer just about persuading it to do things.

当然，现在，在这个范围内，重要的是，当你到达该范围的右侧时，虽然系统的代理权上升，但它不再只是说服它做事。

It’s a bidirectional relationship, what Richard Watson would call a mutual vulnerable knowing.

这是一种双向关系，理查德·沃森（Richard Watson）将其称为“相互脆弱的了解”。

So the idea is that on the right side of that spectrum, when systems reach the higher levels of agency, the idea is that you are willing to let that system persuade you of things as well.

因此，我们的想法是，在该范围的右侧，当系统达到更高级别的机构时，我们的想法是，您也愿意让该系统说服您。

You know, in molecular biology, you do things, hopefully the system does what you want it to do, but you haven’t changed.

你知道，在分子生物学中，你做事时，希望系统能做你想做的事，但你并没有改变。

07:53 You’re still exactly the way you came in.

你还是原来的样子。

But on the right side of that spectrum, if you’re having interactions with even cells, but certainly, you know, dogs, other animals, maybe other creatures soon, you’re not the same at the end of that interaction as you were going in.

但在这个范围的右侧，如果你与甚至细胞发生相互作用，但当然，你知道，狗，其他动物，也许很快还有其他生物，那么在相互作用结束时，你与你进入的时候是不一样的。

It’s a mutual bidirectional relationship.

这是一种相互的双向关系。

So it’s not just you persuading something else, it’s not you pushing things.

所以，你不只是在说服别人，也不是在推动别人。

It’s a mutual bidirectional set of persuasions, whether those are purely intellectual or of other kinds.

这是一套相互的双向说服，无论是纯粹的智力上的还是其他类型的。

So in order to be effective at persuading an intelligent being, you yourself have to be persuadable.

因此，为了有效说服聪明人，你自己必须具有说服力。

08:20 So the closer in intelligence you are to the thing you’re trying to persuade, the more persuadable you have to become, hence the mutual vulnerable knowing.

因此，你在智力上越接近你试图说服的事情，你就必须变得越容易被说服，因此相互脆弱的了解。

What a term.

多么好的一个术语啊。

Yeah.

是的。

08:37 Richard, you should talk to Richard as well.

理查德，你也应该和理查德谈谈。

He’s an amazing guy and he’s got some very interesting ideas about the intersection of cognition and evolution.

他是一个了不起的人，他对认知和进化的交叉点有一些非常有趣的想法。

But I think what you bring up is very important because there has to be a kind of impedance match between what you’re looking for and the tools that you’re using.

但我认为你提出的内容非常重要，因为你正在寻找的东西和你正在使用的工具之间必须存在某种阻抗匹配。

I think the reason physics always sees mechanism and not minds is that physics uses low-agency tools.

我认为物理学总是看到机制而不是思想的原因是物理学使用低代理工具。

You’ve got voltmeters and rulers and things like this.

你有电压表和尺子之类的东西。

And if you use those tools as your interface, all you’re ever going to see is mechanisms and those kinds of things.

如果您使用这些工具作为界面，您将看到的只是机制和类似的东西。

If you want to see minds, you have to use a mind, right?

如果你想看到心灵，你就必须使用心灵，对吧？

You have to have, there has to be some degree of resonance between your interface and the thing you’re hoping to find.

你必须拥有，你的界面和你希望找到的东西之间必须有某种程度的共鸣。

You said this about physics before.

你之前说过关于物理学的事。

09:18 Can you just linger on that and expand on it, what you mean, why physics is not enough to understand life, to understand mind, to understand intelligence?

你能否停留在这个问题上并扩展它，你的意思是，为什么物理学不足以理解生命，理解心灵，理解智力？

You make a lot of controversial statements with your work.

您在作品中发表了很多有争议的言论。

That’s one of them because there’s a lot of physicists that believe they can understand life, the emergence of life, the origin of life, the origin of intelligence using the tools of physics.

这是其中之一，因为有很多物理学家相信他们可以使用物理工具来理解生命、生命的出现、生命的起源、智慧的起源。

Yeah.

是的。

In fact, all the other tools are a distraction to those folks.

事实上，所有其他工具都会分散这些人的注意力。

09:41 If you want to understand fundamentally anything, you have to start at physics to them.

如果你想从根本上理解任何东西，你必须从物理学开始。

And you’re saying, “No, physics is not enough.”

你会说：“不，物理学还不够。”

Here’s the issue.

这就是问题所在。

09:52 Everything here hangs on what it means to understand.

这里的一切都取决于理解的含义。

For me, understand doesn’t just mean have some sort of pleasing model that seems to capture some important aspect of what’s going on.

对我来说，理解不仅仅意味着拥有某种令人愉悦的模型，似乎能够捕捉到正在发生的事情的一些重要方面。

It also means that you have to be generative and creative in terms of capabilities.

这也意味着你必须在能力方面具有创造力和创造力。

And so for me, that means if I tell you this is what I think about cognition in cells and tissues, it means, for example, that I think we’re going to be able to take those ideas and use them to produce new regenerative medicine that actually helps people in various ways, right?

所以对我来说，这意味着如果我告诉你这就是我对细胞和组织认知的看法，这意味着，例如，我认为我们将能够采用这些想法并利用它们来生产新的再生医学，实际上以各种方式帮助人们，对吗？

It’s just an example.

这只是一个例子。

10:26 So if you think as a physicist you’re going to have a complete understanding of what’s going on from that perspective of fields and particles and, you know, who knows what else is at the bottom there.

因此，如果你作为一名物理学家思考，你将从场和粒子的角度全面了解正在发生的事情，而且，你知道，谁知道底部还有什么。

Does that mean then that when somebody is missing a finger or has a psychological problem or has these other high-level issues, that you have something for them, that you’re going to be able to do something?

这是否意味着当某人失去一根手指或有心理问题或有其他高级问题时，你可以为他们提供一些东西，你将能够做一些事情？

Because my claim is that you’re not going to, and even if you have some theory of physics that is completely compatible with everything that’s going on, that is…

因为我的主张是你不会这样做，即使你有一些与正在发生的一切完全兼容的物理理论，那就是……

it’s not enough.

这还不够。

That’s not specific enough to enable you to solve the problems you need to solve.

这还不够具体，无法让您解决需要解决的问题。

11:04 In the end, when you need to solve those problems, the person you’re going to go to is not a physicist.

最后，当你需要解决这些问题时，你去找的人不是物理学家。

It’s going to be either a biologist or a psychiatrist, or who knows, but it’s not going to be a physicist.

要么是生物学家，要么是精神病学家，谁知道呢，但不会是物理学家。

And the simple example is this: let’s say someone comes in here and tells you a beautiful mathematical proof, okay?

简单的例子是这样的：假设有人来到这里并告诉你一个漂亮的数学证明，好吗？

It’s just really, you know, deep and beautiful.

你知道，它真的很深刻、很美丽。

And there’s a physicist nearby, and he says, “Well, I know exactly what happened.

附近有一位物理学家，他说：“好吧，我确切地知道发生了什么。

There were some air particles that moved from that guy’s mouth to your ear.

有一些空气颗粒从那家伙的嘴里转移到了你的耳朵里。

I see what goes on.

我明白发生了什么。

11:32 It moved the cilia in your ear and the electrical signals went up to your brain.” I mean, we have a complete accounting of what happened, done and done.

它移动了你耳朵里的纤毛，电信号就会传到你的大脑。”我的意思是，我们对发生的事情、做过的事情和做过的事情有完整的记录。

But if you want to understand what’s the more important aspect of that interaction, it’s not going to be found in the physics department.

但如果你想了解这种相互作用更重要的方面是什么，在物理系是找不到的。

It’s going to be found in the math department.

它将在数学系找到。

So that’s my only claim is that physics is an amazing lens with which to view the world, but you’re capturing certain things, and if you want to stretch to sort of encompass these other things, we just don’t call that physics anymore, right?

所以我唯一的主张是，物理学是观察世界的神奇镜头，但你正在捕捉某些事物，如果你想延伸到包含这些其他事物，我们就不再称之为物理学了，对吧？

We call that something else.

我们称之为别的东西。

Okay.

好的。

12:03 But you’re kind of speaking about super complex organisms.

但你谈论的是超级复杂的生物体。

Can we go to the simplest possible thing where you first take a step over the line, the Cartesian cut as you’ve called it, from the non-mind to mind, from the non-living to living?

我们可以做最简单的事情吗？你首先跨过这条线，即你所说的笛卡尔切割，从非心灵到心灵，从无生命到生命？

The simplest possible thing, isn’t that in the realm of physics to understand?

最简单的事情，难道不是在物理学领域就能理解的吗？

How do we understand that first step where you’re like, that thing is no mind, probably non-living, and here’s a living thing that has a mind.

我们如何理解第一步，你会说那个东西没有思想，可能是无生命的，而这是一个有思想的生物。

That line.

那条线。

I think that’s a really interesting line.

我认为这是一条非常有趣的路线。

Maybe you can speak to the line as well, and can physics help us understand it?

也许你也可以对着这条线说话，物理学可以帮助我们理解它吗？

Yeah, let’s talk about it.

是的，我们来谈谈吧。

12:43 Well, first of all, of course it can.

嗯，首先，当然可以。

I mean, it can help, meaning that I’m not saying physics is not helpful.

我的意思是，它可以提供帮助，这意味着我并不是说物理没有帮助。

Of course it’s helpful.

当然有帮助。

It’s a very important lens on one slice of what’s going on in any of these systems.

这是观察这些系统中正在发生的事情的一个非常重要的镜头。

But I think the most important thing I can say about that question is I don’t believe in any such line.

但我认为关于这个问题我能说的最重要的是我不相信任何这样的说法。

I don’t believe any of that exists.

我不相信这些东西存在。

I think there is a continuum.

我认为存在一个连续体。

I think we as humans like to demarcate areas on that continuum and give them names because it makes life easier, and then we have a lot of battles over, you know, so-called category errors when people transgress those categories.

我认为，作为人类，我们喜欢在连续体上划分区域并给它们命名，因为这让生活更轻松，然后当人们超越这些类别时，我们会因为所谓的类别错误而发生很多争斗。

13:18 I think most of those categories at this point, they may have done some good service at the beginning of when the scientific method was getting started and so on.

我认为大多数类别在这一点上，他们可能在科学方法开始之初做了一些很好的服务等等。

I think at this point they mostly hold back science.

我认为目前他们主要阻碍科学。

Many, many categories that we can talk about are at this point very harmful to progress, because what those categories do is they prevent you from hoarding tools.

我们可以谈论的很多很多类别在这一点上对进步非常有害，因为这些类别的作用是阻止你囤积工具。

If you think that living things are fundamentally different from non-living things, or if you think that cognitive things are these like advanced brainy things that are very different from other kinds of systems, what you’re not going to do is take the tools that are appropriate to these kind of cognitive systems, right?

如果你认为生物与非生物有根本的不同，或者如果你认为认知事物就像高级的大脑事物，与其他类型的系统非常不同，那么你不会做的就是采用适合这些认知系统的工具，对吗？

13:55 So the tools that have been developed in behavioral science and so on, you’re never going to try them in other contexts because you’ve already decided that there’s a categorical difference, that it would be a categorical error to apply them.

因此，在行为科学等领域开发的工具，你永远不会在其他环境中尝试它们，因为你已经确定存在绝对差异，应用它们将是一个绝对错误。

And people say this to me all the time, that you’re making a category error, as if these categories were given to us, you know, from on high, and we have to obey them forevermore.

人们总是对我说，你犯了一个类别错误，就好像这些类别是从高处赋予我们的，我们必须永远服从它们。

The categories should change with the science.

类别应该随着科学的发展而改变。

So yeah, I don’t believe in any such line, and I think a physics story is very often a useful part of the story, but for most interesting things, it’s not the entire story.

所以，是的，我不相信任何这样的说法，我认为物理故事通常是故事的有用部分，但对于大多数有趣的事情来说，它并不是整个故事。

Okay.

好的。

14:30 So if there’s no line, is it still useful to talk about things like the origin of life?

那么如果没有台词的话，谈论生命起源之类的事情还有用吗？

That’s one of the big open mysteries before us as a human civilization, as scientifically minded curious homo sapiens.

作为人类文明，作为具有科学头脑的好奇智人，这是摆在我们面前的重大未解之谜之一。

How did this whole thing start?

这整件事是如何开始的？

Are you saying there is no start?

你说没有开始？

Is there a point where you could say that invention right there was the start of it all on Earth?

你是否可以说，那里的发明是地球上一切的开始？

My suggestion is that it’s much better than trying to define any kind of a line, okay?

我的建议是，这比尝试定义任何类型的线要好得多，好吗？

15:01 Because inevitably I’ve never found, and people try to…

因为不可避免地我从未找到过，而人们试图……

You know, we play this game all the time when I make my continuum claim.

你知道，当我提出连续统一体主张时，我们一直在玩这个游戏。

Then people try to come up, “Okay, well, what about this, you know, what about this?” And I haven’t found one yet that really shoots that down, that you can’t zoom in and say, “Yeah, okay, but right before then this happened, and if we really look close, like here’s a bunch of steps in between,” right?

然后人们试图上来，“好吧，好吧，这个怎么样，你知道，这个怎么样？”我还没有找到一个真正能解决这个问题的方法，你不能放大并说，“是的，好吧，但就在那之前，这件事发生了，如果我们真的仔细观察，就像中间有一堆步骤，”对吗？

Pretty much everything ends up being a continuum, but here’s what I think is much more interesting than trying to make that line.

几乎所有事情最终都会成为一个连续体，但我认为这比尝试建立这条线更有趣。

15:34 I think what’s really more useful is trying to understand the transformation process.

我认为真正更有用的是尝试理解转变过程。

What is it that happened to scale up?

扩大规模到底发生了什么？

And I’ll give you a really dumb example.

我会给你一个非常愚蠢的例子。

And we always get into this because people often really don’t like this continuum view: the word adult, right?

我们总是陷入这个问题，因为人们通常真的不喜欢这种连续的观点：“成人”这个词，对吗？

15:51 Everybody is going to say, “Look, I know what a baby is.

每个人都会说：“看，我知道婴儿是什么。

I know what an adult is.

我知道什么是成年人。

You’re crazy to say that there’s no difference.” I’m not saying there’s no difference.

你说没有区别真是疯了。”我并不是说没有区别。

What I’m saying is the word adult is really helpful in court because you just need to move things along, and so we’ve decided that if you’re 18, you’re an adult.

我想说的是，“成人”这个词在法庭上确实很有帮助，因为你只需要推动事情向前发展，所以我们决定，如果你年满 18 岁，你就是成年人。

However, what it hides is…

然而，它隐藏的是……

what it completely conceals is the fact that first of all nothing happens on your 18th birthday, right?

它完全掩盖了这样一个事实：首先，你18岁生日那天什么也没发生，对吗？

That’s special.

这很特别。

Second, if you actually look at the data, the car rental companies actually have a much better estimate because they actually look at the accident statistics and they’ll say it’s about 25 is really what you’re looking for, right?

其次，如果你真正查看数据，汽车租赁公司实际上有一个更好的估计，因为他们实际上查看了事故统计数据，他们会说大约 25 起正是你想要的，对吗？

16:27 So theirs is a little better.

所以他们的稍微好一些。

It’s less arbitrary.

它不那么随意。

But in either case what it’s hiding is the fact that we do not have a good story of what happened from the time that you were an egg to the time that you’re the supposed adult and what is the scaling of personal responsibility, decision-making, judgment.

但无论哪种情况，它都隐藏着这样一个事实：我们没有一个好的故事来讲述从你是一个鸡蛋到你被认为是成年人的那段时间发生了什么，以及个人责任、决策和判断的尺度如何。

These are deep fundamental questions.

这些都是深刻的基本问题。

Nobody wants to get into that every time somebody, you know, has a traffic ticket.

没有人愿意在每次有人收到交通罚单时卷入其中。

So we’ve just decided that there’s this adult idea.

所以我们刚刚决定有这个成人的想法。

And of course it does come up in court because then somebody has a brain tumor or somebody’s eaten too many Twinkies or something has happened.

当然，它确实会出现在法庭上，因为有人患有脑肿瘤，或者有人吃了太多夹心饼干，或者发生了一些事情。

You say, “Look, that wasn’t me.

你说：“看，那不是我。

17:01 Whoever did that, I was on drugs.” “Well, why’d you take the drugs?” “Well, that was, you know, that was yesterday.

不管是谁干的，我就是吸毒了。” “那你为什么要吃药呢？” “嗯，那是，你知道，那是昨天的事。

Me today, this is I’m…” Right?

今天的我，这是我……”对吧？

So we get into these very deep questions that are completely glossed over by this idea of an adult.

因此，我们进入了这些非常深刻的问题，而这些问题完全被成年人的想法所掩盖。

So I think once you start scratching the surface, most of these categories are like that.

所以我认为一旦你开始了解表面，大多数类别都是这样的。

They’re convenient and they’re good.

它们很方便而且很好。

You know, I get into this with neurons all the time.

你知道，我一直都在研究神经元。

I’ll ask people, “What’s a neuron?

我会问人们：“什么是神经元？

Like, what’s really a neuron?” And yes, if you’re in neurobiology 101, of course you just say like, “These are what neurons look like.

比如，什么是真正的神经元？”是的，如果你学习神经生物学 101，你当然会说，“这些就是神经元的样子。

17:30 Let’s just study the neuroanatomy and we’re done.” But if you really want to understand what’s going on, well, neurons develop from other types of cells and that was a slow and gradual process, and most of the cells in your body do the things that neurons do.

我们只要研究一下神经解剖学就可以了。”但如果你真的想了解发生了什么，那么神经元是从其他类型的细胞发育而来的，这是一个缓慢而渐进的过程，你体内的大多数细胞都会做神经元所做的事情。

So what really is a neuron, right?

那么神经元到底是什么，对吗？

So once you start scratching this, this happens, and I have some things that I think are coming out of our lab and others that are I think very interesting about the origin of life.

所以一旦你开始研究这个问题，就会发生这种情况，我认为有些东西来自我们的实验室，还有一些我认为关于生命起源非常有趣的东西。

But I don’t think it’s about finding that one boon, like this is.

但我不认为这是为了找到一个恩惠，就像这样。

Yeah, there will be innovations, right?

是的，会有创新，对吗？

There are innovations that allow you to scale in an amazing way, for sure.

当然，有些创新可以让您以惊人的方式进行扩展。

And there are lots of people that study those, right?

有很多人研究这些，对吗？

18:06 So things like thermodynamic, kind of metabolic things and all kinds of architectures and so on.

比如热力学、新陈代谢的东西和各种建筑等等。

But I don’t think it’s about finding a line.

但我不认为这是寻找一条线的问题。

I think it’s about finding a scaling process.

我认为这是为了找到一个扩展过程。

the scaling process, but then there is more rapid scaling and there are slower scaling.

缩放过程，但是缩放速度更快，缩放速度更慢。

18:16 So innovation, invention, I think is useful to understand so you can predict how likely it is on other planets, for example.

因此，我认为理解创新、发明很有用，这样你就可以预测它在其他行星上的可能性有多大。

Or to be able to describe the likelihood of these kinds of phenomena happening in certain kinds of environments.

或者能够描述在某些环境中发生此类现象的可能性。

Again, specifically in answering how many alien civilizations there are.

再次，特别是在回答有多少外星文明时。

18:44 It’s useful.

这很有用。

But it is also useful on a scientific level to have categories, not just ’cause it makes us feel good and fuzzy inside, but because it makes conversation possible and productive, I think.

但在科学层面上进行分类也很有用，我认为，这不仅因为它让我们内心感觉良好和模糊，而且因为它使对话成为可能且富有成效。

If everything is a spectrum, it becomes difficult to make concrete statements, I think.

我认为，如果一切都是一个谱系，就很难做出具体的陈述。

Like, we even use the terms of biology and physics.

就像，我们甚至使用生物学和物理学的术语。

Those are categories.

这些都是类别。

Technically, it’s all the same thing, really.

从技术上来说，其实都是一样的。

Fundamentally, it’s all the same.

从根本上来说，都是一样的。

There’s no difference between biology and physics.

生物学和物理学之间没有区别。

But it’s a useful category.

但这是一个有用的类别。

If you go to the physics department and the biology department, those people are different in some categorical way.

如果你去物理系和生物系，那些人在某些方面是不同的。

So somehow, I don’t know what the chicken or the egg is, but the categories…

所以不知何故，我不知道先有鸡还是先有蛋，但类别......

19:28 Maybe the categories create themselves because of the way we think about them and use them in language, but it does seem useful.

也许这些类别是由于我们思考它们和在语言中使用它们的方式而产生的，但它似乎确实有用。

Let me make the opposite argument.

让我提出相反的论点。

19:35 They’re absolutely useful.

它们绝对有用。

They’re useful specifically when you want to gloss over certain things.

当你想掩盖某些事情时，它们特别有用。

The categories are exactly useful when there’s a whole bunch of stuff.

当有一大堆东西时，类别非常有用。

And this is what’s important about science, is like the art of being able to say something without first having to say everything, right?

这就是科学的重要之处，就像能够说出一些话而不必先说出一切的艺术，对吗？

19:50 which would make it impossible.

这将使它变得不可能。

So, categories are great when you want to say, “Look, I know there’s a bunch of stuff hidden here.

因此，当您想说“看，我知道这里隐藏着很多东西。

I’m going to ignore all that, and we’re just going to, like, let’s get on with this particular thing.” And all of that is great as long as you don’t lose track of the stuff that you glossed over.

我会忽略这一切，我们只是继续做这件事。”只要你不忘记你掩盖的东西，所有这些都很棒。

And that was what I’m afraid is happening in a lot of different ways.

我担心这种情况正在以多种不同的方式发生。

And in terms of, look, I’m very interested in life beyond Earth and all of these kinds of things so that we should also talk about what I call SUTI, S-U-T-I, the search for unconventional terrestrial intelligences.

就我而言，我对地球以外的生命以及所有这些类型的事物非常感兴趣，因此我们还应该谈论我所说的 SUTI、S-U-T-I，即寻找非常规的地球智慧生命。

I think we got much bigger issues than actually recognizing aliens off Earth, but I’ll make this claim.

我认为我们遇到的问题比实际识别地球外的外星人要大得多，但我会这么说。

20:27 I think the categorical stuff is actually hurting that search.

我认为分类的东西实际上损害了搜索。

Because if we try to define categories with the kinds of criteria that we’ve gotten used to, we are going to be very poorly set up to recognize life in novel embodiments.

因为如果我们试图用我们已经习惯的标准来定义类别，我们将很难认识新奇的生活。

I think we have a kind of mind blindness.

我认为我们有一种心灵盲目性。

I think this is really key.

我认为这真的很关键。

To me, the cognitive spectrum is much more interesting than the spectrum of life.

对我来说，认知谱比生活谱更有趣。

I think really what we’re talking about is the spectrum of cognition.

我认为我们真正讨论的是认知范围。

And it is…

它是……

Well, I know it’s weird as a biologist to say, I don’t think life is all that interesting a category.

好吧，我知道作为一名生物学家说“我不认为生命是一个那么有趣的类别”很奇怪。

I think the categories of different types of minds, I think, is extremely interesting.

我认为不同类型思维的分类非常有趣。

21:06 And to the extent that we think our categories are complete and are cutting nature at its joints, we are going to be very poorly placed to recognize novel systems.

如果我们认为我们的范畴是完整的，并且正在割裂自然的关节，那么我们将很难识别新的系统。

So for example, a lot of people will say, “Well, this is intelligent and this isn’t,” right?

例如，很多人会说，“嗯，这是智能的，而这不是，”对吧？

And there’s a binary thing, and that’s useful occasionally for some things.

还有一个二元的东西，它偶尔对某些事情很有用。

I would like to say, instead of that, let’s admit that we have a spectrum, but instead of just saying, “Oh, look, everything’s intelligent,” right?

我想说的是，我们应该承认我们有一个范围，但不要只是说，“哦，看，一切都是智能的”，对吗？

Because if you do that, you’re right, you can’t do anything after that.

因为如果你这样做了，你就是对的，之后你就不能做任何事情了。

What I’d like to say instead is, no, no, you have to be very specific as to what kind and how much.

我想说的是，不，不，你必须非常具体地说明什么类型和多少。

In other words, what problem spaces they’re operating in?

换句话说，他们在哪些问题空间中运作？

21:43 What kind of mind does it have?

它有什么样的心态？

What kind of cognitive capacities does it have?

它具有什么样的认知能力？

You have to actually be much more specific.

实际上你必须更加具体。

And we can even name, right?

我们甚至可以说出名字，对吧？

That’s fine.

没关系。

We can name different types of…

我们可以命名不同类型的...

I mean, this is doing predictive processing.

我的意思是，这是在进行预测处理。

This can’t do that, but it can form memories.

这不能做到这一点，但它可以形成记忆。

What kind?

什么样的？

Well, habituation and sensitization, but not associative conditioning.

嗯，是习惯化和敏化，但不是联想调节。

It’s fine to have categories for specific capabilities, but it actually makes for much more rigorous discussions because it makes you say, what is it that you are claiming this thing does?

对特定功能进行分类很好，但它实际上会带来更严格的讨论，因为它让你说，你声称这个东西的作用是什么？

And it works in both directions.

它是双向的。

So, some people will say, “Well, that’s a cell.

所以，有些人会说：“嗯，那是一个细胞。

That can’t be intelligent.” And I’ll say, “Well, let’s be very specific.

这不可能是明智的。”我会说：“好吧，让我们说得很具体。

22:19 Here are some claims about…

以下是一些关于……的主张

here’s some problem solving that it’s doing.

这是它正在解决的一些问题。

Tell me why that doesn’t…

告诉我为什么不……

you know, why doesn’t that match?

你知道，为什么不匹配？

Or in the opposite direction, somebody comes to me and says, “You’re right, you’re right.

或者相反，有人来找我说：“你是对的，你是对的。

You know, the whole, the whole solar system, man.

你知道，整个太阳系，伙计。

It’s just like this amazing…” I’m like, “Whoa, okay.

这真是太神奇了……”我想，“哇，好吧。

Well, what is it doing?” Like, “Tell me what tools of cognitive and behavioral science are you using to reach that conclusion,” right?

嗯，它在做什么？”就像，“告诉我你使用什么认知和行为科学工具来得出这个结论，”对吗？

And so I think it’s actually much more productive to take this operational stance and say, “Tell me what protocols you think you can deploy with this thing that would lead you to use these terms.”

因此，我认为采取这种操作立场并说“告诉我你认为你可以用这个东西部署哪些协议来引导你使用这些术语”实际上会更有成效。

To have a bit of a meta conversation about the conversation, I should say that part of the persuadability argument that we two intelligent creatures are doing is me playing devil’s advocate every once in a while.

为了对这次对话进行一些元对话，我应该说，我们两个聪明的生物正在做的说服力论证的一部分是我时不时地扮演魔鬼代言人。

22:49 And you did the same, which is kind of interesting, taking the opposite view and see what comes out.

你也做了同样的事情，这很有趣，采取相反的观点，看看会发生什么。

Because you don’t know the result of the argument until you have the argument, and it seems productive to just take the other side of the argument.

因为在你提出论点之前你不知道论点的结果，而且只采取论点的另一方似乎是富有成效的。

For sure.

一定。

23:14 It’s a very important thinking aid to, first of all, you know, what they call steel manning, right?

首先，这是一个非常重要的思维辅助工具，你知道，他们所说的“钢铁配员”，对吗？

To try to make the strongest possible case for the other side and to ask yourself, “Okay, what are all the places that I am sort of glossing over because I don’t know exactly what to say?

尝试为对方提出最有力的论据，并问自己：“好吧，我因为不知道到底该说什么而掩盖了哪些地方？

And where are all the holes in the argument, and what would a, you know, a really good critique really look like?” Yeah.

论证中的所有漏洞在哪里？你知道，真正好的批评到底是什么样子的？”是的。

Sorry to go back there just to linger on the term, because it’s so interesting, persuadability.

很抱歉回到那里只是为了停留在这个词上，因为它非常有趣，具有说服力。

23:38 Did I understand correctly that you mean that it’s kind of synonymous with intelligence?

我是否理解正确，你的意思是它是智力的同义词？

So it’s an engineering-centric view of an intelligence system.

所以这是一个以工程为中心的智能系统视图。

Because if it’s persuadable, you’re more focused on, how can I steer the goals of the system, the behaviors of the system?

因为如果它是可以说服的，你就会更加关注，我如何引导系统的目标、系统的行为？

Meaning an intelligence system maybe is a goal-oriented, goal-driven system with agency.

这意味着智能系统可能是一个以目标为导向、目标驱动的具有代理性的系统。

And when you call it persuadable, you’re thinking more like, “Okay, here’s an intelligence system that I’m interacting with that I would like to get to accomplish certain things.” But fundamentally, are they synonymous or correlated, persuadability and intelligence?

当你称其为可说服时，你的想法更像是，“好吧，这是一个我正在与之交互的智能系统，我希望能够完成某些事情。”但从根本上来说，说服力和智力是同义词还是相关的？

They’re definitely correlated.

它们肯定是相关的。

24:28 So let me…

那么让我...

I want to preface this with one thing.

我想用一件事作为序言。

When I say it’s an engineering perspective, I don’t mean that the standard tools that we use in engineering and this idea of enforced control and steering is how we should view all of the world.

当我说这是工程视角时，我并不是说我们在工程中使用的标准工具以及强制控制和指导的想法是我们应该如何看待世界。

I’m not saying that at all, and I want to be very clear on that because people do email me and say, “Bah, this engineering thing.

我根本不是这么说的，我想对此说得非常清楚，因为人们确实给我发电子邮件说：“呸，这个工程问题。

You’re going to drain the, you know, the life and the majesty out of these high-end, like, human conversation.” My whole point is not that at all.

你知道，你会耗尽这些高端的人类对话中的生命力和威严。”我的重点根本不是这个。

It’s that of course, at the right side of the spectrum, it doesn’t look like engineering anymore, right?

当然，在光谱的右侧，它看起来不再像工程学了，对吧？

25:04 It looks like, it looks like friendship and love and psychoanalysis and all these other tools that we have.

看起来像是友谊、爱情、精神分析以及我们拥有的所有其他工具。

But here’s what I want to do.

但这就是我想做的。

I want to be very specific to my colleagues in regenerative medicine and everything.

我想对我在再生医学和其他领域的同事们进行非常具体的介绍。

Just imagine if I, you know, if I went to a bioengineering department or a genetics department and I started talking about high-level, you know, cognition and psychoanalysis, right?

想象一下，如果我，你知道，如果我去了生物工程系或遗传学系，我开始谈论高层次的认知和精神分析，对吗？

They don’t want to hear that.

他们不想听这个。

So I focus on the engineering approach…

所以我专注于工程方法......

25:28 …because I want to say, look, this is not a philosophical problem.

……因为我想说，看，这不是一个哲学问题。

This is not a linguistics problem.

这不是语言学问题。

We are not trying to define terms in different ways to make anybody feel fuzzy.

我们并不是试图以不同的方式定义术语以使任何人感到模糊。

What I’m telling you is, if you want to reach certain capabilities, if you want to reprogram cancer, if you want to regrow new organs, you want to defeat aging, you want to do these specific things, you are leaving too much on the table by making an unwarranted assumption that the low-level tools that we have, so these are the rules of chemistry and the kind of remolecular rewiring, that those are going to be sufficient to get to where you want to go.

我要告诉你的是，如果你想达到某些能力，如果你想重新编程癌症，如果你想重新长出新的器官，你想战胜衰老，你想做这些特定的事情，那么你就会做出一个无根据的假设，即我们拥有的低级工具，所以这些是化学规则和分子重新布线的类型，这些规则足以到达你想要去的地方，所以你就留下了太多的东西。

25:59 It’s an assumption only, and it’s an unwarranted assumption.

这只是一个假设，而且是一个没有根据的假设。

And actually, we’ve done experiments now, so not philosophy, but real experiments, that if you take these other tools, you can in fact persuade the system in ways that has never been done before.

事实上，我们现在已经做了实验，所以不是哲学实验，而是真正的实验，如果你使用这些其他工具，你实际上可以以以前从未做过的方式说服系统。

And we can unpack all that.

我们可以解开所有这些。

But it is absolutely correlated with intelligence, so let me flesh that out a little bit.

但它与智力绝对相关，所以让我稍微具体说明一下。

What I think is scaling in all of these things, right, because I keep talking about the scaling.

我认为是在所有这些事情上进行扩展，对吧，因为我一直在谈论扩展。

So what is it that’s scaling?

那么什么是缩放呢？

What I think is scaling is something I call the cognitive light cone, and the cognitive light cone is the size of the biggest goal state that you can pursue.

我认为缩放就是我所说的认知光锥，认知光锥就是你可以追求的最大目标状态的大小。

This doesn’t mean how far do your senses reach.

这并不意味着你的感官能到达多远。

26:39 This doesn’t mean how far can you affect it.

这并不意味着你能影响它多远。

So the James Webb Telescope has enormous sensory reach, but that doesn’t mean that’s the size of its cognitive light cone.

因此，詹姆斯·韦伯望远镜具有巨大的感官范围，但这并不意味着它的认知光锥的大小。

The size of the cognitive light cone is the scale of the biggest goal you can actively pursue, but I do think it’s a useful concept to enable us to think about very different types of agents of different composition, different provenance, you know, engineered, evolved, hybrid, whatever, all in the same framework.

认知光锥的大小是你可以积极追求的最大目标的规模，但我确实认为这是一个有用的概念，使我们能够在同一个框架中思考不同组成、不同来源的不同类型的代理，你知道，工程的、进化的、混合的，等等。

And by the way, the reason I use light cone is that it has this idea from physics that you’re putting space and time kind of in the same diagram, which I like here.

顺便说一句，我使用光锥的原因是它具有物理学的想法，即你将空间和时间放在同一个图表中，我喜欢这里。

27:11 So if you tell me that all your goals revolve around maximizing the amount of sugar in this, in this, you know, 10, 20 micron radius of space-time, and that you have, you know, 20 minutes memory going back and maybe five minutes predictive capacity going forward, that tiny little cognitive light cone, I’m going to say, probably a bacterium.

所以，如果你告诉我，你所有的目标都围绕着最大限度地提高这个半径为 10、20 微米的时空中的糖含量，并且你知道，你有 20 分钟的回溯能力，也许还有 5 分钟的未来预测能力，那个微小的认知光锥，我想说，可能是一种细菌。

And if you say to me that, “Well, I’m able to care about several hundred yards sort of scale, I could never care about what happens three weeks from now, two towns over, just impossible,” I would say you might be a dog.

如果你对我说，“好吧，我能够关心几百码的规模，我永远不会关心三周后发生的事情，两个城镇之外，简直不可能，”我会说你可能是一只狗。

And if you say to me, “Okay, I care about really what happens, you know, the financial markets on Earth, you know, long after I’m dead, and this and that,” I’d say you’re probably a human.

如果你对我说，“好吧，我真的关心发生的事情，你知道，地球上的金融市场，你知道，在我死后很久，以及这个和那个，”我会说你可能是一个人。

27:56 And if you say to me, “I care in the linear range, I actively, I’m not just saying it, I can actively care in the linear range about all the living beings on this planet,” I’m going to say, “Well, you’re not a standard human.

如果你对我说，“我在线性范围内积极地关心，我不只是说说而已，我可以在线性范围内积极地关心这个星球上的所有生物，”我会说，“好吧，你不是一个标准的人。

You must be something else,” because humans, I don’t know, standard humans today, I don’t think can do that.

你一定是别的东西，”因为人类，我不知道，今天的标准人类，我认为不能做到这一点。

You must be some kind of a bodhisattva or some other thing that has these massive cognitive light cones.

你一定是某种菩萨或其他拥有这些巨大认知光锥的东西。

So I think what’s scaling from zero, and I do think it goes all the way down.

所以我认为什么是从零开始的，而且我确实认为它会一路下降。

I think we can talk about even particles doing something like this.

我想我们甚至可以讨论粒子做这样的事情。

I think what scales is the size of the cognitive light cone.

我认为尺度就是认知光锥的大小。

And so now this is an interesting…

所以现在这是一个有趣的……

here, I’ll try for a definition of life or whatever, for whatever it’s worth.

在这里，我将尝试为生命或其他什么定义，无论它的价值如何。

28:33 I spent no time trying to make that stick, but if we wanted to…

我没有花时间尝试制作那根棍子，但如果我们想……

I think we call things alive to the extent that the cognitive light cone of that thing is bigger than that of its parts.

我认为我们称事物为“有生命”的，是指该事物的认知光锥大于其各个部分的认知光锥。

So in other words, rocks aren’t very exciting because the things it knows how to do are the things that its parts already know how to do, which is follow gradients and things like that.

换句话说，岩石并不是很令人兴奋，因为它知道如何做的事情是它的各个部分已经知道如何做的事情，即遵循梯度之类的事情。

But living things are amazing at aligning their competent parts so that the collective has a larger cognitive light cone than the parts.

但生物体非常善于调整其能胜任的部分，从而使集体拥有比各部分更大的认知光锥。

I’ll give you a very simple example that comes up in biology and that comes up in our cancer program all the time.

我会给你一个非常简单的例子，这个例子出现在生物学中，并且一直出现在我们的癌症项目中。

Individual cells have little tiny cognitive light cones.

单个细胞有微小的认知光锥。

What are their goals?

他们的目标是什么？

29:15 Well, they’re trying to manage pH, metabolic state, some other things.

嗯，他们正在尝试管理 pH 值、代谢状态和其他一些东西。

There are some goals in transcriptional space, some goals in metabolic space, some goals in physiological state space, but they’re generally very tiny goals.

转录空间有一些目标，代谢空间有一些目标，生理状态空间有一些目标，但它们通常都是非常小的目标。

One thing evolution did was to provide a kind of cognitive glue, which we can also talk about, that ties them together into a multicellular system, and those systems have grandiose goals.

进化所做的一件事是提供一种我们也可以谈论的认知粘合剂，将它们连接在一起形成一个多细胞系统，而这些系统有宏伟的目标。

They’re making limbs, and if you’re a salamander limb and you chop it off, they will regrow that limb with the right number of fingers.

他们正在制造四肢，如果你是蝾螈的四肢，你把它砍掉，他们就会用正确数量的手指重新长出该四肢。

Then they’ll stop when it’s done; the goal has been achieved.

然后他们会在完成后停下来；目标已经实现。

No individual cell knows what a finger is or how many fingers you’re supposed to have, but the collective absolutely does.

没有任何一个细胞知道一根手指是什么，或者你应该有多少根手指，但集体绝对知道。

29:54 And that process of growing that cognitive light cone from a single cell to something much bigger, and of course the failure mode of that process, so cancer, right?

认知光锥从单个细胞成长为更大的物体的过程，当然还有这个过程的失败模式，所以癌症，对吧？

When cells disconnect, they physiologically disconnect from the other cells.

当细胞断开连接时，它们会在生理上与其他细胞断开连接。

Their cognitive light cone shrinks.

他们的认知光锥缩小了。

The boundary between self and world, which is what the cognitive light cone defines, shrinks.

认知光锥所定义的自我与世界之间的界限正在缩小。

Now they’re back to an amoeba.

现在他们又回到了阿米巴原虫。

As far as they’re concerned, the rest of the body is just external environment, and they do what amoebas do.

对它们而言，身体的其他部分只是外部环境，它们的行为与阿米巴原虫的行为相同。

They go where life is good.

他们去生活美好的地方。

They reproduce as much as they can, right?

他们会尽可能多地繁殖，对吗？

So that cognitive light cone, that is the thing that I’m talking about that scales.

所以认知光锥，这就是我所说的可缩放的东西。

And so when we are looking for life, I don’t think we’re looking for specific materials.

因此，当我们寻找生命时，我认为我们并不是在寻找特定的材料。

30:30 I don’t think we’re looking for specific metabolic states.

我认为我们并不是在寻找特定的代谢状态。

I think we’re looking for scales of cognitive light cone.

我认为我们正在寻找认知光锥的尺度。

We’re looking for alignment of parts towards bigger goals in spaces that the parts could not comprehend.

我们正在寻找零件的对齐方式，以实现零件无法理解的空间中的更大目标。

And so cognitive light cone, just to make clear, is about goals that you can actively pursue now.

因此，认知光锥，只是为了明确一下，是关于你现在可以积极追求的目标。

30:42 You said linear, like we’re within reach immediately.

你说的是线性的，就像我们马上就可以到达一样。

No, I didn’t…

不，我没有……

30:54 sorry, I didn’t mean that.

抱歉，我不是那个意思。

First of all, the goal necessarily is often removed in time.

首先，目标必然经常被及时消除。

So, in other words, when you’re pursuing a goal, it means that you have a separation between current state and target state, at minimum.

所以，换句话说，当你追求一个目标时，这意味着你的当前状态和目标状态之间至少有一个分离。

Your thermostat, right?

你的恒温器，对吗？

Let’s just think about that.

让我们想一想。

There’s a separation in time because the thing you’re trying to make happen, so that the temperature goes to a certain level, is not true right now.

时间上有一个分离，因为你试图实现的事情，让温度达到一定水平，现在还不是真的。

And all your actions are going to be around reducing that error, right?

你所有的行动都是为了减少错误，对吧？

That basic homeostatic loop is all about closing that gap.

基本的稳态循环就是为了缩小这一差距。

When I said linear range, this is what I meant.

当我说线性范围时，这就是我的意思。

31:24 If I say to you, “This terrible thing happened to, you know, 10 people,” and, you know, you have some degree of activation about it.

如果我对你说，“这件可怕的事情发生在 10 个人身上”，你知道，你对此会有一定程度的激活。

And then I say, “No, no, no, actually it was 100, you know, 10,000 people.” You’re not a thousand times more activated about it.

然后我说，“不，不，不，实际上有 100 人，你知道，10,000 人。”你对此并没有更加活跃一千倍。

You’re somewhat more activated, but it’s not a thousand.

你有点活跃，但不是一千。

And if I say, “Oh my God, it was actually 10 million people,” you’re not a million times more activated.

如果我说，“天哪，实际上有 1000 万人”，你的活跃程度不会高出一百万倍。

You don’t have that capacity in the linear range.

在线性范围内你没有这样的能力。

You sort of, you sort of, right?

你有点，你有点，对吧？

If you think about that curve, we sort of reach a saturation point.

如果你考虑一下这条曲线，我们就达到了饱和点。

31:54 I have some amazing colleagues in the Buddhist community with whom we’ve written some papers about this.

我在佛教界有一些很棒的同事，我们和他们一起写了一些关于这个问题的论文。

The radius of compassion is like, can you grow your cognitive system to the point that, yeah, it really isn’t just your family group, it really isn’t just the hundred people you know in your, in your, you know, circle?

同情心的半径就像，你能否将你的认知系统发展到这样的程度：是的，它真的不仅仅是你的家庭群体，它真的不仅仅是你在你的圈子里认识的一百个人？

Can you grow your cognitive light cone to the point where, no, no, we care about the whole, whether it’s all of humanity or the whole ecosystem, or the whole, whatever?

你能否将你的认知光锥发展到，不，不，我们关心整体，无论是全人类还是整个生态系统，或者整体，等等？

Can you actually care about that the exact same way that we now care about a much smaller set of people?

你真的能像我们现在关心一小部分人一样关心这一点吗？

That’s what I mean by linear range.

这就是我所说的线性范围。

But this is separated by time like a thermostat, but a bacteria…

但这就像恒温器一样被时间分开，但细菌……

32:25 I mean, if you zoom out far enough, a bacteria could be formulated to have a goal state of creating human civilization, because if you look at the, you know, bacteria…

我的意思是，如果你把镜头拉得足够远，细菌可以被配制为具有创造人类文明的目标状态，因为如果你看看细菌……

…Has a role to play in the whole history of Earth.

......在地球的整个历史中发挥着作用。

So, you know, if you anthropomorphize the goals of a bacteria enough, I mean, it has a concrete role to play in the history of the evolution…

所以，你知道，如果你将细菌的目标充分拟人化，我的意思是，它在进化史上可以发挥具体的作用......

…Of human civilization.

……人类文明。

So, you do need to…

所以，你确实需要……

when you define a cognitive light cone, you’re looking at directly short-term behavior.

当你定义认知光锥时，你正在直接观察短期行为。

Well, no.

嗯，不。

33:08 How do you know what the cognitive light cone of something is?

你怎么知道某物的认知光锥是什么？

Because as you’ve said, it could be almost anything.

因为正如你所说，它几乎可以是任何东西。

The key is you have to do experiments.

关键是你得做实验。

And the way you do experiments is you put barriers…

你做实验的方式就是设置障碍……

You have to do interventional experiments.

你必须做介入实验。

You have to put barriers between it and its goal, and you have to ask what happens.

你必须在它和它的目标之间设置障碍，你必须问会发生什么。

And intelligence is the degree of ingenuity that it has in overcoming barriers between it and its goal.

智力是指它在克服自身与其目标之间的障碍时所具有的独创性程度。

Now, if it were to be that…

现在，如果是这样的话……

Now, this is, I think, a totally doable, but impractical and very expensive experiment.

现在，我认为这是一个完全可行的实验，但不切实际且非常昂贵。

But you could imagine setting up a scenario where the bacteria were blocked from becoming more complex.

但你可以想象设置一个场景，阻止细菌变得更加复杂。

And you can ask if they would try to find ways around it, or whether their goals are actually metabolic.

你可以问他们是否会尝试找到解决方法，或者他们的目标是否实际上是新陈代谢的。

33:51 And as long as those goals are met, they’re not going to actually get around your barrier.

只要这些目标得到实现，它们就不会真正绕过你的障碍。

This business of putting barriers between things and their goals is actually extremely powerful because we’ve deployed it in all kinds of…

这种在事物与其目标之间设置障碍的业务实际上非常强大，因为我们已经将其部署在各种......

And I’m sure we’ll get to this later, but we’ve deployed it in all kinds of weird systems that you wouldn’t think are goal-driven systems.

我相信我们稍后会讨论这个问题，但我们已经将其部署在各种奇怪的系统中，您不会认为这些系统是目标驱动的系统。

And what it allows us to do is to get beyond just what you called anthropomorphizing claims of, say, you know, saying, “Oh, yeah, I think this thing is trying to do this or that.” The question is, well, let’s do the experiment.

它让我们能够做的就是超越所谓的拟人化主张，比如说，你知道，说，“哦，是的，我认为这个东西正在尝试做这个或那个。”问题是，好吧，让我们做一下实验。

And one other thing I want to say about anthropomorphizing is people say this to me all the time.

关于拟人化，我想说的另一件事是人们总是对我这么说。

34:27 I don’t think that exists.

我认为那不存在。

I think that’s kind of like, you know…

我认为这有点像，你知道……

And I’ll tell you why.

我会告诉你原因。

I think it’s like heresy or like other terms that aren’t really a thing.

我认为这就像异端邪说或其他不真实的术语。

Because if you unpack it, here’s what anthropomorphism means: Humans have a certain magic, and you’re making a category error by attributing that magic somewhere else.

因为如果你把它解开，就会发现拟人化的意思是：人类有某种魔力，如果你把这种魔力归因于其他地方，那就犯了类别错误。

My point is we have the same magic that everything has.

我的观点是，我们拥有与一切事物相同的魔力。

We have a couple of interesting things besides, the cognitive light cone and some other stuff.

除此之外，我们还有一些有趣的东西，认知光锥和其他一些东西。

And it isn’t that you have to keep the humans separate because there’s some bright line.

这并不是说你必须将人类分开，因为存在一些明确的界限。

It’s just…

这只是……

It’s that same old…

还是那个老样子……

All I’m arguing for is the scientific method, really.

我所主张的只是科学方法，真的。

That’s really all this is.

这就是全部。

35:11 All I’m saying is you can’t just make pronouncements such as, “Humans are this,” and let’s not sort of push that.

我想说的是，你不能只是发表诸如“人类就是这样”之类的声明，我们就不要强迫它了。

You have to do experiments.

你必须做实验。

After you’ve done your experiments, you can say either, “I’ve done it, and I’ve found…

完成实验后，你可以说：“我已经完成了，而且我发现......

Look at that.

看看那个。

That thing actually can predict the future for the next, you know, 12 minutes.

那东西实际上可以预测接下来 12 分钟的未来。

Amazing.” Or you say, “You know what?

太棒了。”或者你说：“你知道吗？

I’ve tried all the things in the behaviorist handbook, they just don’t help me with this.

我已经尝试了行为主义手册中的所有内容，但它们对我没有帮助。

It’s a very low level of…” Like, that’s it.

这是一个非常低的水平……”就像，就是这样。

It’s a very low level of intelligence.

这是一个非常低的智力水平。

Fine, right?

好吧，对吧？

Done.

完毕。

So that’s really all I’m arguing for, is an empirical approach.

所以这就是我所主张的，是一种经验方法。

And then things like anthropomorphism go away.

然后拟人化之类的东西就消失了。

It’s just a matter of, have you done the experiment, and what did you find?

这只是一个问题，你做了实验吗？你发现了什么？

And that’s actually one of the things you’re saying, that if you remove the categorization of things, you can use the tools…

这实际上是你所说的事情之一，如果你删除事物的分类，你可以使用这些工具......

35:45 …Of one discipline on everything.

……凡事都遵循一种纪律。

You could try.

你可以尝试一下。

To try and then see.

尝试然后看看。

35:57 That’s the underpinnings of the criticism of anthropomorphization, because what is that?

这就是对拟人化批评的基础，因为那是什么？

That’s like psychoanalysis of another human could technically be applied to robots, to AI systems, to more primitive biological systems, and so on.

这就像对另一个人的精神分析在技术上可以应用于机器人、人工智能系统、更原始的生物系统等等。

Try.

尝试。

Yeah.

是的。

36:18 We’ve used everything from basic habituation conditioning all the way through anxiolytics, hallucinogens, all kinds of cognitive modification on a range of things that you wouldn’t believe.

我们使用了各种方法，从基本的习惯调节一直到抗焦虑药、致幻剂、各种认知改变，效果都令人难以置信。

And by the way, I’m not the first person to come up with this.

顺便说一句，我不是第一个提出这个想法的人。

So there was a guy named Bose well over 100 years ago who was studying how anesthesia affected animals and animal cells, and drawing specific curves around electrical excitability.

100 多年前，有一个名叫 Bose 的人正在研究麻醉如何影响动物和动物细胞，并绘制有关电兴奋性的特定曲线。

And he then went and did it with plants and saw some very similar phenomena.

然后他用植物做了实验，发现了一些非常相似的现象。

And being the genius that he was, he then said, “Well, how do I…” I don’t know when to stop, but there’s no, there’s no…

作为天才，他接着说：“好吧，我该怎么……”我不知道什么时候该停下来，但没有，没有……

You know, everybody thinks we should have stopped long before plants because people made fun of him for that.

你知道，每个人都认为我们应该早在植物出现之前就停下来，因为人们因此取笑他。

36:59 And he’s like, “Yeah, but the science doesn’t tell us where to stop.

他说：“是的，但是科学并没有告诉我们在哪里停止。

The tool is working, let’s keep going.” And he showed interesting phenomena on materials, metals, and other kinds of materials, right?

该工具正在发挥作用，让我们继续前进。”他在材料、金属和其他种类的材料上展示了有趣的现象，对吗？

And so…

所以……

…The interesting thing is that there is no generic rule that tells you when you need to stop.

……有趣的是，没有通用规则告诉您何时需要停止。

We make those up.

这些都是我们编造的。

Those are completely made up.

这些完全是编出来的。

You have to just do the science and find out.

你必须做科学并找出答案。

Yeah, we’ll probably get to it.

是的，我们可能会做到这一点。

37:23 You’ve been doing recent work on looking at computational systems, even trivial ones like algorithms— …

你最近一直在研究计算系统，甚至是像算法这样的琐碎的系统——……

sorting algorithms- …and analyzing them in a behavioral kind of way, to see if there are minds inside those sorting algorithms.

排序算法——……并以行为方式分析它们，看看这些排序算法中是否有思想。

And, of course, let me make a pothead statement question here, that you could start to do things like trying to do psychedelics with a sorting algorithm.

当然，让我在这里提出一个傻瓜陈述问题，你可以开始做一些事情，比如尝试用排序算法做迷幻药。

And what does that even look like?

那到底是什么样子的呢？

It looks like a ridiculous question that’ll get you fired from most academic departments, but it may be, if you take it seriously, you could try— …and see if it applies.

这看起来像是一个荒谬的问题，会让你被大多数学术部门解雇，但如果你认真对待它，你可以尝试——……看看它是否适用。

38:00 If a thing could be shown to have some kind of cognitive complexity, some kind of mind, why not apply to it the same kind of analysis and the same kind of tools, like psychedelics, that you would to a human mind that’s a complex human mind?

如果一个事物可以被证明具有某种认知复杂性，某种心灵，为什么不对其应用同样类型的分析和同样类型的工具，比如致幻剂，就像对人类复杂的心灵进行分析一样？

It at least might be a productive question to ask.

这至少可能是一个富有成效的问题。

You’ve seen spiders on psychedelics, more primitive biological organisms on psychedelics.

你见过服用迷幻药的蜘蛛，服用迷幻药的更原始的生物有机体。

Why not try to see what an algorithm does on psychedelics?

为什么不尝试看看算法对迷幻药有什么作用呢？

Anyway.

反正。

Well, yeah, because, you see, the thing to remember is we don’t have a magic sense or really good intuition for what the mapping is between the embodiment of something and the degree of intelligence it has.

嗯，是的，因为，你看，要记住的是，我们对于某物的体现和它所拥有的智能程度之间的映射没有神奇的感觉或真正良好的直觉。

38:33 We think we do because we have an N of one example on Earth and we kind of know what to expect from cells, snakes to, you know, primates, but we really don’t.

我们认为我们做到了，因为我们在地球上有N个例子，而且我们有点知道从细胞、蛇到灵长类动物会发生什么，但我们真的不知道。

We don’t have, and this is, we’ll get into more of the stuff on the Platonic space, but our intuitions around that stuff are so bad that to really think that we know enough not to try things at this point is, I think, really short-sighted.

我们没有，而且我们将进入更多关于柏拉图空间的东西，但我们对这些东西的直觉是如此糟糕，以至于我认为，真正认为我们知道的足够多，在这一点上不去尝试，是非常短视的。

Before we talk about the platonic space, let’s let’s lay out some foundations.

在讨论柏拉图空间之前，让我们先奠定一些基础。

39:09 I think one useful one comes from the paper, Technological Approach to Mind Everywhere.

我认为一篇有用的文章来自《心灵无处不在的技术方法》一文。

An experimentally grounded framework for understanding diverse bodies and minds.

一个基于实验的框架，用于理解不同的身体和思想。

Could you tell me about this framework, and maybe can you tell me about figure one from this paper that has a few components?

您能否告诉我有关此框架的信息，也许您可​​以告诉我有关本文中包含几个组件的图一的信息吗？

One is the tiers of biological cognition that goes from group to whole organism to whole tissue organ, down to neural network, down to cytoskeleton, down to genetic network, and then there’s layers of biological systems from ecosystem, down to swarm, down to organism, tissue, and then finally cell.

一是生物认知的层次，从群体到整个有机体到整个组织器官，下到神经网络，下到细胞骨架，下到遗传网络，然后是生物系统的各个层次，从生态系统，到群体，到有机体，组织，最后是细胞。

So can you explain this figure and can you explain the TAME, so-called, framework?

那么您能解释一下这个图以及所谓的 TAME 框架吗？

So this is the version 1.0, and there’s a kind of update, a 2.0, that I’m writing at the moment, trying to formalize in a careful way all the things that we’ve been talking about here, and in particular, this notion of having to do experiments to figure out where any given system is on a continuum, and we can…

所以这是版本 1.0，还有一种更新，即 2.0，我现在正在编写，试图以仔细的方式形式化我们在这里讨论的所有事情，特别是必须进行实验来找出任何给定系统在连续体上的位置的概念，我们可以......

40:02 let’s just start with figure two maybe for a second, and then we’ll come back to figure one.

让我们从图二开始，也许一会儿，然后我们再回到图一。

And first, just to unpack the acronym, I like the idea that it spells out TAME, because the central focus of this is interactions and how do you interact with a system to have a productive interaction with it, and the idea is that cognitive claims are really protocol claims.

首先，只是为了解开这个缩写词，我喜欢它拼写为 TAME 的想法，因为它的中心焦点是交互以及如何与系统交互以与其进行富有成效的交互，并且这个想法是认知声明实际上是协议声明。

40:42 When you tell me that something has some degree of intelligence, what you’re really saying is, “This is the set of tools I’m going to deploy, and we can all find out how that worked out for you.” And so technological, because I wanted to be clear with my colleagues that this was not a project in just philosophy.

当你告诉我某个东西具有一定程度的智能时，你真正想说的是，“这是我要部署的一套工具，我们都可以知道它对你来说效果如何。”之所以如此技术化，是因为我想向同事们表明，这不仅仅是一个哲学项目。

This had very specific, empirical implications that are going to play out in engineering and regenerative medicine and so on.

这具有非常具体的经验意义，将在工程和再生医学等领域发挥作用。

Technological approach to mind everywhere, this idea that we don’t know yet where different kinds of minds are to be found and we have to empirically figure that out.

技术方法无处不在，我们还不知道在哪里可以找到不同类型的思想，我们必须凭经验找出答案。

41:15 And so what you see here in figure two is basically this idea that there is a spectrum, and I’m just showing four waypoints along that spectrum, and as you move to the right of that spectrum, a couple things happen: persuadability goes up, meaning that the systems become more reprogrammable, more plastic, more able to do different things than whatever they’re standardly doing, so you have more ability to get them to do new and interesting things.

所以你在图二中看到的基本上是一个频谱的想法，我只是展示了沿着该频谱的四个路点，当你移动到该频谱的右侧时，会发生一些事情：说服力上升，这意味着系统变得更可重新编程，更具可塑性，更能够做比他们标准做的事情不同的事情，所以你有更多的能力让他们做新的和有趣的事情。

The effort needed to exert influence goes down; that is, autonomy goes up.

施加影响所需的努力减少；也就是说，自主权提高了。

And to the extent that you are good at convincing or motivating the system to do things, you don’t have to sweat the details as much, right?

如果你擅长说服或激励系统做事，你就不必在细节上花太多功夫，对吧？

And this also has to do with what I call engineering agential materials.

这也与我所说的工程代理材料有关。

41:51 So when you engineer wood, metal, plastic, things like that, you are responsible for absolutely everything because the material is not going to do anything other than hopefully hold its shape.

因此，当你设计木材、金属、塑料之类的东西时，你绝对要对所有事情负责，因为这些材料除了希望保持其形状之外不会做任何事情。

If you’re engineering active matter, or you’re engineering computational materials, or better yet, agential materials like living matter, you can do some very high-level prompting and let the system then do very complicated things that you don’t need to micromanage, and we all know that that increases when you’re starting to work with intelligent systems like animals and humans and so on.

如果你正在设计活性物质，或者你正在设计计算材料，或者更好的是，像生命物质这样的代理材料，你可以做一些非常高级的提示，然后让系统做非常复杂的事情，你不需要进行微观管理，我们都知道，当你开始使用动物和人类等智能系统时，这种情况会增加。

And the other thing that goes down as you get to the right is the amount of mechanism, or physics, that you need to exert the influence goes down.

当你向右移动时，另一件事会下降，那就是你需要施加影响的机制或物理量会下降。

42:31 So if you know how your thermostat is to be set as far as its set point, you really don’t need to know much of anything else, right?

因此，如果您知道如何将恒温器设置为设定点，那么您真的不需要了解太多其他信息，对吗？

You, you just need to know that it is a homeostatic system and that this is how I change the set point.

你，你只需要知道它是一个稳态系统，这就是我改变设定点的方式。

You don’t need to know how the cooling and heating plant works in order to get it to do complex things.

您无需了解冷却和加热设备的工作原理即可使其完成复杂的工作。

By the way, a quick pause just for people who are listening, let me describe what’s in the figure.

顺便说一句，请让正在听的人暂停一下，让我描述一下图中的内容。

42:46 So there’s four different systems going up the scale of persuadability.

因此，有四种不同的系统可以提高说服力。

So the first system is a mechanical clock, then it’s a thermostat, then it’s a dog that gets rewards and punishments, Pavlov’s dog, and then finally a bunch of very smart-looking humans communicating with each other and arguing, persuading each other using reasons.

所以第一个系统是一个机械钟，然后是一个恒温器，然后是一只得到奖励和惩罚的狗，巴甫洛夫的狗，最后是一群看起来非常聪明的人类，他们互相交流、争论，用理由说服对方。

And then there’s arrows below that showing persuadability going up as you go up these systems from the mechanical clock to a bunch of Greeks arguing, and then going down as the effort needed to exert influence, and once again, going down as mechanism knowledge needed to exert that influence.

下面的箭头显示，当你将这些系统从机械钟上升到一群希腊人争论时，说服力就会上升，然后随着施加影响所需的努力而下降，再一次，随着施加这种影响所需的机制知识而下降。

Yeah.

是的。

43:30 I’ll give you an example about that, panel C here with the dog.

我给你举个例子，C 组里有狗。

Isn’t it amazing that humans have been training dogs and horses for thousands of years knowing zero neuroscience?

人类数千年来一直在对神经科学知之甚少的情况下训练狗和马，这难道不令人惊奇吗？

Also amazing is that when I’m talking to you right now, I don’t need to worry about manipulating all of the synaptic proteins in your brain to make you understand what I’m saying and hopefully remember it.

同样令人惊奇的是，当我现在和你说话时，我不需要担心操纵你大脑中的所有突触蛋白来让你理解我在说什么并希望记住它。

You’re going to do that all on your own.

你将自己完成这一切。

I’m giving you very thin, in terms of information content, very thin prompts, and I’m counting on you as a multi-scale agential material to take care of the chemistry underneath, all right?

我给你的信息内容非常薄弱，提示非常薄弱，我指望你作为多尺度代理材料来处理下面的化学反应，好吗？

So you don’t need a wrench to convince me?

所以你不需要扳手来说服我吗？

Correct.

正确的。

44:05 I don’t need, and I don’t need physics to convince you, and I don’t need to know how you work.

我不需要，也不需要物理学来说服你，我不需要知道你是如何工作的。

I don’t need to understand all of the steps.

我不需要理解所有步骤。

What I do need to have is trust that you are a multi-scale cognitive system that already does that for yourself, and you do.

我真正需要的是相信你是一个多尺度的认知系统，它已经为你自己做到了这一点，而你确实做到了。

This is an amazing thing.

这是一件了不起的事情。

I know people don’t think about this enough, I think.

我认为，我知道人们对这个问题的思考还不够。

When you wake up in the morning and you have social goals, research goals, financial goals, whatever it is that you have, in order for you to act on those goals, sodium and calcium and other ions have to cross your muscle membranes.

当你早上醒来时，你有社会目标、研究目标、财务目标，无论你有什么目标，为了让你实现这些目标，钠、钙和其他离子必须穿过你的肌肉膜。

Those incredibly abstract goal states ultimately have to make the chemistry dance in a very particular way, right?

那些令人难以置信的抽象目标状态最终必须让化学反应以一种非常特殊的方式跳舞，对吗？

You—

你——

44:42 Our entire body is a transducer of very abstract things.

我们的整个身体是非常抽象事物的转换器。

And, by the way, not just our brains, but our organs have anatomical goals and other things that we can talk about, because all of this plays out in regeneration and development and so on.

顺便说一句，不仅我们的大脑，我们的器官也有解剖学目标和其他我们可以谈论的东西，因为所有这些都在再生和发育等中发挥作用。

But the scaling, right, of all of these things, the way that…

但是，所有这些事情的扩展，对吧，这样……

the way you regulate yourself is not by, “Oh my God,” you don’t have to sit there and think, “Wow, I really have to push some sodiums across this membrane.” All of that happens automatically, and that’s the incredible benefit of these multi-scale materials.

你调节自己的方式不是“天哪”，你不必坐在那里想，“哇，我真的必须把一些钠推过这层膜。”所有这一切都是自动发生的，这就是这些多尺度材料的令人难以置信的好处。

So what I was trying to do in this paper is a couple of things.

所以我在这篇论文中试图做的是几件事。

45:18 All of these were, by the way, drawn by Jeremy Gay, who’s this amazing graphic artist that works with me.

顺便说一句，所有这些都是由杰里米·盖伊（Jeremy Gay）绘制的，他是一位与我一起工作的令人惊叹的图形艺术家。

First of all, in panel A, which is the spiral I was trying to point out, is that at every level of biological organization, like we all know we’re sort of nested dolls of organs and tissues and cells and molecules and whatever, but what I was trying to point out is that this is not just structural.

首先，在A组中，也就是我试图指出的螺旋，在生物组织的各个层面，就像我们都知道的那样，我们是器官、组织、细胞和分子等等的嵌套娃娃，但我想指出的是，这不仅仅是结构性的。

Every one of those layers is competent and is doing problem-solving in different spaces, and spaces that are very hard for us to imagine.

每一层都有能力，在不同的空间中解决问题，而这些空间是我们很难想象的。

We humans are, because of our own evolutionary history, so obsessed with movement in three-dimensional space that even in AI you see this all the time.

由于我们自己的进化历史，我们人类如此痴迷于三维空间中的运动，甚至在人工智能中你也一直看到这种情况。

45:53 They say, “Well, this thing doesn’t have a robotic body, it’s not embodied.” Yeah, it’s not embodied by moving around in 3D space, but biology has embodiments in all kinds of spaces that are hard for us to imagine, right?

他们说，“嗯，这个东西没有机器人身体，它没有实体化。”是的，它不是通过在 3D 空间中移动来体现的，但生物学在各种我们很难想象的空间中都有体现，对吧？

So your cells and tissues are moving in high-dimensional physiological state spaces, in gene expression state spaces, in anatomical state spaces.

所以你的细胞和组织在高维生理状态空间、基因表达状态空间、解剖状态空间中移动。

They’re doing that perception, decision-making, action loop that we do in 3D space when we think about robots wandering around your kitchen.

当我们想象机器人在你的厨房里闲逛时，他们正在做感知、决策、行动循环，就像我们在 3D 空间中所做的那样。

They’re doing those loops in these other spaces.

他们在其他空间中进行这些循环。

And so the first thing I was trying to point out is that every layer of your body has its own ability to solve problems in those spaces.

因此，我想要指出的第一件事是，你身体的每一层都有自己解决这些空间问题的能力。

46:31 And then on the right, what I was saying is that this distinction between, you know, people say, “Well, there are living beings and then there are engineered machines,” and then they often follow up with all the things machines are never going to be able to do and whatever.

然后在右边，我想说的是，你知道，人们说，“嗯，有生物，然后有工程机器”，然后他们经常跟进所有机器永远无法做的事情等等。

And so what I was trying to point out here is that it is very difficult to maintain those kinds of distinctions, because life is incredibly interoperable.

所以我在这里想指出的是，维持这些区别是非常困难的，因为生活具有令人难以置信的互操作性。

Life doesn’t really care if the thing it’s working with was evolved through random trial and error or was engineered with a higher degree of agency, because at every level within the cell, within the tissue, within the organism, within the collective, you can replace and substitute engineered systems with naturally-evolved systems.

生命并不真正关心它所处理的东西是通过随机试验和错误进化的，还是通过更高程度的机构设计的，因为在细胞内、组织内、有机体内、集体内的每个层面上，你都可以用自然进化的系统替换和替代工程系统。

47:12 And that question of, “Is it real, you know, is it biology or is it technology?” I don’t think is a useful question anymore.

还有一个问题，“这是真的吗？你知道，这是生物学还是技术？”我认为这不再是一个有用的问题。

So I was trying to warm people up with this idea that what we’re going to do now is talk about minds in general, regardless of their history or their composition.

所以我试图让人们暖和起来，我们现在要做的是谈论一般的思想，无论他们的历史或构成如何。

It doesn’t matter what you’re made of.

你是由什么构成的并不重要。

It doesn’t matter how you got here.

你如何来到这里并不重要。

Let’s talk about what you’re able to do and what your inner world looks like.

让我们谈谈你能做什么以及你的内心世界是什么样的。

That was the goal of that.

这就是我们的目标。

Is it useful to, as a thought experiment, as an experiment of radical empathy, to try to put ourselves in the space of the different minds at each stage of the spiral?

作为一个思想实验，作为一个激进同理心的实验，尝试将我们自己置于螺旋的每个阶段的不同思想的空间中有用吗？

47:34 Like, what state space is human civilization as a collective embodied?

比如，人类文明作为一个集体体现了怎样的国家空间？

Like, what does it operate in?

比如，它的作用是什么？

So humans, individual organisms, operate in 3D space.

因此人类，个体有机体，在 3D 空间中运作。

That’s what we understand.

这就是我们的理解。

But when there’s a bunch of us together…

但当我们一群人在一起时……

…What are we doing together?

……我们在一起做什么？

It’s really hard, and you have to do experiments, which at larger scales are really difficult.

这真的很难，你必须做实验，而在更大的范围内，这真的很困难。

But there is such a thing?

但有这样的事吗？

There may well be.

很可能有。

48:14 We have to do experiments.

我们必须做实验。

I don’t know.

我不知道。

Here’s an example.

这是一个例子。

Somebody will say to me, “Well, you know, with your kind of panpsychist view, you probably think the weather is agential too.” It’s like, “Well, I can’t say that, but we don’t know, but have you ever tried to see if a hurricane has habituation or sensitization?” Maybe.

有人会对我说：“好吧，你知道，按照你的泛心论观点，你可能认为天气也是有影响的。”就像，“好吧，我不能这么说，但我们不知道，但你有没有尝试过看看飓风是否具有习惯性或敏感性？”或许。

We haven’t done the experiment.

我们还没有做过实验。

It’s hard, but you could, right?

这很难，但你可以，对吧？

And maybe weather systems can have certain kinds of memories.

也许天气系统可以拥有某些类型的记忆。

I have no idea.

我不知道。

We have to do experiments.

我们必须做实验。

48:41 So I don’t know what the entire human society is doing, but I’ll just give you a simple example of the kinds of tools, and we’re actively trying to build tools now to enable radically different agents to communicate.

所以我不知道整个人类社会在做什么，但我只会给你一个简单的工具示例，我们现在正在积极尝试构建工具，以使完全不同的代理能够进行通信。

So we are doing this using AI and other tools to try and get this kind of communication going across very different spaces.

因此，我们正在使用人工智能和其他工具来尝试让这种沟通跨越非常不同的空间。

I’ll just give you a very dumb example of how that might be.

我会给你一个非常愚蠢的例子来说明这可能是怎样的。

Imagine that you’re playing tic-tac-toe against an alien.

想象一下，您正在与外星人玩井字游戏。

So you’re in a room.

所以你在一个房间里。

You don’t see him.

你看不见他。

You draw the tic-tac-toe thing on the board, on the floor, and you know what you’re doing.

你在棋盘上、地板上画井字游戏，然后你就知道自己在做什么。

49:17 You’re trying to make straight lines with Xs and Os, and you’re having a nice game.

你试图用 Xs 和 Os 画出直线，并且你玩得很开心。

It’s obvious that he understands the process.

看得出来他很清楚这个流程。

Like, sometimes you win, sometimes you lose.

就像，有时你赢，有时你输。

It’s obvious.

这是显而易见的。

In that one little segment of activity, you guys are sharing a world.

在这一小段活动中，你们共享一个世界。

What’s happening in the other room next door?

隔壁的另一个房间发生了什么事？

Well, let’s say the alien doesn’t know anything about geometry.

好吧，假设外星人对几何一无所知。

He doesn’t understand straight lines.

他不懂直线。

What he’s doing is he’s got a box, and it’s full of basically billiard balls, each one of which has a number on it.

他正在做的是他有一个盒子，里面装满了基本上是台球的东西，每个球上都有一个数字。

And all he’s doing is he’s looking through the box to find billiard balls whose numbers add up to 15.

他所做的只是在盒子里寻找数字加起来为 15 的台球。

He doesn’t understand geometry at all.

他根本不懂几何。

All he understands is arithmetic.

他所懂的只是算术。

49:55 You don’t think about arithmetic, you think geometry.

你考虑的不是算术，而是几何。

The reason you guys are playing the same game is that there’s this magic square, right?

你们玩同一个游戏的原因是有这个幻方，对吧？

That somebody constructed that basically is a three-by-three square, where if you pick the numbers right, they add up to 15.

有人构建的基本上是一个三乘三的正方形，如果你选对了数字，它们加起来就是 15。

He has no idea that there’s a geometric interpretation to this.

他不知道这有几何解释。

He is solving the problem that he sees, which is totally algebraic.

他正在解决他所看到的问题，这完全是代数问题。

You don’t know anything about that.

你对此一无所知。

But if there is an appropriate interface like this magic square, you guys can share that experience.

但如果有像这个幻方这样合适的界面，你们就可以分享这种经验。

You can have an experience.

你可以去体验一下。

It doesn’t mean you start to think like him.

这并不意味着你开始像他一样思考。

It means that you guys are able to interact in a particular way.

这意味着你们能够以特定的方式进行互动。

Okay, so there’s a mapping between the two different ways of seeing the world that allows you to communicate with each other.

好的，两种不同的看待世界的方式之间存在一个映射，使您可以相互交流。

Of seeing a thin slice of the world.

看到世界的一小部分。

Thin slice of the world.

世界的一小部分。

50:36 How do you find that mapping?

您如何找到该映射？

So you’re saying we’re trying to figure out ways of finding that mapping…

所以你是说我们正在试图找出找到该映射的方法......

…For different kinds of systems.

...针对不同类型的系统。

What’s the process for doing that?

这样做的过程是什么？

So the process is twofold.

所以这个过程是双重的。

50:48 One is to get a better understanding of what space the system is navigating, what goals it has, what level of ingenuity it has to reach those goals.

一是更好地了解系统正在航行的空间、它有什么目标以及实现这些目标需要什么水平的独创性。

For example, xenobots, right?

例如，xenobots，对吗？

We make xenobots or anthropods.

我们制造异种机器人或节肢动物。

These are biological systems that have never existed on Earth before.

这些是地球上以前从未存在过的生物系统。

We have no idea what their cognitive properties are.

我们不知道他们的认知特性是什么。

We’re learning.

我们正在学习。

We found some things.

我们发现了一些东西。

But you can’t predict that from first principles because they’re not at all what their past history would inform you of.

但你无法从基本原则中预测这一点，因为它们根本不是他们过去的历史所告诉你的。

Can you actually explain briefly what a xenobot is and what an anthropod is?

你能简单解释一下什么是异种机器人以及什么是类人动物吗？

So one of the things that we’ve been doing is trying to create novel beings that have never been here before.

所以我们一直在做的事情之一就是尝试创造以前从未出现过的新奇生物。

51:24 The reason is that typically when you have a biological system, an animal or a plant, and you say, “Hey, why does it have certain forms of behavior, certain forms of anatomy, certain forms of physiology?

原因是，通常当你有一个生物系统、动物或植物时，你会说：“嘿，为什么它有某些形式的行为、某些形式的解剖学、某些形式的生理学？

Why does it have those?” The answer is always the same.

为什么会有那些？”答案总是一样的。

Well, there’s a history of evolutionary selection, and there’s a long, long history going back of adaptation, and there are certain environments, and this is what survived, and so that’s why it has.

嗯，有进化选择的历史，有很长很长的适应历史，并且有某些环境，这就是生存下来的，所以这就是它存在的原因。

So what I wanted to do was break out of that mold, and to basically force us as a community to dig deeper into where these things come from.

所以我想做的就是打破这种模式，从根本上迫使我们作为一个社区更深入地挖掘这些东西的来源。

52:07 And that means taking away the crutch where you just say, “Well, it’s evolutionary selection that’s why it looks like that.” So in order to do that, we have to make artificial synthetic beings now.

这意味着拿走拐杖，你只需说：“嗯，这是进化选择，这就是为什么它看起来像这样。”因此，为了做到这一点，我们现在必须制造人工合成生物。

To be clear, we are starting with living cells, so it’s not that they had no evolutionary history.

需要明确的是，我们是从活细胞开始的，所以并不是说它们没有进化历史。

The cells do.

细胞确实如此。

They had evolutionary history in frogs or humans or whatever.

它们在青蛙、人类或其他什么方面都有进化历史。

But the creatures they make and the capabilities that these creatures have were never directly selected for.

但它们创造的生物以及这些生物所拥有的能力从来都不是直接选择的。

And in fact, they never existed.

事实上，它们从未存在过。

So you can’t tell the same kind of story.

所以你不能讲同样类型的故事。

And what I mean is, we can take epithelial cells off of an early frog embryo, and you don’t change the DNA.

我的意思是，我们可以从早期青蛙胚胎中取出上皮细胞，而不会改变 DNA。

No synthetic biology circuits, no material scaffolds, no nanomaterials, no weird drugs, none of that.

没有合成生物电路，没有材料支架，没有纳米材料，没有奇怪的药物，这些都没有。

52:46 What we’re mostly doing is liberating them from the instructive influences of the rest of the cells that they were in in their bodies.

我们主要做的就是将它们从体内其他细胞的指导性影响中解放出来。

And so when you do that, normally these cells are bullied by their neighboring cells into having a very boring life.

因此，当你这样做时，通常这些细胞会受到邻近细胞的欺凌，过着非常无聊的生活。

They become a two-dimensional outer covering for the embryo, and they keep out the bacteria, and that’s that.

它们成为胚胎的二维外壳，将细菌拒之门外，仅此而已。

So you might ask, “Well, what are these cells capable of when you take them away from that influence?” So when you do that, they form another little life form we call a xenobot.

所以你可能会问，“那么，当你让这些细胞远离这种影响时，它们能发挥什么作用呢？”因此，当你这样做时，它们会形成另一种小生命形式，我们称之为异种机器人。

And it’s this self-motile little thing that has cilia covering its surface.

正是这个自我运动的小东西，表面覆盖着纤毛。

The cilia are coordinated so they row against the water, and then the thing starts to move, and has all kinds of amazing properties.

纤毛协调一致，因此它们在水面上划行，然后这个东西开始移动，并具有各种令人惊奇的特性。

53:25 It has different gene expression, so it has its own novel transcriptome.

它有不同的基因表达，因此有自己新颖的转录组。

It’s able to do things like kinematic self-replication, meaning make copies of itself from loose cells that you put in its environment.

它能够做诸如运动学自我复制之类的事情，这意味着从放置在其环境中的松散细胞中复制自身。

It has the ability to respond to sound, which normal embryos don’t do.

它具有对声音做出反应的能力，而正常胚胎则没有这种能力。

It has these novel capacities.

它具有这些新颖的功能。

And we did that, and we said, “Look, here are some amazing features of this novel system.

我们这样做了，然后说：“看，这是这个新颖系统的一些令人惊奇的功能。

Let’s try to understand where they came from.” And some people said, “Well, maybe it’s a frog-specific thing,” you know?

让我们尝试了解它们从哪里来。”有些人说，“好吧，也许这是青蛙特有的东西，”你知道吗？

Maybe this is just something unique to frog cells.

也许这只是青蛙细胞所特有的东西。

And so we said, “Okay, what’s the furthest you can get from frog embryonic cells?”

所以我们说，“好吧，从青蛙胚胎细胞中你能得到的最远是多少？”

54:00 How about human adult cells?” And so we took cells from adult human patients who were donating tracheal epithelia for biopsies and things like that, and those cells, again, no genetic change, nothing like that.

那么人类成体细胞呢？”因此，我们从成年患者身上提取了细胞，这些患者捐献了气管上皮细胞用于活检等，而这些细胞又没有发生基因变化，没有类似的东西。

They self-organized into something we call anthropods.

它们自我组织成我们称之为节肢动物的东西。

Again, a self-motile little creature.

又是一个自我驱动的小生物。

9,000 different gene expressions.

9,000 种不同的基因表达。

So about half the genome is now different.

所以现在大约有一半的基因组是不同的。

And they have interesting abilities.

他们有有趣的能力。

For example, they can heal human neural wounds.

例如，它们可以治愈人类神经伤口。

So in vitro, if you plate some neurons and you put a big scratch through it so you damage them, anthropods can sit down, and they will try…

所以在体外，如果你给一些神经元镀上一层大划痕，这样你就损坏了它们，节肢动物就可以坐下来，它们会尝试……

They will spontaneously, without us having to teach them to do it, they will spontaneously try to knit the neurons across.

他们会自发地尝试将神经元编织在一起，而无需我们教他们这样做。

What is this video that we’re looking at here?

我们在这里看到的这个视频是什么？

So this is an anthropod.

所以这是一种节肢动物。

54:44 So often when I give talks about this, I show people this video, and I say, “What do you think this is?” And people will say, “Well, it looks like some primitive organism you got from the bottom of a pond somewhere.” And I’ll say, “Well, what do you think the genome would look like?” And they say, “Well, the genome would look like some primitive creature.” Right?

当我谈论这个问题时，我经常向人们展示这段视频，然后我说，“你认为这是什么？”人们会说，“嗯，它看起来像是从某个池塘底部得到的某种原始生物。”我会说，“好吧，你认为基因组会是什么样子？”他们说，“好吧，基因组看起来就像某种原始生物。”对吗？

If you sequence that thing, you’ll get 100% Homo sapiens.

如果你对那个东西进行测序，你就会得到 100% 智人。

And that doesn’t look like any stage of normal human development.

这看起来不像正常人类发展的任何阶段。

It doesn’t act like any stage of human development.

它的表现与人类发展的任何阶段都不一样。

It has the ability to move around.

它具有四处移动的能力。

It has, as I said, over 9,000 differential gene expressions.

正如我所说，它有超过 9,000 个差异基因表达。

Also interestingly, it is younger than the cells that it comes from.

同样有趣的是，它比它来源的细胞更年轻。

55:20 So it actually has the ability to roll back its age, and we could talk about that and what the implications of that are.

所以它实际上有能力回滚它的年龄，我们可以讨论这一点以及它的含义是什么。

But to go back to your original question, what we’re doing with these kind of systems…

但回到你最初的问题，我们正在用这些系统做什么......

Trying to talk to it.

试图与它交谈。

We’re trying to talk to it.

我们正在尝试与它交谈。

55:31 That’s exactly right.

完全正确。

And not just to this.

而且不仅仅是这个。

We’re trying to talk to molecular networks.

我们正在尝试与分子网络对话。

So we found a couple years ago that gene regulatory networks, never mind the cells, but the molecular pathways inside of cells can have several different kinds of learning, including Pavlovian conditioning.

因此，我们几年前发现，基因调控网络，不管细胞，但细胞内部的分子途径可以有几种不同类型的学习，包括巴甫洛夫条件反射。

And what we’re doing now is trying to talk to it.

我们现在正在做的就是尝试与它对话。

The biomedical applications are obvious.

生物医学应用是显而易见的。

Instead of, “Hey, Siri,” you want, “Hey, liver, why do I feel like crap today?” And you want an answer.

你不需要说“嘿，Siri”，而是“嘿，肝脏，为什么我今天感觉很糟糕？”而你想要一个答案。

55:54 “Well, you know, your potassium levels are this and that, and I don’t feel good for these reasons.” And you should be able to talk to these things, and there should be an interface that allows us to communicate, right?

“嗯，你知道，你的钾含量是这样那样的，由于这些原因我感觉不太好。”而且你应该能够和这些东西对话，并且应该有一个接口可以让我们进行交流，对吧？

And I think AI is going to be a huge component of that interface, of allowing us to talk to these systems.

我认为人工智能将成为该界面的重要组成部分，让我们能够与这些系统对话。

It’s a tool to combat our mind-blindness, to help us see diverse, very unconventional minds that are all around us.

它是对抗我们思维盲目性的工具，帮助我们看到周围各种不同的、非常非传统的思维。

Can you generalize that?

你能概括一下吗？

56:19 So let’s say we meet an alien or an unconventional mind here on Earth.

假设我们在地球上遇到了外星人或非传统思想。

Think of it as a black box.

将其视为一个黑匣子。

You show up.

你出现了。

What’s the procedure for trying to get some hooks into a communication protocol with the thing?

尝试将一些挂钩纳入与该事物的通信协议的过程是什么？

Yeah.

是的。

56:43 That is exactly the mission of my lab.

这正是我实验室的使命。

It is to enable us to develop tools to recognize these things, to learn to communicate with them, to ethically relate to them.

它使我们能够开发工具来识别这些事物，学习与它们沟通，并在道德上与它们建立联系。

And in general, to expand our ability to do this in the world around us.

总的来说，是为了扩大我们在周围世界做到这一点的能力。

I specifically chose these kinds of things because they’re not as alien as proper aliens would be.

我特别选择了这些东西，因为它们并不像真正的外星人那样陌生。

So we have some hope.

所以我们还有一些希望。

I mean, we’re made of them.

我的意思是，我们是由他们组成的。

We have many things in common.

我们有很多共同点。

There’s some hope of understanding them.

理解他们还是有希望的。

You’re talking about xenobots and anthropods?

你在谈论异种机器人和节肢动物吗？

Xenobots, anthropods, cells, and everything else.

异种机器人、节肢动物、细胞和其他一切。

57:12 But they’re alien in a couple of important ways.

但它们在几个重要方面是外星人。

One is the space they live in is very hard for us to imagine.

一是他们居住的空间是我们很难想象的。

What space do they live in?

他们住在什么空间？

Well, your body, your body’s cells, long before we had a brain that was good for navigating three-dimensional space, was navigating the space of anatomical possibilities.

好吧，你的身体，你身体的细胞，早在我们拥有适合导航三维空间的大脑之前，就已经在解剖学可能性的空间中导航了。

It was going from, you start as an egg, and you have to become, you know, a snake or a giraffe or a human, whatever we’re going to be.

它是从一个鸡蛋开始的，你知道，你必须成为一条蛇、一只长颈鹿或一个人，无论我们将成为什么。

57:42 And I specifically am telling you that this general idea, when people model that with cellular automata type of ideas, this open-loop kind of thing where everything just follows local rules and eventually, there’s complexity, and here you go.

我特别告诉你，当人们用元胞自动机类型的想法来建模时，这种总体想法是这种开环的事情，一切都遵循局部规则，最终会变得复杂，就这样。

Now, you’ve got a giraffe or a human.

现在，你有一只长颈鹿或一个人。

I’m specifically telling you that that model is totally insufficient to grasp what’s actually going on.

我特别告诉大家，这个模型完全不足以掌握实际情况。

What’s actually going on, and there have been many, many experiments on this, is that the system is navigating a space.

实际情况是，系统正在空间中导航，对此已经进行了很多很多实验。

It is navigating a space of anatomical possibilities.

它正在探索一个解剖学可能性的空间。

If you try to block where it’s going, it will try to get around you.

如果你试图阻止它去往的地方，它就会试图绕过你。

58:17 If you try to challenge it with things it’s never seen before, it will try to come up with a solution.

如果你尝试用它以前从未见过的东西来挑战它，它会尝试想出一个解决方案。

If you really defeat its ability to do that, which you can, you know, they’re not infinitely intelligent, so you can defeat them.

如果你真的击败了它的能力，你可以，你知道，他们不是无限聪明的，所以你可以击败他们。

You will either get birth defects, or you will get creative problem-solving such as what you’re seeing here with xenobots and anthropods.

你要么会出现先天缺陷，要么会得到创造性的解决问题的方法，就像你在这里看到的异种机器人和节肢动物一样。

If you can’t be a human, you’ll find another way to be.

如果你不能成为一个人，你会找到另一种方式。

You can be an anthropod, for example, or you’ll be something else.

例如，你可以是一种节肢动物，也可以是其他动物。

Just to clarify, what’s the difference between cellular automata type of action where you’re just responding to your local environment and creating some kind of complex behavior, and operating in the space of anatomical possibilities?

只是为了澄清一下，细胞自动机类型的动作（您只是响应本地环境并创建某种复杂的行为）与在解剖学可能性的空间中进行操作之间有什么区别？

Sure.

当然。

So there’s a kind of goal, I guess, you’re articulating.

所以我想，你正在阐明一种目标。

Yes.

是的。

There is some kind…

有某种…

Yes

是的

…of thing.

……的事情。

59:01 There’s a will to X something.

有做某事的意愿。

The will thing, let’s put that aside.

意志的事情，让我们把它放在一边。

Okay, sorry.

好吧，抱歉。

Because that’s a…

因为那是一个……

59:08 Well, it’s fine too.

嗯，也不错。

There I go, anthropomorphizing.

我来了，拟人化。

59:10 I just always love to quote Nietzsche, so there we go.

我总是喜欢引用尼采的话，所以我们就这样吧。

Yeah.

是的。

59:13 Yeah, yeah.

是啊，是啊。

And I’m not saying I’m not saying that’s wrong.

我并不是说我不是说这是错误的。

I’m just saying I don’t have data for that one, but I’ll tell you the stuff that I’m quite certain of.

我只是说我没有这方面的数据，但我会告诉你我非常确定的事情。

There are a couple of different formalisms that we have in control theory.

控制理论中有几种不同的形式主义。

One of those formalisms is open-loop complexity.

这些形式之一是开环复杂性。

In other words, I’ve got a bunch of subunits, like a cellular automaton.

换句话说，我有一堆子单元，就像元胞自动机一样。

They follow certain rules, and you turn the crank, time goes forward, whatever happens, happens.

它们遵循一定的规则，你转动曲柄，时间就会前进，无论发生什么，都会发生。

Now, clearly you can get complexity from this.

现在，显然你可以从中得到复杂性。

Clearly you can get some very interesting-looking things, right?

显然你可以获得一些看起来非常有趣的东西，对吧？

So the game of life, all those kinds of cool things, right?

人生的游戏，所有这些很酷的事情，对吧？

You can get complexity.

你可以得到复杂性。

No, no, no problem.

不，不，没问题。

59:47 But the idea that that model is going to be sufficient to explain and control things like morphogenesis is a hypothesis.

但认为该模型足以解释和控制形态发生等事物的想法只是一个假设。

It’s okay to make that hypothesis, but we know, we know it’s false despite the fact that that is what we learned, you know, in basic cell biology and developmental biology classes.

做出这个假设是可以的，但我们知道，我们知道这是错误的，尽管事实上这是我们在基础细胞生物学和发育生物学课程中学到的。

When the first time you see something like this, inevitably, especially if you’re an engineer in those classes, you go, “Hey, how does it know to do that?

当你第一次看到这样的东西时，不可避免地，特别是如果你是这些课程中的工程师，你会说：“嘿，它是怎么知道这样做的？

How does it know, you know, four fingers instead of seven?” What they tell you is, “It doesn’t know anything.” Make sure.

你知道，它怎么知道是四个手指而不是七个手指？”他们告诉你的是，“它什么都不知道。”确保。

That’s very clear.

这非常清楚。

They all insist, like, when we learn these things, they insist nothing here knows anything.

他们都坚持认为，当我们学习这些东西时，他们坚持认为这里什么都不知道。

1:00:27 There are rules of chemistry, they roll forward, and this is what happens.

化学有规则，它们不断向前推进，这就是所发生的事情。

Okay.

好的。

Now, that model is testable.

现在，该模型是可测试的。

We can ask, “Does that model explain what happens?” Here’s where that model falls down.

我们可以问，“这个模型能解释发生的事情吗？”这就是该模型失败的地方。

If you have that model and situations change, either there’s damage or something in the environment that’s happened, those kinds of open-loop models do not adjust to give you the same goal by different means.

如果您有该模型并且情况发生变化，无论是损坏还是环境中发生了某些事情，这些类型的开环模型都不会调整以通过不同的方式为您提供相同的目标。

This is William James’ definition of intelligence: the same goal by different means.

这就是威廉·詹姆斯对智力的定义：用不同的方式实现相同的目标。

And in particular, working them backward, let’s say you are in regenerative medicine, and you say, “Okay, but this is the situation now.

特别是，逆向分析，假设你从事再生医学，你会说：“好吧，但这就是现在的情况。

I want it to be different.” What should the rules be?

我希望它有所不同。”规则应该是什么？

It’s not reversible.

这是不可逆的。

1:01:09 So the thing with those kinds of open-loop models is they’re not reversible.

因此，这类开环模型的问题是它们是不可逆的。

You don’t know what to do to make the outcome that you want.

你不知道该怎么做才能达到你想要的结果。

All you know how to do is roll them forward, right?

你所知道的就是将它们向前滚动，对吧？

Now, in biology, we see the following.

现在，在生物学中，我们看到了以下内容。

If you have a developmental system and you put barriers between…

如果你有一个发展系统并且你在……之间设置了障碍

So I’m going to give you two pieces of evidence that suggest that there is a goal.

因此，我将向您提供两个证据，表明存在目标。

One piece of evidence is that if you try to block these things from the outcome that they normally have, they will do some amazing things.

一个证据是，如果你试图阻止这些事情发生通常的结果，它们就会做出一些令人惊奇的事情。

Sometimes very clever things, sometimes not at all the way that they normally do it, right?

有时是非常聪明的事情，有时却完全不像他们通常做的那样，对吧？

So this is William James’ definition.

这就是威廉·詹姆斯的定义。

1:01:45 By different means, by following different trajectories, they will go around various local maxima and minima to get to where they need to go.

通过不同的方式，通过遵循不同的轨迹，它们将绕过各种局部最大值和最小值以到达它们需要去的地方。

It is navigation of a space.

这是空间的导航。

It is not blind, turn the crank, and wherever we end up is where we end up.

它不是盲目的，转动曲柄，我们最终到的地方就是我们最终的地方。

That is not what we see experimentally.

这不是我们通过实验看到的。

And more importantly, I think, what we’ve shown, and this is something that I’m particularly happy with in our lab, over the last 20 years, we’ve shown the following.

更重要的是，我认为，我们所展示的，这是我在我们实验室中特别满意的，在过去 20 年里，我们展示了以下内容。

We can actually rewrite the goal states because we found them.

我们实际上可以重写目标状态，因为我们找到了它们。

We have shown through our work on bioelectric imaging and bioelectric reprogramming, we have actually shown how those goal memories are encoded, at least in some cases.

通过我们在生物电成像和生物电重编程方面的工作，我们已经证明，我们实际上已经展示了这些目标记忆是如何编码的，至少在某些情况下是这样。

1:02:21 We certainly haven’t got them all, but we have some.

我们当然没有全部拥有，但我们拥有一些。

If you can find where the goal state is encoded, read it out, and reset it, and the system will now implement a new goal based on what you just reset, that is the ultimate evidence that your goal-directed model is working.

如果您可以找到目标状态的编码位置，将其读出并重置，并且系统现在将根据您刚刚重置的内容实现新目标，那么这就是您的目标导向模型正在发挥作用的最终证据。

Because if there was no goal, that shouldn’t be possible.

因为如果没有目标，那是不可能的。

Right?

对吗？

Once you can find it, read it, interpret it, and rewrite it, it means that by any engineering standard, it means that you’re dealing with a homeostatic mechanism.

一旦你能找到它、阅读它、解释它并重写它，就意味着按照任何工程标准，都意味着你正在处理一种稳态机制。

How do you find where the goal’s encoded?

你如何找到目标的编码位置？

So, through lots and lots of hard work.

所以，经过很多很多的努力。

The barrier thing is part of that?

障碍物是其中的一部分吗？

1:02:58 Creating barriers and observing?

制造障碍并观察？

The barrier thing tells you that you should be looking for a goal.

障碍告诉你，你应该寻找一个目标。

So step one, when you approach an agentic system, is create a barrier of different kinds until you see how persistent it is at pursuing the thing it seemed to have been pursuing originally.

因此，当你接近一个代理系统时，第一步是创建不同类型的障碍，直到你看到它在追求它最初似乎一直在追求的东西时有多么坚持。

Yeah.

是的。

And then you know, okay, cool, this is a…

然后你就知道，好吧，酷，这是一个……

1:03:14 This thing has agency, first of all.

首先，这个东西有代理权。

And then second of all, like, you start to build the intuition about exactly which goal it’s pursuing.

其次，你开始建立关于它所追求的目标的直觉。

Yes.

是的。

1:03:24 The first couple of steps are all imagination.

前几步都是想象。

You have to ask yourself, “What space is this thing even working in?” And you really have to stretch your mind, because we can’t imagine all the spaces that systems work in, right?

你必须问自己，“这个东西到底在什么空间里工作？”你真的必须拓展你的思维，因为我们无法想象系统工作的所有空间，对吗？

So step one is, what space is it?

所以第一步是，它是什么空间？

Step two, what do I think the goal is?

第二步，我认为目标是什么？

And let’s not mistake step two, you’re not done.

我们不要误会第二步，你还没有完成。

Just because you have made a hypothesis, that doesn’t mean you can say, “Well, I see it doing this, therefore that’s the goal.” You don’t know that.

仅仅因为你做出了假设，并不意味着你可以说：“嗯，我看到它正在这样做，因此这就是目标。”你不知道这一点。

You have to actually do experiments.

你必须实际做实验。

Now, once you’ve made those hypotheses, now you do the experiments.

现在，一旦你做出了这些假设，就可以进行实验了。

1:03:50 You say, “Okay, if I want to block it from reaching its goal, how do I do that?” And this, by the way, is exactly the approach we took with the sorting algorithms and with everything else.

你说：“好吧，如果我想阻止它实现目标，我该怎么做呢？”顺便说一句，这正是我们在排序算法和其他所有方面所采用的方法。

You hypothesize the goal, you put a barrier in, and then you get to find out what level of ingenuity it has.

你假设目标，设置障碍，然后你就会发现它的独创性程度。

Maybe what you see is, “Well, that derailed everything, so probably this thing isn’t very smart.” Or you say, “Oh, wow, it can go around and do these things.” Or you might say, “Wow, it’s taking a completely different approach using its affordances in novel ways, like that’s a high level of intelligence.” You will find out what the answer is.

也许你看到的是，“嗯，这让一切都脱轨了，所以这个东西可能不是很聪明。”或者你会说，“哦，哇，它可以四处走动并做这些事情。”或者你可能会说，“哇，它采取了一种完全不同的方法，以新颖的方式利用其可供性，就像这是一种高水平的智能一样。”你会发现答案是什么。

Another pothead question.

又是一个傻瓜问题。

1:04:21 Is it possible to look at, speaking of unconventional organisms and going to Richard Dawkins for example with memes, is it possible to think of things like ideas?

是否有可能看看，谈到非常规有机体，例如理查德·道金斯（Richard Dawkins）的模因，是否有可能思考像想法这样的东西？

Like how weird can we get?

就像我们能变得多么奇怪？

Can we look at ideas as organisms then creating barriers for those ideas, and seeing are the ideas themselves…

我们能否将想法视为有机体，然后为这些想法设置障碍，并看到想法本身......

If you take the actual individual ideas and trying to empathize and visualize what kind of space they might be operating in, can they be seen as organisms that have a mind?

如果你采取实际的个人想法，并试图理解和想象他们可能在什么样的空间中运作，他们可以被视为有思想的有机体吗？

Yeah.

是的。

1:04:58 Okay, if you want to get really weird, we can get really weird here.

好吧，如果你想变得非常奇怪，我们可以在这里变得非常奇怪。

Think about the caterpillar-butterfly transition, okay?

想想毛毛虫到蝴蝶的转变，好吗？

So, you’ve got a caterpillar, soft-bodied kind of creature, has a particular controller that’s suitable for running a soft body, you know, kind of robot.

所以，你有一个毛毛虫，一种软体生物，有一个适合运行软体的特殊控制器，你知道，一种机器人。

It has a brain for that task, and then it has to become this butterfly, hard-bodied creature, flies around.

它有一个大脑来完成这项任务，然后它必须变成这只蝴蝶，身体坚硬的生物，飞来飞去。

Okay.

好的。

During the process of metamorphosis, its brain is basically ripped up and rebuilt from scratch, right?

在变态的过程中，它的大脑基本上是被撕裂并从头开始重建的，对吗？

Now, what’s been found is that if you train the caterpillar, so you give it a new memory, meaning that if the caterpillar sees this color disc, then it crawls over and eats some leaves.

现在，我们发现，如果你训练毛毛虫，你就给了它新的记忆，这意味着如果毛毛虫看到这个颜色圆盘，它就会爬过去吃一些叶子。

Turns out, the butterfly retains that memory.

事实证明，蝴蝶保留了这段记忆。

1:05:39 Now, the obvious question is, how the hell do you retain memories when the medium is being refactored like that?

现在，显而易见的问题是，当媒介被这样重构时，你到底如何保留记忆？

Let’s put that aside.

让我们把它放在一边。

That’s something that I’m going to get somewhere even weirder than that.

我将会得到比这更奇怪的东西。

There’s something else that’s even more interesting than that.

还有比这更有趣的事情。

It’s not just that you have to retain the memory.

这不仅仅是你必须保留记忆。

You have to remap that memory onto a completely new context, because guess what?

您必须将该内存重新映射到全新的上下文，因为猜猜怎么着？

The butterfly doesn’t move the way the caterpillar moves, and it doesn’t care about leaves.

蝴蝶的移动方式与毛毛虫不同，它也不关心树叶。

It wants nectar from flowers.

它想要从花中获取花蜜。

And so if that memory is going to survive, it can’t just persist.

因此，如果这种记忆想要保存下来，它就不能只是持续存在。

It has to…

它必须……

Be remapped

被重新映射

…be remapped into a novel context.

……被重新映射到一个新颖的背景中。

1:06:11 Now, here’s where things get weird.

现在，事情变得奇怪了。

We can take a couple of different perspectives here.

我们可以在这里采取几种不同的观点。

We can take the perspective of the caterpillar facing some sort of crazy singularity and say, “My God, I’m going to cease to exist, but, you know, I’ll sort of be reborn in this new higher-dimensional world where I’ll fly.” Okay, so that’s one thing.

我们可以从毛毛虫面对某种疯狂奇点的角度说：“天哪，我将不复存在，但是，你知道，我会在这个新的更高维度的世界中重生，在那里我会飞翔。”好吧，这是一回事。

We can take the perspective of the butterfly and say that, “Well, here I am, but, you know, I seem to be saddled with some tendencies and some memories, and I don’t know where the hell they came from, and I don’t remember exactly how I got them, and they seem to be a core part of my psychological makeup, and, you know, they’re…

我们可以从蝴蝶的角度说，“好吧，我在这里，但是，你知道，我似乎背负着一些倾向和一些记忆，我不知道它们到底从哪里来，我也不记得我到底是如何得到它们的，它们似乎是我心理构成的核心部分，而且，你知道，它们……

1:06:49 If they come from somewhere.

如果他们来自某个地方。

I don’t know where they come from.” Right?

我不知道他们从哪里来。”对吗？

So you can take that perspective.

所以你可以采取这种观点。

But there’s a third perspective that I think is really interesting and useful.

但我认为还有第三种观点非常有趣且有用。

The third perspective is that of the memory itself.

第三个视角是记忆本身的视角。

If you take a perspective of the memory, so what is a memory?

如果从记忆的角度来看，那么什么是记忆呢？

It is a pattern.

这是一种模式。

It is an informational pattern that was continuously reinforced within one cognitive system, and now here I am on this memory.

这是一种在一个认知系统中不断强化的信息模式，现在我就在这个记忆中。

What do I need to do to persist into the future?

未来我需要做什么才能坚持？

Well, now I’m facing the paradox of change.

好吧，现在我面临着变化的悖论。

If I try to remain the same, I’m gone.

如果我试图保持不变，我就会消失。

There’s no way the butterfly is going to retain me in the original form that I’m in now.

蝴蝶不可能让我保持现在的样子。

What I need to do is change, adapt, and morph.

我需要做的是改变、适应和变形。

Now, you might say, “Well, that’s kind of crazy.

现在，你可能会说：“嗯，这有点疯狂。

1:07:31 Well, how are you taking the perspective of a pattern within an excitable medium?” Right?

好吧，你如何看待可兴奋媒介中的模式？”正确的？

Agents are physical things.

代理是有形的东西。

You’re talking about information, right?

你说的是信息，对吗？

So let me tell you another quick science fiction story.

让我告诉你另一个简短的科幻故事。

Imagine that some creatures come out from the center of the earth.

想象一些生物从地球中心出来。

They live down in the core.

他们生活在核心地带。

They’re super dense, okay?

它们非常密集，好吗？

They’re incredibly dense because they live down in the core.

它们的密度非常大，因为它们生活在地核中。

They have gamma ray vision, you know, for…

他们有伽马射线视觉，你知道，为了……

And so on.

等等。

So they come out to the surface.

所以他们就会浮出水面。

What do they see?

他们看到了什么？

Well, all of this stuff that we’re seeing here, this is like a thin plasma to them.

好吧，我们在这里看到的所有这些东西，对他们来说就像稀薄的等离子体。

They are so dense.

它们是如此密集。

None of this is solid to them.

这些对他们来说都不可靠。

1:08:06 They don’t see any of this stuff.

他们看不到任何这些东西。

So they’re walking around, you know, because the planet is sort of, you know, covered in this like thin gas, you know.

所以他们在四处走动，你知道，因为地球有点像稀薄的气体一样覆盖着。

And one of them is a scientist and he’s taking measurements of the gas, and he says to the others, “You know, I’ve been watching this gas, and there are like little whirlpools in this gas, and they almost look like agents.

其中一个是科学家，他正在测量气体，他对其他人说，“你知道，我一直在观察这种气体，这种气体中有小漩涡，它们看起来几乎像药剂。

They almost look like they’re doing things.

他们看起来几乎像是在做事。

They’re moving around, they kind of hold themselves together for a little bit, and they’re trying to make stuff happen.” And the others say, “Well, that’s crazy.

他们四处走动，稍微团结起来，努力让事情发生。”其他人则说：“好吧，这太疯狂了。

Patterns in a gas can’t be agents.

气体中的模式不能成为媒介。

We’re agents.

我们是代理商。

We’re solid.

我们很坚强。

This is just patterns in an excitable medium.”

这只是一种令人兴奋的媒介中的模式。”

1:08:38 And by the way, how long do they hold together?

顺便问一下，他们在一起能坚持多久？

He says, “Well, about 100 years.” “Well, that’s crazy.

他说：“嗯，大约 100 年。” “嗯，这太疯狂了。

Nothing…

没什么……

You know, no real agent can exist to dissipate that fast.” Okay.

你知道，没有任何真正的特工能够消散得那么快。”好的。

We are all metabolic patterns, among other things, right?

除其他外，我们都是新陈代谢模式，对吧？

And so one of the things that…

其中一件事是……

And so you see what I’m warming up to here.

所以你知道我在这里正在做什么。

So one of the things that we’ve been trying to dissolve, and this is some work that I’ve done with Chris Fields and others, is this distinction between thoughts and thinkers.

因此，我们一直试图解决的问题之一，也是我与克里斯·菲尔兹（Chris Fields）和其他人一起完成的一些工作，就是思想和思想家之间的区别。

So all agents are patterns within some excitable medium, we could talk about what that is, and they can spawn off others.

因此，所有代理都是某种可兴奋介质中的模式，我们可以讨论那是什么，并且它们可以产生其他代理。

And now you can have a really interesting spectrum.

现在你可以得到一个非常有趣的频谱。

Here’s the spectrum.

这是频谱。

1:09:15 You can have fleeting thoughts, which are like waves in the ocean when you throw a rock in.

你可能会有转瞬即逝的念头，就像你扔一块石头进去时，它们就像大海中的波浪一样。

You know, they sort of go through the excitable medium and then they’re gone.

你知道，他们经历了令人兴奋的媒介，然后就消失了。

They pass through and they’re gone, right?

他们经过之后就消失了，对吗？

So those are kind of fleeting thoughts.

所以这些都是转瞬即逝的想法。

Then you can have patterns that have a degree of persistence, so they might be hurricanes or solitons or persistent thoughts or earworms or depressive thoughts.

然后你就可以拥有具有一定程度持久性的模式，因此它们可能是飓风或孤子或持久的想法或耳虫或抑郁的想法。

Those are harder to get rid of.

这些更难摆脱。

They stick around for a little while.

他们停留了一会儿。

They often do a little bit of niche construction, so they change the actual brain to make it easier to have more of those thoughts, right?

他们经常做一些利基建设，所以他们改变了实际的大脑，让他们更容易产生更多这样的想法，对吗？

Like, that’s a thing.

就像，那是一件事。

And so they stay around longer.

因此他们停留的时间更长。

Now what’s further than that?

现在还有什么比这更进一步呢？

1:10:00 Well, fragments, personality fragments of a dissociative personality disorder, they’re more stable, and they’re not just on autopilot.

嗯，碎片，分离性人格障碍的人格碎片，它们更稳定，而且它们不仅仅是处于自动驾驶状态。

They have goals and they can do things, and then past that is a full-blown human personality.

他们有目标，可以做事，然后就是一个成熟的人格。

And who the hell knows what’s past that?

谁知道过去发生了什么？

Maybe some sort of trans-human, you know, trans-personal, like, I don’t know, right?

也许某种超人类，你知道，超个人，就像，我不知道，对吧？

But this idea, again, I’m back to this notion of a spectrum.

但这个想法，我又回到了频谱的概念。

It’s there is not a sharp distinction between, you know, we are real agents and then we have these thoughts.

你知道，我们是真正的代理人，然后我们有这些想法，这之间没有明显的区别。

Yeah, patterns can be agents too, but again, you don’t know until you do the experiment.

是的，模式也可以是代理，但同样，只有进行实验你才会知道。

So if you want to know whether a soliton or a hurricane or a thought within a cognitive system is its own agent, do the experiment.

因此，如果你想知道孤子、飓风或认知系统中的思想是否是其自身的代理人，请做实验。

See what it can do.

看看它能做什么。

1:10:43 Does it, can it learn from experience?

是吗，可以吸取经验吗？

Does it have memories?

它有记忆吗？

Does it have goal states?

它有目标状态吗？

What can it do, right?

它能做什么，对吗？

Does it have language?

它有语言吗？

So coming back to your original question, yeah, we can definitely apply this methodology to ideas and concepts and social whatevers, but you’ve got to do the experiment.

所以回到你最初的问题，是的，我们绝对可以将这种方法应用于想法、概念和社会事物，但你必须做实验。

That’s such a challenging thought experiment of thinking about memories, from the caterpillar to the butterfly as an organism.

这是一个非常具有挑战性的思考记忆的思想实验，从毛毛虫到蝴蝶作为一个有机体。

1:11:04 I think at the very basic level, intuitively, we think of organisms as hardware…

我认为在最基本的层面上，直觉上，我们将有机体视为硬件......

…And software as not possibly being able to be organisms, but…

......软件不可能成为有机体，但是......

1:11:26 …what you’re saying is that it’s all just patterns in an excitable medium, and it doesn’t really matter what the pattern is.

……你的意思是，这一切都只是可兴奋介质中的模式，模式是什么并不重要。

We need to…

我们需要……

and what the excitable medium is.

以及兴奋介质是什么。

We need to do the testing of how persistent is it?

我们需要测试一下它的持久性如何？

How goal-oriented is it?

目标导向程度如何？

And there are certain kinds of tests to do that, and you can apply that to memories.

有某些类型的测试可以做到这一点，你可以将其应用于记忆。

You can apply that to ideas.

你可以将其应用到想法中。

You can apply that to anything, really.

你真的可以将它应用到任何事情上。

I mean, you could probably think about consciousness.

我的意思是，你可能会想到意识。

You could…

你可以……

There’s really no boundary to what you can imagine.

你的想象真的没有界限。

Probably really, really wild things could be minds.

也许真正非常疯狂的东西就是思想。

Yeah.

是的。

1:12:08 Stay tuned.

敬请关注。

I mean, this is exactly what we’re doing.

我的意思是，这正是我们正在做的事情。

We’re getting progressively more and more unconventional.

我们变得越来越非传统。

I mean, so this whole distinction between software and hardware, I think it’s a super important concept to think about.

我的意思是，软件和硬件之间的整个区别，我认为这是一个需要考虑的非常重要的概念。

And yet, the way we’ve mapped it onto the world, I would like to blow that up in the following way.

然而，我们将其映射到世界的方式，我想通过以下方式将其放大。

And again, I want to point out what the practical consequences are, because this is not just, you know, fun stories that we tell each other.

我想再次指出实际后果是什么，因为这不仅仅是我们互相讲述的有趣故事。

These have really important research implications.

这些具有非常重要的研究意义。

Think about a Turing machine.

想想图灵机。

So one thing you can say is the machine’s the agent.

所以你可以说的一件事是机器是代理。

1:12:47 It has passive data, and it operates on the data, and that’s it.

它拥有被动数据，并且对数据进行操作，仅此而已。

The story of agency is the story of whatever that machine can and can’t do.

代理的故事就是机器能做什么和不能做什么的故事。

The data is passive, and it moves it around.

数据是被动的，它会四处移动。

You can tell the opposite story.

你可以讲相反的故事。

You can say, “Look, the patterns on the data are the agent.

你可以说：“看，数据上的模式就是代理。

The machine is a stigmergic scratch pad in the world of the data doing what data does.” The machine is just the consequences, the scratch pad of it working itself out.

在数据世界里，机器只是一个令人耻辱的便笺簿，做着数据的事情。”机器只是结果，它的便笺本会自行发挥作用。

And both of those stories make sense depending on what you’re trying to do.

这两个故事都有意义，具体取决于你想要做什么。

Here’s the biomedical side of things.

这是事情的生物医学方面。

So our program in bioelectrics and aging, okay?

那么我们的生物电和衰老项目，好吗？

1:13:19 One model you could have is the physical organism is the agent and the cellular collective has pattern memories, specifically what I was saying before, goals, anatomical goals.

你可以拥有的一种模型是，物理有机体是代理，细胞集体具有模式记忆，特别是我之前所说的，目标，解剖目标。

If you want to persist for 100 plus years, your cells better remember what your correct shape is and where the new cells go, right?

如果你想坚持 100 多年，你的细胞最好记住你的正确形状是什么以及新细胞去哪里，对吗？

So there are these pattern memories.

所以就有了这些模式记忆。

They exist during embryogenesis, during regeneration, during resistance to aging.

它们存在于胚胎发生期间、再生期间、抗衰老期间。

We can see them.

我们可以看到他们。

We can visualize them.

我们可以将它们形象化。

One thing you can imagine is, fine, the physical body, the cells, are the agent.

你可以想象的一件事是，好吧，身体、细胞就是媒介。

The electrical pattern memories are just data, and what might happen during aging is that the data might get degraded.

电模式存储器只是数据，老化期间可能发生的情况是数据可能会退化。

They might get fuzzy.

他们可能会变得模糊。

1:14:01 And so what we need to do is reinforce the memories, reinforce the pattern memories.

所以我们需要做的就是强化记忆，强化模式记忆。

That’s one specific research program, and we’re doing that.

这是一个具体的研究项目，我们正在这样做。

But that’s not the only research program, because the other thing you might imagine is that, what if the patterns are the agent in exactly the same sense as we think in our brains?

但这并不是唯一的研究项目，因为您可能会想到的另一件事是，如果这些模式是与我们大脑中思考的含义完全相同的代理，该怎么办？

It’s the patterns of electrophysiological computations, whatever else, that is the agent, right?

这是电生理学计算的模式，无论其他什么，这就是代理，对吧？

1:14:30 And that what they’re doing in the brain are the side effects of the patterns working themselves out.

他们在大脑中所做的事情是这些模式自行产生的副作用。

And those side effects might be to fire off some muscles and some glands and some other things.

这些副作用可能是激发一些肌肉、一些腺体和其他一些东西。

From that perspective…

从这个角度来看……

maybe what’s actually happening is, maybe the agent’s finding it harder and harder to be embodied in the physical world.

也许实际发生的情况是，也许特工发现越来越难体现在现实世界中。

Why?

为什么？

Because the cells might get less responsive.

因为细胞的反应可能会减弱。

In other words, the cells are sluggish.

换句话说，细胞反应迟缓。

The patterns are fine.

图案很好。

They’re having a harder time making the cells do what they need to do, and that maybe what you need to do is not reinforce the memories, maybe what you need to do is make the cells more responsive to them, and that is a different research agenda.

他们很难让细胞做他们需要做的事情，也许你需要做的不是强化记忆，也许你需要做的是让细胞对它们更加敏感，这是一个不同的研究议程。

So which we are also doing.

我们也在做这件事。

1:15:07 We have evidence for that as well, actually now, and we published it recently.

事实上，我们现在也有证据证明这一点，并且我们最近发布了它。

And so my point here is, when we tell these crazy sci-fi stories, the only worth to them and the only reason I’m talking about them now, and I hadn’t been…

所以我的观点是，当我们讲述这些疯狂的科幻故事时，它们的唯一价值也是我现在谈论它们的唯一原因，而我并没有……

you know, a year ago I wasn’t talking about this stuff, is because these are now actionable in terms of specific experimental research agendas that are heading to the clinic, I hope, in some of these biomedical approaches.

你知道，一年前我不是在谈论这些东西，是因为这些现在可以根据具体的实验研究议程进行操作，我希望这些生物医学方法中的一些实验研究议程将进入临床。

And so now here we can go beyond this and we can say, okay, so up until now we’ve considered…

所以现在我们可以超越这个，我们可以说，好吧，到目前为止我们已经考虑过……

What are disease states?

什么是疾病状态？

Well, we know there’s organic disease, something that’s physically broken.

嗯，我们知道存在器质性疾病，即身体上的损坏。

We can see the tissues breaking down.

我们可以看到组织破裂。

1:15:40 There’s damage in the joint, you know, where the liver is doing what, you know, we can see these things.

关节受损，你知道，肝脏在做什么，你知道，我们可以看到这些东西。

But what about disease states that are not physical states, they’re physiological states or informational states or cognitive problems?

但是，那些不是身体状态、而是生理状态、信息状态或认知问题的疾病状态呢？

So in other words, in all of these other spaces, you can start to ask, what’s a barrier in gene expression space?

换句话说，在所有这些其他空间中，您可以开始问，基因表达空间中的障碍是什么？

What’s a local minimum that traps you in physiological state space, and what is a stress pattern that keeps itself together, moves around the body, causes damage, tries to keep itself going, right?

什么是将你困在生理状态空间中的局部最小值，什么是压力模式，它使自身保持在一起，在身体周围移动，造成损害，试图保持自身运转，对吗？

What level of agency does it have?

它有什么级别的机构？

1:16:15 This suggests an entirely different set of approaches to biomedicine, and, you know, anybody who’s, let’s say, in the alternative medicine community, is probably yelling at the screen right now saying, “We’ve been saying this for hundreds of years,” and yeah, but.

这表明了一套完全不同的生物医学方法，而且，你知道，替代医学界的任何人现在都可能对着屏幕大喊，“我们已经这样说了数百年了”，是的，但是。

And I’m well aware these ideas are not new.

我很清楚这些想法并不新鲜。

What’s new is being able to now take this and make them actionable and say, “Yeah, but we can image this now.

新鲜的是现在能够接受这一点并让他们采取行动并说：“是的，但我们现在可以想象这一点。

I can now actually see the bioelectric patterns and why they go here and not there,” and we have the tools that now hopefully will get us to therapeutics.

我现在可以真正看到生物电模式以及它们为什么会出现在这里而不是那里。”我们现在拥有的工具有望帮助我们进行治疗。

So this is very actionable stuff, and it all leans on not assuming we know minds when we see them, because we don’t, and we have to do experiments.

所以这是非常可行的东西，这一切都取决于我们在看到思想时不要假设我们知道它们，因为我们不知道，而且我们必须做实验。

To return back to the software-hardware distinction, you’re saying that we can see the software is the organism and the hardware is just the scratchpad, or you could see the hardware as the organism and the software is the thing that the hardware generates, and in so doing, we can decrease the amount of importance we assign to something like the human brain, or it could be the activations, it could be the electrical signals that are the organisms, and then the brain is the scratchpad.

回到软件与硬件的区别，你说我们可以把软件看作有机体，而硬件只是暂存器，或者你可以把硬件看作有机体，而软件是硬件生成的东西，这样，我们就可以降低我们对人脑之类的东西的重视程度，或者它可以是激活，也可以是作为有机体的电信号，然后大脑就是暂存器。

And by saying scratchpad, I don’t mean it’s not important.

我说暂存器并不意味着它不重要。

1:17:30 When we get to talking about the Platonic space, we have to talk about how important the interface actually is.

当我们谈论柏拉图空间时，我们必须谈论界面实际上有多么重要。

It’s…

这是……

The scratchpad isn’t unimportant, the scratchpad is critical.

暂存器并非不重要，而是至关重要。

It’s just that my only point is that when we have these formalisms of software, of hardware, of other things, the way we map those formalisms onto the world is not obvious.

只是我唯一的观点是，当我们拥有这些软件、硬件或其他事物的形式主义时，我们将这些形式主义映射到世界上的方式并不明显。

It’s not given to us.

它不是给我们的。

We get used to certain things, right?

我们已经习惯了某些事情，对吗？

But, but who’s the hardware, who’s the software, who’s the agent and who’s the excitable medium is to be determined.

但是，谁是硬件，谁是软件，谁是代理，谁是兴奋媒介，还有待确定。

So this is a good place to talk about the increasingly radical weird ideas that you’ve been writing about.

所以这是一个谈论你一直在写的日益激进的奇怪想法的好地方。

1:18:02 You’ve mentioned it a few times, the Platonic space.

你已经多次提到过柏拉图空间。

So there’s this “Ingressing Minds” paper where you described the Platonic space.

因此，在这篇“Ingressing Minds”论文中，您描述了柏拉图空间。

You mentioned there’s an asynchronous conference…

你提到有一个异步会议......

…

……

Happening, which is a fascinating concept because it’s asynchronous.

发生，这是一个有趣的概念，因为它是异步的。

People are just contributing asynchronously.

人们只是异步贡献。

So what happened was this crazy notion, which I’ll describe momentarily, I have given a couple talks on it.

所以发生了这个疯狂的想法，我将立即描述它，我已经就此进行了几次演讲。

1:18:30 I then found a couple papers in the machine learning community called the Platonic Representation Hypothesis, and I said, “That’s pretty cool.

然后我在机器学习社区找到了几篇名为柏拉图表示假说的论文，我说：“这非常酷。

These guys are climbing up to the same point where I’m getting at it from biology and philosophy and whatever.

这些人正在攀爬到我从生物学和哲学等方面得到的相同点。

They’re getting there from computer science and machine learning.” We’ll take a couple hours, I’ll give a talk, they’ll give a talk, we’ll talk about it.

他们通过计算机科学和机器学习实现了这一目标。”我们会花几个小时，我会发表演讲，他们也会发表演讲，我们会讨论这个问题。

I thought there were going to be three talks at this thing.

我以为这件事要进行三场会谈。

1:18:57 Once I started reaching out to people for this, everybody sort of said, “You know, I know somebody who’s really into this stuff, but they never talk about it because there’s no audience for this,” so I reached out to them.

一旦我开始为此联系人们，每个人都会说，“你知道，我知道有人真正喜欢这个东西，但他们从不谈论它，因为没有观众，”所以我联系了他们。

And then they said, “Yeah.

然后他们说：“是的。

Oh, yeah, I know this mathematician,” or, “I know this, you know, economist, whatever, who has these ideas and there’s nowhere we can have her talk about them.” So I got this whole list and it became completely obvious that we can’t do this in a normal…

哦，是的，我认识这位数学家，”或者，“我知道这个，你知道，经济学家，无论如何，谁有这些想法，但我们没有地方可以让她谈论它们。”所以我得到了整个清单，很明显我们不能以正常的方式做到这一点......

You know, we are now booked up through December, so every week in our center, somebody gives a talk.

您知道，我们现在 12 月份的预约都已满，所以每周都会有人在我们中心发表演讲。

We kind of discuss it.

我们有点讨论它。

It all goes on this thing.

一切都在这件事上进行。

1:19:29 I’ll give you a link to it, and then there’s a huge running discussion after that, and then in the end, we’re all going to get together for an actual real-time discussion section and talk about it.

我会给你一个链接，然后会有一个大规模的持续讨论，最后，我们将聚在一起进行一个实际的实时讨论部分并讨论它。

But there’s going to be probably 15 or so talks about this from all kinds of disciplines.

但可能会有 15 个左右的来自各个学科的讨论来讨论这个问题。

It’s blown up in a way that I didn’t realize how much undercurrent of these ideas had already existed that were ready, like now, now is the time, and I think…

它以一种我没有意识到这些想法的暗流已经存在多少的方式被炸毁，这些想法已经准备好了，就像现在，现在是时候了，我想……

This is…

这是……

Like I’ve been thinking about these things for, I don’t know, 30-plus years.

好像我已经思考这些事情三十多年了，我不知道。

I never talked about them before because they weren’t actionable before.

我以前从未谈论过它们，因为它们以前不可行。

There wasn’t a way to actually make empirical progress with this now.

现在还没有办法在这方面真正取得实证进展。

1:20:07 You know, this is something that Pythagoras and Plato and probably many people before them talked about, but now we’re to the point where we can actually do experiments and they’re making a difference in our research program.

你知道，这是毕达哥拉斯和柏拉图以及他们之前的许多人谈论过的事情，但现在我们已经到了可以实际做实验的地步，他们正在改变我们的研究计划。

You can just look it up, “Platonic Space Conference.” There’s a bunch of different fascinating talks.

你可以查一下，“柏拉图式太空会议”。有很多不同的有趣的演讲。

1:20:19 Yours first on the patterns of forms and behavior, beyond emergence, then radical Platonism and radical empiricism from Joel Dietz, and Patterns And Explanatory Gaps In Psychotherapy, Does God Play Dice?

您首先讨论了形式和行为的模式，超越了涌现，然后是乔尔·迪茨的激进柏拉图主义和激进经验主义，以及心理治疗中的模式和解释差距，上帝玩骰子吗？

from Alexey Tolchinsky and so on.

来自阿列克谢·托尔钦斯基等。

So, let’s talk about it.

那么，我们来谈谈吧。

What is it?

它是什么？

And it’s fascinating that the origins of some of these ideas are connected to ML people thinking about representation space.

令人着迷的是，其中一些想法的起源与机器学习人员对表示空间的思考有关。

Yeah.

是的。

1:20:58 The first thing I want to say is that while I’m currently calling it the Platonic space, I am in no way trying to stick close to the things that Plato actually thought about.

我想说的第一件事是，虽然我目前将其称为柏拉图空间，但我绝不试图坚持柏拉图实际思考的事情。

In fact, to whatever extent we even know what that is, I think I depart from that in quite…

事实上，无论我们在多大程度上知道那是什么，我想我都偏离了这一点……

in some ways, and I’m going to have to change the name at some point.

在某些方面，我将不得不在某个时候更改名字。

The reason I’m using the name now is because I wanted to be clear about a particular connection to mathematics, which a lot of mathematicians would call themselves Platonists because what they think they’re doing is discovering…

我现在使用这个名字的原因是因为我想弄清楚与数学的特殊联系，很多数学家会称自己为柏拉图主义者，因为他们认为自己正在做的是发现……

not inventing as a human construction, but discovering a structured, ordered space of truths.

不是人类的发明创造，而是发现一个结构化的、有序的真理空间。

Let’s put it this way.

这么说吧。

1:21:38 In biology, as in physics, there’s something very curious that happens that if you keep asking why, then something interesting goes on.

在生物学中，就像在物理学中一样，会发生一些非常奇怪的事情，如果你不断问为什么，就会发生一些有趣的事情。

Let’s…

让我们…

Well, I’ll give you two examples.

好吧，我给你举两个例子。

First of all, imagine cicadas.

首先，想象一下蝉。

So the cicadas come out at 13 years and 17 years, okay?

那么蝉13岁和17岁就出来了，好吗？

And so if you’re a biologist and you say, “So why is that?” And then you get this explanation for, well, it’s because they’re trying to be off-cycle from their predators.

因此，如果你是一名生物学家，你会说：“那这是为什么呢？”然后你会得到这样的解释：嗯，这是因为它们试图摆脱捕食者的束缚。

Because if it was 12 years, then every two years, every three years, every four years, every six years, a predator would eat you when you come out, right?

因为如果是12年，那么每两年、每三年、每四年、每六年，当你出来时，掠食者就会吃掉你，对吗？

So, and you say, “Okay, okay, cool.

所以，你说：“好吧，好吧，酷。

That makes sense.

这是有道理的。

What’s special about 13 and 17?” Oh, they’re prime.

13号和17号有什么特别之处？”哦，他们是主要的。

Uh-huh.

嗯嗯。

And why are they prime?

为什么他们是主要的？

1:22:18 Well, now you’re in the math department.

好吧，现在你在数学系。

You’re no longer in the biology department.

你不再在生物系了。

You’re no longer in the physics department.

你不再是物理系的人了。

You’re now…

你现在……

you’re now in the math department to understand why the distribution of primes is what it is.

你现在在数学系，要理解为什么素数的分布是这样的。

Another example, and I’m not a physicist, but what I see is every time you talk to a physicist and you say, “Hey, why do the, you know, leptons do this or that, or the fermions are doing whatever?” Eventually, the answer is, oh, because there’s this mathematical, you know, this SU(8) group or whatever the heck it is, and it has certain symmetries in these certain structures.

另一个例子，我不是物理学家，但我看到的是每次你和物理学家交谈时你都会说，“嘿，为什么轻子会这样做或那样做，或者费米子会做任何事情？”最终，答案是，哦，因为有这个数学，你知道，这个 SU(8) 群或者不管它是什么，并且它在这些特定的结构中具有一定的对称性。

Yeah, great.

是的，太棒了。

Once again, you’re in the math department.

再一次，你在数学系。

So something interesting happens is that there are facts that you come across, many of them are very surprising.

所以有趣的事情发生了，你会遇到一些事实，其中许多都非常令人惊讶。

1:22:55 You don’t get to design them.

你不需要设计它们。

You get more out than you put in, in a certain way, because you make very minimal assumptions.

在某种程度上，你得到的比你投入的更多，因为你做了非常少的假设。

And then certain facts are thrust upon you.

然后某些事实就强加给你了。

For example, the value of Feigenbaum’s constant, the value of natural logarithm E.

例如费根鲍姆常数的值、自然对数E的值。

These things you sort of discover, right?

这些都是你发现的，对吧？

And the salient fact is this, if those facts were different, then biology and physics would be different, right?

突出的事实是，如果这些事实不同，那么生物学和物理学就会不同，对吗？

So they matter, they impact instructively, functionally, they impact the physical world.

所以它们很重要，它们具有指导性、功能性的影响，它们影响着物质世界。

If the distribution of primes was something else, well then the cicadas would have been coming out at different times.

如果素数的分布是别的什么，那么蝉就会在不同的时间出现。

But the reverse isn’t true.

但反之则不然。

What I mean is, there is nothing you can do in the physical world to change E, as far as I know, to change E or to change Feigenbaum’s constant.

我的意思是，据我所知，在物理世界中你无法改变 E 或费根鲍姆常数。

1:23:40 You could have swapped out all the constants at the Big Bang, right?

你可以交换大爆炸时的所有常数，对吗？

You can change all the different things, you are not going to change those things.

你可以改变所有不同的事情，但你不会改变那些事情。

So this, I think Plato and Pythagoras understood very clearly, that there is a set of truths which impact the physical world, but they themselves are not defined by and determined by what happens in the physical world.

因此，我认为柏拉图和毕达哥拉斯非常清楚地理解，存在一组影响物理世界的真理，但它们本身并不是由物理世界中发生的事情定义和决定的。

You can’t change them by things you do in the physical world, right?

你无法通过在物质世界中所做的事情来改变它们，对吗？

And so I’ll make a couple claims about that.

因此，我将对此提出一些主张。

One claim is, I think we call physics those things that are constrained by those patterns.

一种说法是，我认为我们将受这些模式约束的事物称为物理学。

When you say, “Hey, why is this the way it is?” Ah, it’s because this is how symmetries or topology or whatever.

当你说：“嘿，为什么会这样？”啊，这是因为这就是对称性或拓扑学之类的东西。

Biology are the things that are enabled by those.

生物学是由这些因素促成的事物。

They’re free lunches.

他们是免费的午餐。

They’re…

他们是……

1:24:24 Biology exploits these kinds of truths, and it really enables biology and evolution to do amazing things without having to pay for it.

生物学利用了这些真理，它确实使生物学和进化论能够做出令人惊奇的事情，而无需为此付出代价。

I think there’s a lot of free lunches going on here.

我认为这里有很多免费的午餐。

And so I show you a xenobot or an anthropod, and I say, “Hey, look, here are some amazing things they’re doing,” that tissue has never done before in their history.

所以我向你展示了一个异种机器人或节肢动物，然后我说，“嘿，看，它们正在做一些令人惊奇的事情”，这些组织在它们的历史上从未做过。

You say, first of all, where did that come from?

你说，首先，它从哪里来？

And when did we pay the computational cost for it?

我们什么时候为此支付计算成本？

Because we know when we pay the computational cost to design a frog or a human, it was for the eons that the genome was bashing against the environment getting selected, right?

因为我们知道，当我们付出计算成本来设计青蛙或人类时，基因组在亿万年里一直在对抗环境的选择，对吗？

So you pay the computational cost of that.

所以你要付出计算成本。

There’s never been any anthropods.

从来没有任何节肢动物。

There’s never been any xenobots.

从来没有任何异种机器人。

1:25:02 When do we pay the computational cost for designing kinematic self-replication and, you know, all these things that they’re able to do?

我们什么时候为设计运动学自我复制以及它们能够做的所有这些事情付出计算成本？

So there’s two things people say.

所以人们会说两件事。

One is, “Well, it’s sort of…

其中之一是，“嗯，这有点......

you got it at the same time that they were being selected to be good humans and good frogs.” Now, the problem with that is it kind of undermines the point of evolution.

你在他们被选为好人类和好青蛙的同时就明白了。”现在的问题是它有点破坏了进化论的观点。

The point of evolutionary theory was to have a very tight specificity between how you are now and the history of selection that got you here, right?

进化论的要点是，你现在的样子和让你来到这里的选择历史之间有一个非常严格的特异性，对吗？

The history of environments that got you to this point.

让您走到这一步的环境历史。

If you say, “Yeah, okay, so this is what your environmental history was.

如果你说：“是的，好吧，这就是你的环境历史。

And by the way, you got something completely different.”

顺便说一句，你得到了完全不同的东西。”

1:25:37 You got these other skills that you didn’t know about, that’s really strange, right?

你还拥有这些你不知道的技能，这真的很奇怪，对吧？

And so then what people say is, “Well, it’s emergent.” And I say, “What’s that?

所以人们会说，“嗯，这是紧急情况。”我说：“那是什么？

What does that mean?” And they say…

那是什么意思？他们说……

besides the fact that you got surprised, right?

除了你感到惊讶之外，对吧？

Emergence often just means I didn’t see it coming.

出现往往只意味着我没有预见到它的到来。

You know, there was something happened.

你知道，发生了一些事情。

I didn’t know that was going to happen.

我不知道会发生这种事。

So what does it mean that it’s emergent?

那么它的出现意味着什么呢？

And people say, “Well,” and there are many emergent things like this.

人们会说，“好吧”，这样的突发事件有很多。

For example, the fact that gene regulatory networks can do associative learning.

例如，基因调控网络可以进行联想学习。

Like, that’s amazing, and you don’t need evolution for that.

就像，这太神奇了，而且你不需要进化来做到这一点。

Even random genetic regulatory networks can do associative learning.

即使是随机的基因调控网络也可以进行联想学习。

1:26:07 I say, “Why does that happen?” And they say, “Well, it’s just a fact that holds in the world.

我说：“为什么会这样？”他们说：“嗯，这只是世界上存在的事实。

Just a fact that holds.” So now you have an option, and you can go one of two ways.

这只是一个事实。”所以现在你有一个选择，你可以选择两种方法之一。

You can either say, “Okay, look, I like my sparse ontology.

你可以说：“好吧，看，我喜欢我的稀疏本体。

I don’t want to think about weird platonic spaces.

我不想思考奇怪的柏拉图式空间。

I’m a physicalist.

我是一个物理主义者。

I want the physical world, nothing more.” So what we’re going to do is when we come across these crazy things that are very specific, like, you know, anthropods have four specific behaviors that they switch around.

我想要物质世界，仅此而已。”所以我们要做的是，当我们遇到这些非常具体的疯狂的事情时，比如，你知道，节肢动物有四种特定的行为，它们会改变。

Why four?

为什么是四个？

Why not 12?

为什么不是12个？

Why not 100?

为什么不是100？

Like four, why four?

就像四个，为什么是四个？

1:26:36 When we come across these things, just like when we come across the value of E or Feigenbaum’s number or whatever, what we’re going to do is we’re going to write it down in our big book of emergence.

当我们遇到这些事情时，就像当我们遇到 E 的值或费根鲍姆数或其他什么时，我们要做的就是把它写在我们的涌现大书中。

And that’s it.

就是这样。

We’re just going to have to live with it.

我们只能忍受它。

This is what happens.

这就是发生的事情。

We’re just…

我们只是……

You know, there’s some cool surprises.

你知道，有一些很酷的惊喜。

You know, when we come across them, we’re going to write them down.

你知道，当我们遇到它们时，我们会把它们写下来。

Great.

伟大的。

It’s a random grab bag of stuff.

这是一个随机抓包的东西。

And when we come across them, we’ll write them down.

当我们遇到它们时，我们会把它们写下来。

That’s one…

那是一个……

the upside is you get to be a physicalist, and you get to keep your sparse ontology.

好处是你可以成为一名物理主义者，并且可以保留稀疏的本体论。

1:27:02 The downside is I find it incredibly pessimistic and mysterian because you’re basically then just willing to make a catalog of these amazing patterns.

缺点是我发现它非常悲观和神秘，因为你基本上只是愿意为这些令人惊奇的模式制作一个目录。

Why not, instead, and this is why I started with this Platonic terminology, why not do what the mathematicians already do?

为什么不呢，这就是为什么我从柏拉图式的术语开始，为什么不做数学家已经做的事情呢？

A huge number of them say, “We are going to make the same optimistic assumption that science makes, that there’s an underlying structure to that latent space.” It’s not, like, a random grab bag of stuff.

他们中的很多人说，“我们将做出与科学相同的乐观假设，即潜在空间有一个潜在的结构。”它不像是随机抓包的东西。

There’s a space to it where these patterns come from, and by studying them systematically, we can get from one to another.

这些模式的来源有一个空间，通过系统地研究它们，我们可以从一种模式转变为另一种模式。

We can map out the space.

我们可以绘制出空间。

We can find out the relationships between them.

我们可以找出它们之间的关系。

1:27:43 We can get an idea of what’s in that space, and we’re not going to assume that it’s just random.

我们可以了解该空间中的内容，并且我们不会假设它只是随机的。

We’re going to assume there’s some kind of structure to it.

我们假设它有某种结构。

And you’ll see all kinds of people, I mean, you know, well-known mathematicians that talk about this stuff.

你会看到各种各样的人，我的意思是，你知道，著名的数学家谈论这些东西。

You know, Penrose and lots of other people who will say that, “Yeah, there’s another space physically, and it has spatial structure.

你知道，彭罗斯和许多其他人会说，“是的，物理上还有另一个空间，它有空间结构。

It has components to it and so on.

它有其组件等等。

We can traverse that space in various ways.” And then there’s the physical space.

我们可以通过各种方式穿越那个空间。”然后是物理空间。

So I find that much more appealing because it suggests a research program, which we are now undergoing in our lab.

所以我发现这更有吸引力，因为它提出了一个研究计划，我们现在正在实验室进行该计划。

1:28:14 The research program is everything that we make, cells, embryos, robots, biobots, language models, simple machines, all of it, they are interfaces.

研究项目是我们制造的一切，细胞、胚胎、机器人、生物机器人、语言模型、简单机器，所有这些，它们都是接口。

All physical things are interfaces to these patterns.

所有物理事物都是这些模式的接口。

You build an interface, some of those patterns are going to come through that interface.

您构建一个界面，其中一些模式将通过该界面出现。

Depending on what you build, some patterns versus others are going to come through.

根据您构建的内容，将会出现一些模式与其他模式。

The research program is mapping out that relationship between the physical pointers that we make, and the patterns that come through it, right?

该研究计划正在绘制我们制作的物理指针与通过它产生的模式之间的关系，对吗？

Understanding what is the structure of that space, what exists in that space, and what do I need to make physically to make certain patterns come through?

了解该空间的结构是什么，该空间中存在什么，以及我需要在物理上做什么才能使某些模式得以体现？

1:28:50 Now, when I say patterns, we have to ask, “What kinds of things live in that space?” Well, the mathematicians will tell you, “We already know.

现在，当我说模式时，我们必须问：“那个空间里生活着什么样的东西？”好吧，数学家会告诉你，“我们已经知道了。

We have a whole list of objects.

我们有一个完整的对象列表。

You know, the amplituhedrons and all this crazy stuff that lives in that space.” Yeah, I think that’s one layer of stuff that lives in that space, but I think those patterns are the lower agency kinds of things that are basically studied by mathematicians.

你知道，振幅面体和所有这些生活在那个空间里的疯狂的东西。”是的，我认为这是存在于那个空间中的一层东西，但我认为这些模式是数学家基本上研究的较低代理类型的东西。

What also lives in that space are much more active, more complex, higher agency patterns that we recognize as kinds of minds, that behavioral scientists would look at that pattern and say, “Well, I know what that is.

在这个空间中还存在着更活跃、更复杂、更高级的代理模式，我们将其视为一种思维，行为科学家会研究这种模式并说：“好吧，我知道那是什么。

That’s the competency for delayed gratification or problem-solving of certain kinds,” or whatever.

这就是延迟满足或解决某些问题的能力，”或者其他什么。

1:29:29 And so, what I end up with right now is a model in which that latent space contains things that come through physical objects, so simple, simple patterns, right?

所以，我现在最终得到的是一个模型，其中潜在空间包含通过物理对象而来的东西，非常简单的模式，对吗？

So facts about triangles and Fibonacci patterns and fractals and things like that.

关于三角形、斐波那契模式和分形以及类似事物的事实。

But also, if you make more complex interfaces such as biologicals, and importantly, not just biologicals, but let’s say cells and embryos and tissues, what you will then pull down is much more complex patterns that we say, “Ah, that’s a mind.

而且，如果你制作更复杂的界面，例如生物制品，重要的是，不仅仅是生物制品，还包括细胞、胚胎和组织，那么你将得到更复杂的模式，我们会说，“啊，那是一个思想。

That’s a human mind,” or, “That’s a snake mind,” or whatever.

那是人类的思想，”或者，“那是蛇的思想，”或者其他什么。

1:30:02 So I think the mind-brain relationship is exactly the kind of thing that the math-physics relationship is, that in some very interesting way, there are truths of mathematics that become embodied, and they kind of haunt physical objects, right, in a very specific functional way.

所以我认为心灵与大脑的关系正是数学与物理关系的一种，以某种非常有趣的方式，数学的真理被具体化，并且它们以一种非常具体的功能方式困扰着物理对象，对吧。

And in the exact same way, there are other patterns that are much more complex, higher agency patterns that basically inform living things that we see as obvious embodied minds.

以完全相同的方式，还有其他更复杂、更高级的代理模式，它们基本上告知我们视为明显体现的思想的生物。

Okay, given how weird and complicated what you’re describing is, we’ll talk about it more, but you gotta ELI5 the basics to a person who’s never seen this.

好吧，考虑到你所描述的内容是多么奇怪和复杂，我们会更多地讨论它，但你必须向从未见过这个的人 ELI5 基础知识。

1:30:35 So again, you mentioned things like pointers.

你再次提到了诸如指针之类的东西。

So the physical object themselves or the brain is a pointer to that platonic space.

因此，物理对象本身或大脑是指向柏拉图空间的指针。

What is in that platonic space?

那个柏拉图式的空间里有什么？

What is the platonic space?

什么是柏拉图空间？

What is the embodiment?

体现是什么？

What is the pointer?

指针是什么？

Yeah, okay.

是啊，好吧。

1:31:05 Let’s try it this way.

我们这样试试吧。

There are certain facts of mathematics.

有一些数学事实。

So the distribution of prime numbers, right, that if you map them out, they make these nice spirals.

所以素数的分布，对吧，如果你把它们映射出来，它们就会形成这些漂亮的螺旋。

And there’s an image that I often show, which is a very particular kind of fractal.

我经常展示一张图像，这是一种非常特殊的分形。

1:31:22 And that fractal is the Hally map, which is, it’s pretty awesome that it actually looks very organic.

这个分形就是哈利图，也就是说，它看起来非常有机，非常棒。

It looks very biological.

它看起来非常生物化。

So if you look at that thing, that image, which has very specific complex structure, it’s a map of a very compact mathematical object.

因此，如果你看那个东西，那个图像，它具有非常具体的复杂结构，它是一个非常紧凑的数学对象的地图。

That formula is like, you know, Z cubed plus seven.

这个公式就像 Z 的立方加七。

It’s something like that.

是这样的。

That’s it.

就是这样。

So now you look at that structure and you say, “Where does that actually come from?” It’s definitely not packed into the Z cubed plus seven.

现在你看看这个结构，你会说：“它实际上来自哪里？”它绝对不包含在 Z 的立方加七中。

It’s not, there’s not enough bits in that to give you all of that.

事实并非如此，其中没有足够的位来为您提供所有这些。

There’s no fact of physics that determines this.

没有任何物理事实可以决定这一点。

There’s no evolutionary history.

没有进化史。

It’s not like we selected this based on some, you know, from a larger set over time.

这并不是说我们是根据随着时间的推移从更大的集合中选择的一些内容。

Where does this come from?

这是从哪里来的？

1:32:01 Or the fact that…

或者事实是……

Think about the way that biology exploits these things.

想想生物学利用这些东西的方式。

Imagine a world in which the highest fitness belonged to a certain kind of triangle, right?

想象一个世界，其中最高的适应度属于某种三角形，对吧？

So evolution cranks a bunch of generations and it gets the first angle right, then cranks a bunch more generations, gets a second angle right.

因此，进化推动了许多代，并获得了正确的第一个角度，然后又推动了更多代，获得了正确的第二个角度。

Now there’s something amazing that happens.

现在发生了一些令人惊奇的事情。

It doesn’t need to look for the third angle because you already know.

它不需要寻找第三个角度，因为你已经知道了。

If you know two, you get this magical free gift from geometry that says, “Well, I already know what the third one should be.” You don’t have to go look for it.

如果你知道两个，你就会从几何学中得到这份神奇的免费礼物，它说：“好吧，我已经知道第三个应该是什么了。”你不必去寻找它。

1:32:29 Or as evolution, if you invent a voltage-gated ion channel, which is basically a transistor, right, and you can make a logic gate, then all the truth tables and the fact that NAND is special and all these other things, you don’t have to evolve those things.

或者作为进化，如果你发明了一个电压门控离子通道，它基本上是一个晶体管，对吧，你可以制作一个逻辑门，那么所有的真值表和 NAND 是特殊的事实以及所有其他东西，你不必进化这些东西。

You get those for free.

您可以免费获得这些。

You inherit those.

你继承了那些。

Where do all those things live?

所有这些东西都住在哪里？

These mathematical truths that you come across that you don’t have any choice about.

你遇到的这些数学真理是你别无选择的。

You know, once you’ve committed to certain axioms, there’s a whole bunch of other stuff that is now just what it is.

你知道，一旦你信守了某些公理，还有一大堆其他的东西现在就这样了。

And so what I’m saying is, and this is what Pythagoras was saying, I think, that there is a whole space of these kinds of truths.

所以我想说的是，我认为这就是毕达哥拉斯所说的，存在着一个充满此类真理的空间。

1:33:04 Now, he was focused on mathematical ones, but he was embodying them in music and in geometry and in things like that.

现在，他专注于数学问题，但他将它们体现在音乐、几何和类似的事物中。

There are the space of patterns and they make a difference in the physical world, to machines, to sound, to things like that.

模式的空间存在，它们对物理世界、机器、声音等事物产生影响。

I’m extending it, and what I’m saying is, yeah, and so far we’ve only been looking at the low agency inhabitants of that world.

我正在扩展它，我想说的是，是的，到目前为止我们只关注了那个世界的低代理居民。

There are other patterns that we would recognize as kinds of minds, and that you don’t see them in this space until there’s an interface, until there’s a way for them to come through the physical world.

还有其他一些模式，我们会认为它们是思想的种类，并且在这个空间中你看不到它们，直到有一个界面，直到有一种方式让它们穿过物理世界。

That interface, the same way that you have to make a triangular object before you can actually see the rule of what you’re going to gain, right?

这个界面，就像你必须先制作一个三角形物体，然后才能真正看到你将获得的东西的规则一样，对吗？

1:33:45 Out of the rules of geometry and whatever.

脱离几何规则等等。

Or you have to actually do the computation on the fractal before you actually see that pattern.

或者，在真正看到该模式之前，您必须实际对分形进行计算。

If you want to see some of those minds, you have to build an interface, right?

如果你想看到其中一些想法，你必须构建一个界面，对吧？

At least if you’re going to interact with them in the physical world, the way we normally do science.

至少如果你要在物理世界中与它们互动，就像我们通常进行科学研究的方式一样。

As Darwin said, “Mathematicians have their own new sense, like a different sense than the rest of us.” And so that’s right.

正如达尔文所说：“数学家有他们自己的新感觉，就像与我们其他人不同的感觉。”没错。

You know, mathematicians can perhaps interact with these patterns directly in that space.

你知道，数学家也许可以在那个空间中直接与这些模式进行交互。

But for the rest of us, we have to make interfaces.

但对于我们其他人来说，我们必须制作界面。

1:34:13 And when we make interfaces, which might be cells or robots, you know, embryos or whatever, what we are pulling down are minds that are fundamentally not produced by physics.

当我们制造界面时，它可能是细胞或机器人，你知道，胚胎或其他什么东西，我们所拉下的是基本上不是由物理学产生的思想。

So I don’t believe that—I don’t know if we’re going to get into the whole consciousness thing—but I don’t believe that we create consciousness, whether we make babies or whether we make robots.

所以我不相信——我不知道我们是否会进入整个意识领域——但我不相信我们创造了意识，无论我们制造婴儿还是制造机器人。

Nobody’s creating consciousness.

没有人创造意识。

What you create is an interface, a physical interface through which specific patterns, which we call kinds of minds, are going to ingress, right?

你创建的是一个界面，一个物理界面，通过它特定的模式，我们称之为各种思想，将进入，对吧？

And consciousness is what it looks like from that direction looking out into the world.

意识就是从那个方向看世界的样子。

It’s what we call the view from the perspective of the platonic patterns.

这就是我们所说的柏拉图模式视角的观点。

Just to clarify, what you’re saying is a pretty radical idea here.

只是为了澄清一下，你所说的是一个非常激进的想法。

1:34:53 So if there’s a mapping from mathematics to physics, okay, that’s understandable, intuitive as you’ve described.

因此，如果存在从数学到物理的映射，那么，正如您所描述的那样，这是可以理解的、直观的。

But what you’re suggesting is there’s a mapping from some kind of abstract mind object to an embodied brain that we think of as a mind— —as fellow humans.

但你的意思是，存在着从某种抽象思维对象到我们认为是人类同胞的思维的具体大脑的映射。

What is that?

那是什么？

What exactly…

到底是什么……

‘Cause you said interface.

因为你说的是接口。

You’ve also said pointer.

你也说了指针。

So the brain, and I think you said somewhere, a thin interface.

所以大脑，我想你在某个地方说过，一个薄接口。

A thin client.

瘦客户端。

1:35:37 Yeah.

是的。

The brain— The brain, a brain is a thin client.

大脑——大脑，大脑是一个瘦客户端。

Yeah.

是的。

Thin client.

瘦客户端。

1:35:40 Okay.

好的。

So you’re…

所以你是……

A brain is a thin client to this other world.

大脑是另一个世界的瘦客户端。

Can you just lay out very clearly how radical the idea is?

您能非常清楚地说明这个想法有多激进吗？

Because you’re kind of dancing around.

因为你有点在跳舞。

I think you could also point to Donald Hoffman and who speaks of an interface to a world.

我想你也可以提到唐纳德·霍夫曼（Donald Hoffman），他谈到了与世界的界面。

So we only interact with the, quote unquote, real world through an interface.

因此，我们只能通过界面与现实世界进行交互。

What is the connection here?

这里面有什么联系呢？

Okay, a couple of things.

好吧，有几件事。

1:36:11 First of all, when you said it makes sense for physics, I want to show that it’s not as simple as it sounds.

首先，当你说这对物理学有意义时，我想表明它并不像听起来那么简单。

Because what it means is that even in Newton’s boring, sort of classical universe, long before quantum anything, Newton’s world, physicalism was already dead in Newton’s world.

因为这意味着，即使在牛顿无聊的经典宇宙中，早在量子出现之前，牛顿的世界里，物理主义就已经在牛顿的世界中消亡了。

I mean, think about what that means.

我的意思是，想想这意味着什么。

This is, this is nuts.

这，这太疯狂了。

Because already he knew perfectly well…

因为他已经很清楚了……

I mean, Pythagoras and Plato knew that even in a totally classical, deterministic world, already you have the ingression of information that determines what happens and what’s possible and what’s not possible in that world from a space that is itself not physical.

我的意思是，毕达哥拉斯和柏拉图知道，即使在一个完全经典的、确定性的世界中，也已经有信息从一个本身非物理的空间进入，决定了那个世界中会发生什么、什么是可能的、什么是不可能的。

In other words, it’s something like the natural logarithm E, right?

换句话说，它类似于自然对数E，对吧？

1:36:57 Nothing in Newton’s world is set to the value of E.

牛顿的世界中没有任何东西被设定为 E 的值。

There is nothing you could do to set the value of E in that world.

在那个世界中你无法设置 E 的值。

And yet, the fact that it was that and not something else governed all sorts of properties of things that happened.

然而，事实上，正是它而不是其他东西决定了所发生事件的各种属性。

That classical world was already haunted by patterns from outside that world.

那个古典世界已经被那个世界之外的模式所困扰。

This should be like…

这应该是这样的……

This is wild.

这太疯狂了。

This is not saying that, “Okay, everything was cool.

这并不是说，“好吧，一切都很酷。

Physicalism was great up until, you know, maybe we got quantum interfaces or we got consciousness or whatever.

物理主义一直很伟大，直到我们有了量子接口或者意识等等。

But originally it was fine.” No, this is saying that that worldview was already impossible really, since…

不过本来还好。”不，这是说那个世界观真的已经不可能了，因为……

So from a very long time ago, we already knew that there are non-physical properties that matter in the physical world.

因此，从很久以前，我们就已经知道物理世界中存在一些重要的非物理属性。

This is the chicken or, or the egg question.

这是先有鸡还是先有蛋的问题。

1:37:42 You’re saying Newton’s laws are creating the physical world?

你是说牛顿定律正在创造物理世界？

That is a very deep follow-on question that we will come back to in a minute.

这是一个非常深刻的后续问题，我们稍后会再讨论。

1:37:51 All I was saying about Newton is that you don’t need quantum anything.

关于牛顿，我想说的是，你不需要量子任何东西。

You don’t need to think about consciousness.

你不需要考虑意识。

You already, long before you get to any of that, as Pythagoras, I think, knew, already we have the idea that this physical world is being strongly impacted by truths that do not live in the physical world.

我认为，早在你到达这些之前，你就已经知道，正如毕达哥拉斯所知道的那样，我们已经知道这个物质世界正在受到不存在于物质世界中的真理的强烈影响。

And when I say…

当我说……

Wait.

等等。

1:38:18 Which truths are we referring to?

我们指的是哪些真理？

Are we talking about Newton’s laws, like mathematical equations, or…

我们是在谈论牛顿定律，比如数学方程，还是……

No, no.

不，不。

1:38:23 Mathematical facts.

数学事实。

So, for example, the actual value of E or…

因此，例如，E 的实际值或......

Oh, like very primitive mathematical facts.

哦，就像非常原始的数学事实。

Yeah, yeah.

是啊是啊。

1:38:29 I mean, some of them are…

我的意思是，其中一些是……

I mean, if you ask Don Hoffman, there’s this amplituhedron thing that is a set of mathematical objects that determines all the scattering amplitudes of the particles and whatever.

我的意思是，如果你问唐·霍夫曼，这个振幅面体是一组数学对象，它决定了粒子的所有散射振幅等等。

They don’t have to be simple.

它们不必很简单。

I mean, the old ones were simple.

我的意思是，旧的很简单。

Now they’re like crazy.

现在他们就像疯了一样。

I can’t imagine this amplituhedron thing, but maybe they can.

我无法想象这个幅面体的东西，但也许他们可以。

But all of these are mathematical structures that explain and determine facts about the physical world, right?

但所有这些都是解释和确定物理世界事实的数学结构，对吗？

If you ask physicists, “Hey, why this many of this type of particle?” “Ah, because this mathematical thing has these symmetries.” That’s why.

如果你问物理学家，“嘿，为什么有这么多这种类型的粒子？” “啊，因为这个数学东西有这些对称性。”这就是原因。

So Newton is discovering these things.

所以牛顿正在发现这些东西。

1:39:00 They’re not…

他们不是……

He’s not inventing.

他不是在发明。

This is very controversial, right?

这是非常有争议的，对吧？

1:39:04 And there are, of course, physicists and mathematicians who disagree with what I’m saying, for sure.

当然，肯定有物理学家和数学家不同意我所说的。

But what I’m leaning on is simply this: I don’t know of anything you can do in the physical world.

但我所依赖的只是：我不知道你在物质世界中能做什么。

You’re around at the Big Bang, you get to set all the constants.

你身处大爆炸之中，你可以设置所有的常数。

Set physics however you want.

按照您想要的方式设置物理效果。

Can you change E?

可以改E吗？

Can you change Feigenbaum’s constant?

你能改变费根鲍姆常数吗？

I don’t think you can.

我认为你不能。

Is that an obvious statement?

这是一个显而易见的说法吗？

1:39:28 I don’t even know what it means to change the parameters at the start of the Big Bang.

我什至不知道在大爆炸开始时改变参数意味着什么。

So physicists do this.

所以物理学家这样做。

1:39:34 They’ll say, “Okay, you know, if we made the ratio between gravitation and the electromagnetic force different, would we have matter?

他们会说：“好吧，你知道，如果我们改变万有引力和电磁力之间的比例，我们会有物质吗？

How many dimensions would we have?

我们有多少个维度？

Would there be inflation?

会出现通货膨胀吗？

Would there be this or that?” Right?

会有这个或那个吗？”正确的？

You can imagine playing with it.

你可以想象玩它。

There are however many unitless constants of physics.

然而，存在许多无单位的物理常数。

These are the kind of knobs on the universe that could, in theory, be different, and then you’d have different physics, you’d have different physical properties.

从理论上讲，宇宙中的这些旋钮可能会有所不同，然后你就会有不同的物理学，你就会有不同的物理特性。

You’re saying that’s not gonna change the axiomatic systems that mathematics has?

你是说这不会改变数学的公理系统？

What I’m not saying is that every alien everywhere is going to have the exact same math that we have.

我并不是说世界各地的每个外星人都会有与我们完全相同的数学。

1:40:10 That’s not what I’m claiming, although, maybe.

不过，也许这不是我所说的。

But that’s not what I’m claiming.

但这不是我所主张的。

What I’m saying is, you get more out than you put in.

我想说的是，你得到的比你付出的更多。

Once you’ve made a choice…

一旦你做出选择……

And maybe some alien somewhere made a different choice of how they’re going to do their math.

也许某个地方的某个外星人对他们的数学计算方式做出了不同的选择。

But once you’ve made your choice, then you get saddled with a whole bunch of new truths that you discover that you can’t do anything about.

但一旦你做出了选择，你就会背负一大堆新的事实，你发现你对此无能为力。

They are given to you from somewhere.

它们是从某个地方给你的。

And you can say they’re random, or you can say, “No, there’s this space of these facts that they’re pulled from.

你可以说它们是随机的，或者你可以说，“不，它们是从这些事实的空间中提取出来的。

There’s a latent space of options that they come from.”

它们来自一个潜在的选择空间。”

1:40:41 So when your E is exactly 2.718 and so on, there is nothing you can do in physics to change it.

因此，当你的 E 恰好是 2.718 等时，你在物理学中无法改变它。

And you’re saying that space is immutable?

你是说空间是不变的？

1:40:46 It’s-

这是——

I’m not saying it’s immutable.

我并不是说它是一成不变的。

1:40:50 So I think Plato may or may not have thought that these forms are eternal and unchanging.

所以我认为柏拉图可能会也可能不会认为这些形式是永恒不变的。

That’s one place we differ.

这是我们不同的地方。

I actually think that space has some action to it, maybe even some computation to it.

我实际上认为空间对它有一些作用，甚至可能有一些计算。

But we’re, we’re just pointers.

但我们只是指针。

1:41:01 Can this-

这可以吗——

Well, so I’ll circle back around to that whole thing.

好吧，所以我会回到整件事。

1:41:05 So the only thing I was trying to do is blow up the idea that we’re cool with how it works in physics.

所以我唯一想做的就是推翻我们对它在物理学中的运作方式很感兴趣的想法。

No problem there.

那里没问题。

I think that’s a much bigger deal than people normally think it is.

我认为这比人们通常认为的要重要得多。

I think already there, you have this weird haunting of the physical world by patterns that are not coming from the physical world.

我认为已经存在了，你已经通过非来自物质世界的模式对物质世界产生了这种奇怪的困扰。

1:41:28 The reason I emphasize this is because now what I’m going to…

我之所以强调这一点是因为现在我要做的是……

when I amplify this into biology, I don’t think it sort of jumps as a new thing.

当我将其扩展到生物学中时，我不认为它是一个新事物。

I think it’s just a much more…

我认为这只是更多……

I think what we call biology are systems that exploit the hell out of it.

我认为我们所谓的生物学是一种充分利用它的系统。

I think physics is so constrained by it, but we call biology those things that make use of those kinds of things and run with it.

我认为物理学受到它的限制，但我们将那些利用这些事物并与之运行的事物称为生物学。

And so, again, I just think it’s a scaling.

所以，我再说一遍，我只是认为这是一种缩放。

I don’t think it’s a brand new thing that happens.

我不认为这是一个全新的事情发生。

I think it’s a scaling, right?

我认为这是一个缩放，对吗？

So what I’m saying is we already know from physics that there are non-physical patterns, and these are generally patterns of form, which is why I call them low agency, because they’re like fractals that stand still, and they’re like prime number distributions.

所以我想说的是，我们已经从物理学中知道存在非物理模式，这些通常是形式模式，这就是为什么我称它们为低能动性，因为它们就像静止的分形，它们就像素数分布。

1:42:10 Although there’s a mathematician that’s talking in our symposium that’s telling me that actually I’m too chauvinistic even there.

尽管有一位数学家在我们的研讨会上发言，他告诉我，实际上即使在那里我也太沙文主义了。

That actually, even those things have more oomph than even I gave them credit for, which I love.

事实上，即使是那些东西也比我所认为的更有魅力，这是我喜欢的。

So what I’m saying is those kinds of static patterns are things that we typically see in physics, but they’re not the full extent of what lives in that space.

所以我想说的是，这些静态模式是我们在物理学中通常看到的东西，但它们并不是那个空间中存在的全部内容。

That space is also home to some patterns that are very high agency.

这个空间也是一些具有很高代理性的模式的所在地。

And if we give them a body, if we build a body that they can inhabit, then we get to see different behavioral competencies that the behavior scientists say, “Oh, I know what that looks like.” That’s this kind of behavioral, you know, this kind of mind or that kind of mind.

如果我们给他们一个身体，如果我们建造一个他们可以居住的身体，那么我们就会看到行为科学家所说的不同的行为能力，“哦，我知道那是什么样子的。”这就是这种行为，你知道，这种心态或那种心态。

1:42:49 In a certain sense, I mean, yes, what I’m saying is extremely radical, but it is a very old idea.

从某种意义上说，我的意思是，是的，我所说的是极其激进的，但这是一个非常古老的想法。

It’s an old idea of a dualistic worldview, right?

这是二元世界观的古老观念，对吧？

Where the mind was not in the physical body, and that it in some way interacted with the physical brain.

心灵不在肉体中，并且它以某种方式与肉体的大脑相互作用。

So, I just want to be clear.

所以，我只想说清楚。

I’m not claiming that this is fundamentally a new idea.

我并不是说这从根本上来说是一个新想法。

This has been around forever.

这一直存在。

However, it’s mostly been discredited, and it’s a very unpopular view nowadays.

然而，这种观点大多遭到质疑，而且现在是一种非常不受欢迎的观点。

There are very few people in the, for example, cognitive science community or anywhere else in science that like this kind of view.

例如，在认知科学界或科学界的其他地方很少有人喜欢这种观点。

Primarily, and already Descartes was getting crap for this when he first tried it out as this interaction problem, right?

首先，当笛卡尔第一次尝试这个交互问题时，他已经对此感到厌烦了，对吧？

1:43:30 So the idea was, okay, well, if you have this non-physical mind and then you have this brain that presumably obeys conservation of mass energy and things like that, how are you supposed to interact with it?

所以这个想法是，好吧，好吧，如果你有这个非物质思维，然后你有这个大脑，大概遵循质量能量守恒和类似的东西，你应该如何与它互动？

And there are many other problems there.

还有很多其他问题。

So what I’m trying to point out is that first of all, physics already had this problem.

所以我想指出的是，首先，物理学已经存在这个问题。

You didn’t have to wait till you had biology and cognitive science to ask about it.

你不必等到有了生物学和认知科学才去问这个问题。

And what I think is happening and the way we need to think about this is coming back to my point that I think the mind-brain relationship is basically of the same kind as the math-physics relationship.

我认为正在发生的事情以及我们需要思考的方式又回到了我的观点，即我认为心脑关系基本上与数学物理关系相同。

1:44:06 The same way that non-physical facts of physics haunt physical objects is basically how I think different kinds of patterns that we call kinds of minds are manifesting through our…

就像物理的非物理事实困扰物理对象一样，我认为我们所谓的不同类型的思维模式基本上是通过我们的……表现出来的。

through interfaces like brains.

通过像大脑这样的界面。

How do we prove or disprove the existence of that world?

我们如何证明或反驳那个世界的存在？

1:44:19 ‘Cause it’s a pretty radical one.

因为这是一个非常激进的想法。

‘Cause this physical world, we can poke.

因为这个物理世界，我们可以戳破。

It’s there.

它就在那里。

It feels like all the incredible things like consciousness and cognition and all the goal-oriented behavior in agency all seems to come from this 3D entity.

感觉所有不可思议的东西，比如意识和认知，以及机构中所有以目标为导向的行为，似乎都来自这个 3D 实体。

Yeah, I mean-

是的，我的意思是-

And so, we can test it.

所以，我们可以测试它。

1:44:44 We can poke it.

我们可以戳它。

We can hit it with a stick.

我们可以用棍子打它。

Yeah, sort of.

是的，有点像。

Makes noises.

发出噪音。

Sort of.

有点像。

1:44:50 I mean, Descartes got some stuff wrong, I think.

我的意思是，我认为笛卡尔搞错了一些东西。

But one thing that he did get right, the fact that you actually don’t know what you can poke and what you can’t poke.

但他确实做对了一件事，即你实际上不知道你可以戳什么和不能戳什么。

The only thing you actually know are the contents of your mind, and everything else might be…

你唯一真正知道的就是你头脑中的内容，其他一切可能都是……

And, in fact, what we know from Anil Seth and Don Hoffman and various other people, it’s definitely a construct.

事实上，我们从阿尼尔·塞思、唐·霍夫曼和其他人那里了解到，这绝对是一个概念。

You might be on drugs, and you might wake up tomorrow and say, “My God, I had the craziest dream of being Lex Fridman.” Amazing.

你可能吸毒了，明天醒来你可能会说：“天啊，我做了一个最疯狂的梦想，就是成为莱克斯·弗里德曼。”惊人的。

It’s a nightmare.

这是一场噩梦。

Yeah, well…

是啊，好吧……

1:45:17 Yeah, that, that…

是啊，那个，那个……

Who knows?

谁知道？

But-

但是——

It’s a ride.

这是一次旅程。

Right?

正确的？

1:45:20 But you see, it’s not clear at all that the physical poking is your primary reality.

但你看，根本不清楚物理戳戳是你的主要现实。

That’s not clear to me at all.

我根本不清楚。

I don’t know.

我不知道。

1:45:30 That’s an obvious thing that a lot of people can show…

这是很多人都可以展示的显而易见的事情……

is true to take a step to the Descartes, “I think, therefore I am.” That’s the only thing you know for sure, and everything else could be an illusion or a dream.

真正迈出了笛卡尔的一步，“我思故我在”。这是你唯一确定的事情，其他一切都可能是幻觉或梦。

That’s already a leap.

这已经是一个飞跃了。

I think from a basic caveman science perspective, the repeatable experiment…

我认为从基本的穴居人科学角度来看，可重复的实验......

…Is the one that most of intelligence comes from here.

……大部分情报都来自这里。

The reality is exactly as it is.

现实就是这样。

To take a step towards the Donald Hoffman worldview takes a lot of guts and imagination, and stripping away of the ego and all these kinds of processes.

向唐纳德·霍夫曼的世界观迈出一步需要大量的勇气和想象力，并剥离自我和所有这些过程。

I think you can get there more easily by synthetic bioengineering in the following sense.

我认为通过以下意义上的合成生物工程可以更容易地实现这一目标。

1:46:11 Do you feel a lack of X-ray perception?

您是否感觉缺乏 X 射线感知？

Do you feel blind in the X-ray spectrum or in the ultraviolet?

您在 X 射线光谱或紫外线中感到失明吗？

I mean, you don’t.

我的意思是，你不知道。

You have absolutely no clue that stuff is there, and all of your reality as you see it is shaped by your evolutionary history.

你完全不知道东西在那里，而你所看到的所有现实都是由你的进化历史塑造的。

It’s shaped by the cognitive structure that you have, right?

它是由你的认知结构决定的，对吗？

There are tons of stuff going on around us right now that we are completely oblivious.

现在我们周围发生了很多事情，但我们却完全忽视了。

There’s equally all kinds of other stuff which we construct, and this is just modern cognitive science that says that a lot of what we think is going on is a total fabrication constructed by us.

同样，我们还构建了各种其他东西，这只是现代认知科学，它表明我们认为正在发生的很多事情都是我们构建的。

1:46:54 So I think this is not a…

所以我认为这不是一个……

I don’t think this is a philos-…

我不认为这是一个哲学——

I mean, Descartes got there from a philosophical point.

我的意思是，笛卡尔是从哲学角度出发的。

That’s not what I’m, that’s not the leap I’m asking us to make.

那不是我，这不是我要求我们实现的飞跃。

I’m saying that depending on your embodiment, depending on your interface, and this is increasingly going to be more relevant as we make first augmented humans that have sensory substitution.

我是说，这取决于你的体现，取决于你的界面，随着我们制造出第一个具有感官替代的增强人类，这将变得越来越重要。

You’re going to be walking around.

你会四处走动。

Your friend’s going to be like, “Oh, man.

你的朋友会说：“哦，伙计。

I have this primary perception of the solar weather and the stock market because I got those implants.” “And what do you see?” “Well, I see the, you know, the traffic or the internet through the Trans-Pacific Channel.” We’re all going to be living in somewhat different worlds.

我对太阳天气和股市有这种主要的感知，因为我植入了这些植入物。” “你看到了什么？” “嗯，我通过跨太平洋海峡看到了交通或互联网。”我们都将生活在有些不同的世界中。

That’s the first thing.

这是第一件事。

1:47:29 The second thing is we’re going to become better attuned to other beings, whether they be cells, tissues.

第二件事是我们将变得更好地适应其他生物，无论它们是细胞还是组织。

You know, what’s it like to be a cell living in a 20,000-dimensional transcriptional space?

你知道，作为一个生活在 20,000 维转录空间中的细胞是什么感觉？

To novel beings that have never been here before, that have all kinds of crazy spaces that they live in, and that might be AIs, it might be cyborgs, it might be hybrids, it might be all sorts of things.

对于以前从未来过这里的新奇生物来说，他们生活在各种疯狂的空间中，可能是人工智能，可能是半机械人，可能是混血儿，可能是各种各样的东西。

So this idea that we have a consensus reality here that’s independent of some very specifically chosen aspects of our brain and our interaction, we’re going to have to give that up no matter what to relate to these other beings.

因此，我们在这里有一个共识现实，它独立于我们大脑和我们互动的一些非常特别选择的方面，我们将不得不放弃它，无论与这些其他存在有什么关系。

I think the tension is, and absolutely, and this idea that you’re talking about, almost…

我认为紧张是绝对的，而你所说的这个想法几乎……

1:48:07 I think you’ve termed it cognitive prosthetics…

我认为你将其称为认知假肢......

…Which is different ways of perceiving and interacting with the world.

……这是感知世界和与世界互动的不同方式。

But I guess the question is, is our human experience, the direct human experience, is that just a slice of the real world, or is it a pointer to a different world?

但我想问题是，我们人类的经验，直接的人类经验，只是现实世界的一部分，还是指向另一个世界的指针？

That’s what I’m trying to figure out.

这就是我想弄清楚的。

Figure out, because the claim you’re making is a really fascinating one, a compelling one.

弄清楚吧，因为你提出的主张非常令人着迷，令人信服。

There’s a pretty strong one, which is there’s another world into which our brain is an interface, which means you could theoretically map that world systematically.

有一个非常强大的一个，那就是我们的大脑是另一个世界的接口，这意味着理论上你可以系统地绘制那个世界。

Yeah, which is exactly what we’re trying to do.

是的，这正是我们正在尝试做的。

1:48:52 I mean, we’re…

我的意思是，我们……

Right, right, but it’s not clear that that world exists.

是的，是的，但尚不清楚那个世界是否存在。

Yeah, yeah, okay.

是啊是啊，好吧。

1:48:59 So, that’s the beautiful part about this, and this is why I’m talking about this now, whereas I wasn’t, you know, about a year ago.

所以，这就是这件事的美妙之处，这就是为什么我现在谈论这个，而大约一年前我还没有谈论这个。

Up until a year ago, I was never talking about this because I think this is now actionable.

直到一年前，我从未谈论过这个问题，因为我认为现在这是可行的。

So there’s this diagram that’s called the Map of Mathematics, and they basically try to show how all the different pieces of math link together, and there’s a bunch of different versions of it.

因此，有一个称为数学地图的图表，他们基本上试图展示所有不同的数学部分如何链接在一起，并且有很多不同的版本。

So there are two features to this.

所以这有两个特点。

One is that, what is it a map of?

一是，它是什么地图？

Well, it’s a map of various truths.

嗯，这是一张包含各种真理的地图。

It’s a map of facts that are thrust on you.

这是一张强加给你的事实地图。

You don’t have a choice.

你别无选择。

Once you’ve picked some axioms, you just, you know, hear some surprising facts that are just going to be given to you.

一旦你选择了一些公理，你就会听到一些即将提供给你的令人惊讶的事实。

1:49:38 But the other key thing about this is that it has a metric.

但另一个关键点是它有一个指标。

It’s not just a random heap of facts.

这不仅仅是一堆随机的事实。

They’re all connected to each other in a particular way.

它们都以特定的方式相互连接。

They literally make a space, and so when I say it’s a space of patterns, what I mean is it is not just a random bag of patterns such that when you have one pattern, you are no closer to finding any other pattern.

它们确实创造了一个空间，所以当我说这是一个模式空间时，我的意思是它不仅仅是一袋随机的模式，这样当你有一个模式时，你就不会更接近找到任何其他模式。

I’m saying that there’s some kind of a metric to it so that when you find one, others are closer to it, and then you can get there.

我是说，它有某种度量标准，这样当你找到一个度量标准时，其他人就更接近它，​​然后你就可以到达那里。

So that’s the claim.

这就是主张。

And obviously, this is…

显然，这是……

Now, not everybody buys this, and so on.

现在，并不是每个人都买这个，等等。

This is one idea.

这是一个想法。

Now, how do we know that this exists?

现在，我们怎么知道它存在呢？

Well, I’ll say a couple of things.

好吧，我会说几件事。

If that didn’t exist, what is that a map of?

如果不存在，那地图是什么？

1:50:18 If there is no space, if you don’t want to call it a space, that’s okay, but you can’t get away from the fact that as a matter of research, there are patterns that relate to each other in a particular way.

如果没有空间，如果你不想称其为空间，那也没关系，但你无法回避这样一个事实：作为研究的问题，存在着以特定方式相互关联的模式。

What’s, you know, well, the final step of calling it a space is minimal.

你知道，好吧，称其为空间的最后一步是最小的。

The bigger issue is what the hell is it a map of then if it’s not a space?

更大的问题是，如果它不是一个空间，那么它到底是什么地图？

So that’s the first thing.

这是第一件事。

Now, that’s how it plays out, I think, in math and physics.

现在，我想，这就是数学和物理中的表现。

Now, in biology, here’s how we’re going to know if this makes any sense.

现在，在生物学中，我们将通过以下方式知道这是否有意义。

What we are doing now is trying to map out that space by saying, “Look, we took…

我们现在正在做的就是尝试通过说“看，我们采取了......

1:50:53 We know that the frog genome maps to one thing, and that’s a frog.

我们知道青蛙基因组映射到一件事，那就是青蛙。

It turns out that exact same genome, if you just take the slightest step with the exact same genome but you just take some cells out of their environment, they can also make xenobots with very specific different transcriptomes, very specific behaviors, very specific shapes.

事实证明，完全相同的基因组，如果你只用完全相同的基因组采取最轻微的步骤，但你只是将一些细胞从其环境中取出，它们也可以制造出具有非常特定的不同转录组、非常特定的行为、非常特定的形状的异种机器人。

It’s not just, “Oh, well, you know, they do whatever,” and that they have very specific behaviors, just like the frog had very specific properties.

这不仅仅是“哦，好吧，你知道，他们做任何事”，而且他们有非常具体的行为，就像青蛙有非常具体的属性一样。

We can start to map out what all those are, right, and make that…

我们可以开始规划出所有这些是什么，对吧，然后……

1:51:25 And basically try to draw the latent space from which those things are pulled, and one of two things is going to happen in the future.

基本上尝试绘制出那些东西被拉出的潜在空间，并且未来将发生两件事之一。

So this is, you know, come back in 20 years, and we’ll see how this worked out.

所以，你知道，20 年后我们会看到结果如何。

One thing that could happen is that we’re going to see, “Oh, yeah, just like the map of mathematics, we made a map of the space.” And we know now that if I want a system that acts like this and this, here’s the kind of body I need to make for it, because those are the patterns that exist.

可能发生的一件事是我们会看到，“哦，是的，就像数学地图一样，我们制作了一张空间地图。”我们现在知道，如果我想要一个像这样那样运作的系统，我需要为其制作这样的身体，因为这些是存在的模式。

The Anthrobots have four different behaviors, not seven and not one.

人类机器人有四种不同的行为，不是七种，也不是一种。

And so, that’s what I can pull from.

所以，这就是我可以借鉴的。

These are the options I have.

这些是我的选择。

Is it possible that there are varying degrees of grandeur to the space that you’re thinking about mapping?

您正在考虑绘制地图的空间是否可能存在不同程度的宏伟？

1:51:59 Meaning, it could strictly be just the space of biology, or is this a space of, like, minds, which feels like it could encompass a lot more than just biology?

意思是，它可能严格来说只是生物学的空间，或者这是一个类似思想的空间，感觉它可以包含比生物学更多的东西？

Yeah, except that…

是的，除了那个……

1:52:25 and I don’t see how it would be separate because I’m not just talking about an anatomical shape and transcriptional profile.

我不明白它是如何分开的，因为我不只是在谈论解剖形状和转录特征。

I’m also talking about behavioral competencies.

我也在谈论行为能力。

So when we make something and we find out that, okay, it does habituation, sensitization.

因此，当我们制作一些东西时，我们发现，好吧，它确实会让人习惯、敏感。

It does not do Pavlovian conditioning, and it does do delayed gratification, and it doesn’t have language, that is a very specific cognitive profile.

它不进行巴甫洛夫条件反射，但它确实进行延迟满足，而且它没有语言，这是一种非常具体的认知特征。

That’s a region of that space, and there’s another region that looks different, because I don’t make a sharp distinction between biology and cognition.

这是那个空间的一个区域，还有另一个看起来不同的区域，因为我没有在生物学和认知之间做出明确的区分。

If you want to explain behaviors, they are drawn from some distribution as well.

如果你想解释行为，它们也来自某种分布。

So I think in 20 years, or however long it’s going to take, one of two things will happen.

所以我认为 20 年后，或者无论需要多长时间，以下两件事之一将会发生。

1:53:08 Either we and other people who are working on this are going to actually produce a map of that space and say, “Here’s why you’ve gotten systems that work like this and like this and like this, but you’ve never seen any that work like that,” right?

我们和其他从事这方面工作的人要么会实际绘制出该空间的地图，然后说：“这就是为什么你已经得到了像这样、这样、这样工作的系统，但你从未见过任何像这样工作的系统，”对吗？

Or, we’re going to find out that I’m wrong, and that basically it’s not worth calling it a space because it is so random and so jumbled up that there is, we’ve been able to make zero progress in linking the embodiments that we make to the patterns that come through.

或者，我们会发现我错了，基本上不值得称其为空间，因为它是如此随机和混乱，以至于我们在将我们所做的实施例与所经历的模式联系起来方面取得了零进展。

Just to be clear, I mean, from your blog post on this, from the paper, we’re talking about a space that includes a lot of stuff.

需要澄清的是，我的意思是，从你关于此的博客文章、从论文中来看，我们正在谈论一个包含很多东西的空间。

Yeah, yeah.

是啊是啊。

It includes human, what is it, meditating?

它包括人类，它是什么，冥想？

1:53:48 Steve.

史蒂夫.

“Hello, my name is Steve.” AI systems, so all those basic computational systems, objects, biological systems, concepts.

“你好，我叫史蒂夫。”人工智能系统，所有这些基本的计算系统、对象、生物系统、概念。

It includes everything.

它包括一切。

Well, it includes specific patterns that we have given names to.

嗯，它包括我们已命名的特定模式。

Right.

正确的。

Some of those patterns we’ve named mathematical objects.

我们将其中一些模式命名为数学对象。

1:54:08 Some of those patterns we’ve named anatomical outcomes.

我们将其中一些模式命名为解剖学结果。

Some of those patterns we’ve named psychological types.

我们将其中一些模式命名为心理类型。

So every entry in an encyclopedia, old-school Britannica, is a pointer to this space.

因此，百科全书（老派的大英百科全书）中的每一个条目都是指向这个空间的指针。

There is a set of things that I feel very strongly about because the research is telling us that’s what’s going on, and then there’s a bunch of other stuff that I see as hypotheses for next steps that guide experiment.

我对一系列事情的感受非常强烈，因为研究告诉我们这就是正在发生的事情，然后还有很多其他东西我认为是指导实验的后续步骤的假设。

1:54:40 So what I’m about to tell you, I don’t, you know, these are things I don’t actually know.

所以我要告诉你的是，我不知道，你知道，这些是我实际上不知道的事情。

These are just guesses that, you know, you need to make some guesses to make progress.

这些只是猜测，你知道，你需要做出一些猜测才能取得进展。

I don’t think that there are specific, or I don’t know, but it doesn’t mean that there are going to be specific Platonic patterns for, “This is the Titanic, and this is the sister of the Titanic, and this is some other kind of boat.” This is not what I’m saying.

我不认为有具体的，或者我不知道，但这并不意味着会有具体的柏拉图模式，“这是泰坦尼克号，这是泰坦尼克号的姐妹船，这是其他类型的船。”这不是我说的。

What I’m saying is, in some way that we absolutely need to work out, when we make minimal interfaces, we get more than we put in.

我想说的是，在某种程度上，我们绝对需要解决，当我们制作最小的界面时，我们得到的比我们投入的更多。

We get behaviors.

我们得到行为。

We get shapes.

我们得到形状。

We get mathematical truths, and we get all kinds of patterns that we did not have to create.

我们得到了数学真理，也得到了各种我们不必创造的模式。

We didn’t micromanage them.

我们没有对他们进行微观管理。

We didn’t know they were coming.

我们不知道他们会来。

1:55:22 We didn’t have to put any effort into making them.

我们不需要付出任何努力来制作它们。

They come from some distribution that seems to exist that we don’t have to create.

它们来自一些似乎存在但我们不必创建的发行版。

And exactly whether that space is sparse or dense, I don’t know.

我不知道那个空间到底是稀疏的还是密集的。

So, for example, if there is, you know, some kind of a Platonic form for the movie, The Godfather, if it’s surrounded by a bunch of crappy versions and then crappier versions still, I have no idea, right?

所以，举例来说，如果电影《教父》有某种柏拉图式的形式，如果它被一堆蹩脚的版本包围着，然后又是更蹩脚的版本，我不知道，对吧？

I don’t know if the space is sparse or not.

不知道空间是否稀疏。

I, you know, I don’t know if it’s finite or infinite.

我，你知道，我不知道它是有限的还是无限的。

These are all things I don’t know.

这些都是我不知道的事情。

What I do know is that it seems like physics, and for sure biology and cognition, are the benefits of ingressions that are free lunches in some sense.

我所知道的是，似乎物理学，当然还有生物学和认知，都是入侵的好处，在某种意义上是免费午餐。

We did not make them.

我们没有制造它们。

1:56:04 Calling them emergent does nothing for a research program, okay?

称它们为紧急事件对于研究项目来说毫无意义，好吗？

That just means you got surprised.

这只是意味着你感到惊讶。

I think, I think it’s much better if you make the optimistic assumption that they come from a structured space, that we have a prayer in hell of actually exploring.

我认为，如果你乐观地假设它们来自一个结构化的空间，我们在地狱中祈祷实际探索，那就更好了。

And in some decades, if I’m wrong, and it says, “You know what?

几十年后，如果我错了，它会说：“你知道吗？

We tried.

我们尝试过。

It looks like it really is random.

看起来确实是随机的。

Too bad.” Fine.

太糟糕了。”美好的。

Is there a difference?

有区别吗？

1:56:24 Like, can we one day prove the existence of this world?

比如，我们有一天能证明这个世界的存在吗？

And is there a difference between it being a really effective model for connecting things, explaining things, versus an actual place where the information about these distributions that we’re sampling actually exists, that we can hit with a stick?

它是一个连接事物、解释事物的真正有效的模型，与我们正在采样的分布信息实际存在、我们可以用棍子敲击的实际地方之间有区别吗？

Yeah, you can try to make that distinction.

是的，你可以尝试区分一下。

Yeah.

是的。

But I think modern cognitive neuroscience will tell you that whatever you think this is, at most, it is a very effective model for predicting the future experiences you’re going to have.

但我认为现代认知神经科学会告诉你，无论你认为这是什么，它最多都是一个非常有效的模型，可以预测你未来的经历。

So all of this that we think about as physical reality is just a convenient model.

因此，我们所认为的物理现实只是一个方便的模型。

I mean, that’s not me.

我的意思是，那不是我。

1:57:13 That’s predictive processing and active inference—that’s modern neuroscience telling you this.

这就是预测处理和主动推理——现代神经科学告诉你这一点。

This isn’t anything that I’m particularly coming up with.

这不是我特别想出来的。

All I’m saying is the distinction you’re trying to make, which is an old-school, realist kind of view, that is it metaphorical or is it real?

我所说的只是你试图做出的区分，这是一种老派的现实主义观点，它是隐喻的还是真实的？

All we have in science are metaphors, I think, and the only question is how good are your metaphors.

我认为，我们在科学中所拥有的一切都是隐喻，唯一的问题是你的隐喻有多好。

And I think as agents living in a world, all we have are models of what we are and what the outside world is.

我认为，作为生活在一个世界中的主体，我们所拥有的只是我们自己和外部世界的模型。

That’s it.

就是这样。

And the question is, how good is it a model?

问题是，这个模型有多好？

1:57:49 And my claim about this is in some small number of decades, this will either give rise to a very enabling mapping of the space for AI, for bioengineering, for, you know, biology, whatever.

我对此的主张是，在短短几十年内，这将为人工智能、生物工程、生物学等领域带来非常有利的空间映射。

Or we are going to find out that it really sucks, because it really is a random grab bag of stuff, and we tried the optimistic research program, it failed, and we’re just going to have to live with surprise.

或者我们会发现它真的很糟糕，因为它确实是一个随机的东西，我们尝试了乐观的研究计划，它失败了，我们只能带着惊喜生活。

I mean, I doubt that’s going to happen, but it’s a possible outcome.

我的意思是，我怀疑这会发生，但这是一个可能的结果。

But do you think there is some place where the information is stored about these distributions that are being sampled through the thin interfaces?

但是您认为是否有某个地方存储有关通过瘦接口采样的这些分布的信息？

1:58:16 Like an actual place?

就像一个真实的地方吗？

Place is weird because it isn’t the same as our physical space-time, okay?

地方很奇怪，因为它与我们的物理时空不一样，好吗？

1:58:28 I don’t think it’s that.

我不认为是这样。

So calling it a place is a little weird.

所以称它为一个地方有点奇怪。

No, but like physics, general relativity describes a space-time.

不，但像物理学一样，广义相对论描述了时空。

Okay.

好的。

Could other physics theories be able to describe this other space where information is stored that we can apply, maybe different, but in the same spirit, laws about—

其他物理理论是否能够描述我们可以应用的存储信息的另一个空间，也许不同，但本着同样的精神，有关以下的定律：

Yes

是的

information?

信息？

I definitely think there are going to be systematic laws.

我绝对认为将会有系统的法律。

1:58:53 I don’t think they’re going to look anything like physics.

我不认为它们看起来像物理学。

You can call it physics if you want, but I think it’s going to be so different that that probably just, you know, cracks the word.

如果你愿意的话，你可以称之为物理学，但我认为它会非常不同，以至于你知道，这可能只是破解这个词。

And whether information is going to survive that, I’m not sure.

我不确定信息是否会在这种情况下幸存下来。

But I definitely think that there are going to be laws.

但我绝对认为会有法律。

But I think they’re going to look a lot more like aspects of psychology and cognitive science than they’re going to look like physics.

但我认为它们看起来更像心理学和认知科学的各个方面，而不是物理学。

That’s my guess.

这是我的猜测。

So what does it look like to prove that world exists?

那么如何证明世界存在呢？

What it looks like is a successful research program that explains how you pull particular patterns when you need them, and why some patterns come and others don’t, and show that they come from an ordered space.

它看起来像是一个成功的研究项目，它解释了如何在需要时提取特定模式，以及为什么有些模式出现而其他模式不出现，并表明它们来自有序空间。

Across a large number of organisms?

跨越大量生物体？

Well, it’s not just organisms.

嗯，这不仅仅是有机体。

1:59:43 I mean, I think it’s going to end up, and I mean, you can talk to the machine learning people about how they got to this point.

我的意思是，我认为这将会结束，我的意思是，你可以与机器学习人员讨论他们是如何走到这一步的。

Again, because this is not just me.

再说一次，因为这不仅仅是我。

There are a bunch of different disciplines that are converging on this now simultaneously.

现在有许多不同的学科同时汇聚于此。

You’re going to find again, just like in mathematics, where from different directions everybody sort of is looking at different things.

你会再次发现，就像在数学中一样，每个人都从不同的方向看待不同的事物。

Say, “Oh my God, this is one underlying structure that seems to inform all of this.” So in physics, in mathematics, in computer science, machine learning, possibly in economics, certainly in biology, possibly in cognitive science, we’re going to find these structures.

说：“天哪，这似乎是一个潜在的结构，它告诉了这一切。”因此，在物理学、数学、计算机科学、机器学习、可能在经济学、当然在生物学、可能在认知科学中，我们将找到这些结构。

2:00:20 It was already obvious in Pythagoras’ time that there are these patterns.

在毕达哥拉斯时代，这些模式的存在就已经很明显了。

The only remaining question is, are they part of an ordered, structured space, and are we up to the task of mapping out the relationship between what we build and the patterns that come through it?

唯一剩下的问题是，它们是有序的、结构化的空间的一部分吗？我们是否能够完成绘制我们构建的内容与通过它产生的模式之间的关系的任务？

So from the machine learning perspective, is it then the case that even something as simple as LLMs are sneaking up onto this world, that the representations that they form are sneaking up to it?

那么从机器学习的角度来看，即使是像法学硕士这样简单的东西也正在悄悄进入这个世界，他们形成的表征也在悄悄接近这个世界吗？

When…

当……

2:00:54 I’ve given this talk to some audiences, especially in the organicist community.

我向一些观众，特别是有机主义者社区做了这次演讲。

People like the first part where it’s like, okay, now there’s an idea for what the magic, quote unquote, is that’s special about living things and so on.

人们喜欢第一部分，好吧，现在有了一个想法，即生物的特殊之处，等等。

Now, if we could just stop there, we would have dumb machines that just do what the algorithm says, and we have these magical living interfaces that can be the recipient for these ingressions.

现在，如果我们能就此打住，我们就会有愚蠢的机器，它们只会按照算法所说的去做，并且我们有这些神奇的生活界面，可以成为这些入侵的接收者。

Cool, right?

很酷，对吧？

We can cut up the world in this way.

我们可以用这种方式来切割世界。

Unfortunately or fortunately, I think, that’s not the case.

我认为不幸或幸运的是，事实并非如此。

And I think that even simple minimal computational models are to some extent beneficiaries of these free lunches.

我认为，即使是简单的最小计算模型在某种程度上也是这些免费午餐的受益者。

2:01:41 I think that the theories we have, and this goes back to the thin client interface kind of idea.

我认为我们拥有的理论可以追溯到瘦客户端界面的想法。

The theories we have of both physics and computation, so theory of algorithms, you know, Turing machines, all that good stuff.

我们拥有物理和计算理论，所以算法理论，你知道，图灵机，所有这些好东西。

Those are all good theories of the front-end interface, and they’re not complete theories of the whole thing.

这些都是前端界面的好理论，但它们并不是整个事情的完整理论。

They capture the front end which is why they get surprised, which is why these things are surprising when they happen.

他们捕捉前端，这就是为什么他们会感到惊讶，这就是为什么这些事情发生时会令人惊讶。

I think that when we see embryos of different species, we are pulling from well-trodden familiar regions of that space, and we know what to expect: frog, you know, snake, whatever.

我认为，当我们看到不同物种的胚胎时，我们是从那个空间中经常被踩踏的熟悉区域中拉出来的，并且我们知道会发生什么：青蛙，你知道，蛇，等等。

2:02:21 When we make cyborgs and hybrids and biobots, we are pulling from new regions of that space that look a little weird and they’re unexpected, but you know, we can still kind of get our mind around them.

当我们制造半机械人、混合体和生物机器人时，我们是从那个空间的新区域中提取出来的，这些区域看起来有点奇怪，而且出乎意料，但你知道，我们仍然可以围绕它们思考。

When we start making AIs, proper AIs, we are now fishing in a region of that space that may never have had bodies before.

当我们开始制造人工智能，真正的人工智能时，我们现在正在那个空间的一个以前可能从未有过物体的区域钓鱼。

It may have never been embodied before.

它可能以前从未被体现过。

And what we get from that is going to be extremely surprising.

我们从中得到的结果将会非常令人惊讶。

And the final thing just to mention on that is that because of this, because of the inputs from this Platonic space, some of the really interesting things that artificial constructs can do are not because of the algorithm; they’re in spite of the algorithm.

最后要提到的是，正因为如此，因为来自柏拉图空间的输入，人工构造可以做的一些真正有趣的事情并不是因为算法；而是因为算法。他们不顾算法。

They are filling up the spaces in between.

他们正在填补之间的空间。

2:03:09 There’s what the algorithm is forcing you to do, and then there’s the other cool stuff it’s doing which is nowhere in the algorithm.

这是算法强迫你做的事情，然后是它正在做的其他很酷的事情，而这些事情在算法中是找不到的。

And if that’s true, and we think it’s true even of very minimal systems, then this whole business of language models and AIs in general, watching the language part may be a total red herring because the language is what we force them to do.

如果这是真的，而且我们认为即使对于非常小的系统也是如此，那么总的来说，语言模型和人工智能的整个业务，观察语言部分可能完全是转移注意力，因为语言是我们强迫他们做的。

The question is, what else are they doing that we are not good at noticing?

问题是，他们还做了哪些我们不善于注意到的事情？

And this is, you know, this is something that we are, I think, as an existential step for humanity, to become better at this because we are not good at recognizing these things now.

我认为，这是人类生存的一步，我们要在这方面变得更好，因为我们现在不擅长认识这些事情。

You’ve got to tell me more about this behavior that is observable, that is unrelated to the explicitly stated goal of a particular algorithm.

你必须告诉我更多关于这种可观察到的行为，这与特定算法的明确规定的目标无关。

2:03:49 So you looked at a simple algorithm of sorting.

所以您查看了一个简单的排序算法。

Can you explain what was done?

你能解释一下做了什么吗？

Sure.

当然。

2:04:04 First, just the goal of this study: there are two things that people generally assume.

首先，本研究的目的是：人们普遍假设有两件事。

One is that we have a pretty good intuition about what kind of systems are going to have competencies.

一是我们对什么样的系统将具有能力有很好的直觉。

So from observing biologicals, we’re not terribly surprised when biology does interesting things.

因此，通过观察生物学，当生物学做出有趣的事情时，我们并不感到非常惊讶。

Everybody always says, “Well, it’s biology, you know, of course it does all this cool stuff.” And yeah, but do we have these machines?

每个人总是说，“嗯，这是生物学，你知道，它当然可以做所有这些很酷的事情。”是的，但是我们有这些机器吗？

And the whole point of having machines and algorithms and so on is they do exactly what you tell them to do, right?

拥有机器和算法等的全部意义在于它们完全按照你告诉它们的方式去做，对吗？

And people feel pretty strongly that that’s a binary distinction, and that’s what we can carve up the world in that way.

人们强烈地感觉到这是一种二元区别，这就是我们可以用这种方式瓜分世界的东西。

So I wanted to do two things.

所以我想做两件事。

2:04:42 I wanted to first of all explore that and hopefully break the assumption that we’re good at seeing this, because I think we’re not.

我想首先探索这一点，并希望打破我们擅长看到这一点的假设，因为我认为我们不擅长。

And I think it’s extremely important that we understand very soon that we need to get much better at knowing when to expect these things.

我认为非常重要的是，我们很快就会明白，我们需要更好地知道何时会发生这些事情。

And the other thing I wanted to do was to find out, you know, mostly people assume that you need a lot of complexity for this.

我想做的另一件事是找出，你知道，大多数人认为为此需要很多复杂性。

So when somebody says, “Well, the capabilities of my mind are not properly encompassed by the rules of biochemistry,” everybody’s like, “Yeah, that makes sense.” Where, you know, you’re very complex and okay, your mind does things that you couldn’t…

因此，当有人说，“嗯，我的思维能力并没有被生物化学规则正确地涵盖”时，每个人都会说，“是的，这是有道理的。”你知道，你非常复杂，但好吧，你的大脑会做你做不到的事情……

2:05:22 You didn’t see that coming from the rules of biochemistry, right?

你没有从生物化学规则中看到这一点，对吗？

Like, we know that.

就像，我们知道这一点。

So mostly people think that has to do with complexity, and what I would like to find out as part of understanding what kind of interfaces give rise to what kind of ingressions, is it really about complexity?

所以大多数人认为这与复杂性有关，作为理解什么样的接口会引起什么样的入侵的一部分，我想找出答案，这真的与复杂性有关吗？

How much complexity do you actually need?

您实际需要多少复杂性？

Is there some threshold after which this happens?

发生这种情况是否有某个阈值？

Is it really specific materials?

真的是特定材料吗？

Is it biologicals?

是生物制品吗？

Is it something about evolution?

这与进化有关吗？

Like, what is it about these kinds of things that allows this surprise, right?

就像，这些事情到底是什么让我们感到惊讶，对吧？

Allows this idea that we are more than the sum of our parts.

允许这样的想法：我们不仅仅是各个部分的总和。

And I had a strong intuition that none of those things are actually required, that this is…

我有一种强烈的直觉，这些东西实际上都不是必需的，这是……

2:05:58 This kind of magic, so to speak, seeps into pretty much everything.

可以说，这种魔力几乎渗透到一切事物中。

And so to look at that, I wanted also to have an example that had significant shock value.

因此，为了了解这一点，我还想要一个具有重大震撼价值的例子。

Because the thing with biology is there’s always more mechanism to be discovered, right?

因为生物学的问题是总是有更多的机制有待发现，对吗？

Like, there’s infinite depth of what the materials are doing.

就像，材料的作用有无限的深度。

You know, somebody will always say, “Well, there’s a mechanism for that, you just haven’t found it yet.” So I wanted an example that was simple, transparent, so you could see all the stuff.

你知道，有人总是会说，“好吧，有一个机制，只是你还没有找到它。”所以我想要一个简单、透明的例子，这样你就可以看到所有的东西。

There was nowhere to hide.

无处可藏。

I wanted it to be deterministic, because I don’t want it to be something around unpredictability or stochasticity, and I want it to be something familiar to people, minimal.

我希望它是确定性的，因为我不希望它具有不可预测性或随机性，而且我希望它是人们所熟悉的、最小的。

2:06:35 And I wanted to use it as a model system for honing our abilities to take a new system and looking at it with fresh eyes, and that’s because these sorting algorithms have been studied for over 60 years.

我想用它作为一个模型系统来磨练我们采用新系统并以新的眼光看待它的能力，这是因为这些排序算法已经被研究了 60 多年。

We all think we know what they do and what their properties are.

我们都认为我们知道他们做什么以及他们的属性是什么。

The algorithm itself is just a few lines of code, you know?

算法本身只是几行代码，你知道吗？

You can see exactly what’s there, it’s deterministic.

你可以准确地看到那里有什么，它是确定性的。

So that’s why.

所以这就是原因。

That’s why, right?

这就是原因，对吧？

I wanted the most shock value out of a system like that, if we were to find anything, and to use it as an example of taking something minimal and seeing what can be gotten out of it.

如果我们要找到任何东西，我希望从这样的系统中获得最大的震撼价值，并用它作为一个例子，以最小的方式获取一些东西，看看可以从中得到什么。

2:07:08 So I’ll describe two interesting things about it, and then we have lots of other work coming in the next year about even simpler systems.

因此，我将描述有关它的两个有趣的事情，然后我们明年将开展许多关于更简单系统的其他工作。

I mean, it’s actually crazy.

我的意思是，这实际上很疯狂。

So the very first thing is this: the standard sorting…

所以第一件事是：标准排序……

so let’s say bubble sort, right?

那么我们就说冒泡排序吧？

And all these sorting algorithms, you know, what you’re starting out with is an array of jumbled up digits, okay, so integers.

所有这些排序算法，你知道，你一开始就是一个混乱的数字数组，好吧，所以是整数。

It’s an array of mixed up integers, and what the algorithm is designed to do is to eventually arrange them all into order, and what it does, generally, is compare some pieces of that array and based on which one is larger than which, it swaps them around.

它是一个混合整数的数组，该算法的设计目的是最终将它们全部按顺序排列，通常，它的作用是比较该数组的某些部分，并根据哪个大于哪个，将它们交换。

2:07:46 And you can imagine that if you just keep doing that and you just keep comparing and swapping, then eventually you can get all the digits in the same order.

你可以想象，如果你继续这样做，继续比较和交换，那么最终你可以得到相同顺序的所有数字。

So, the first thing I decided to do, and this is the work of my student Kaining Zhang and then Adam Goldstein on this paper, this goes back to our original discussion about putting a barrier between it and its goals.

所以，我决定做的第一件事，这是我的学生 Kaining Chang 和 Adam Goldstein 在这篇论文中的工作，这可以追溯到我们最初关于在它和它的目标之间设置障碍的讨论。

And the first thing I said, “Okay, how do we put a barrier in?” Well, how about this?

我说的第一句话是：“好吧，我们如何设置障碍？”嗯，这个怎么样？

The traditional algorithm assumes that the hardware is working correctly.

传统算法假设硬件工作正常。

So if you have a seven and then a five, and you tell them to swap, the lines that swap the five and the seven, and then you go on, you never check.

因此，如果你有一个七，然后有一个五，你告诉他们交换，交换五和七的线，然后你继续，你永远不会检查。

Did it swap?

换了吗？

2:08:24 Because you assume that it’s reliable hardware, okay?

因为你认为它是可靠的硬件，好吗？

So what we decided to do was to break one of the digits so that it doesn’t move.

所以我们决定做的是破坏其中一个数字，使其不再移动。

When you tell it to move, it doesn’t move.

当你让它移动时，它却不动。

We don’t change the algorithm.

我们不改变算法。

That’s really key.

这真的很关键。

We do not put anything new in the algorithm that says, “What do you do if the damn thing didn’t move?” Okay?

我们并没有在算法中加入任何新内容，比如“如果那该死的东西不动了你该怎么办？”好的？

Just run it exactly the same way.

只需以完全相同的方式运行即可。

What happens?

会发生什么？

Turns out, something very interesting happens.

事实证明，发生了一些非常有趣的事情。

It still works, so it still sorts it, but it eventually sorts it by moving all the stuff around the broken number, okay?

它仍然有效，所以它仍然对它进行排序，但它最终通过将所有内容移动到损坏的数字周围来对其进行排序，好吗？

And that makes sense, but here’s something interesting.

这是有道理的，但这里有一些有趣的事情。

Suppose we, suppose we plot, at any given moment, we plot the degree of sortedness of the string as a function of time.

假设我们，假设我们在任何给定时刻绘制字符串的排序程度作为时间的函数。

2:09:09 If you run the normal algorithm, it’s running and it’s guaranteed to get where it’s going.

如果你运行正常的算法，它就会运行并且保证到达目的地。

That’s the, you know, it’s got to sort, and it will always reach the end.

这就是，你知道，它必须排序，而且它总是会到达终点。

But when it encounters one of the broken digits, what happens is, the actual sortedness goes down.

但当它遇到一个损坏的数字时，实际的排序就会下降。

In order to then recoup and get better order later.

为了以后收回并获得更好的订单。

What it’s able to do is to go against the thing that it’s trying to do.

它能够做的就是违背它想要做的事情。

2:09:34 To go around in order to meet its goal later on.

为了以后达到目标而四处走动。

Now, if I showed this to a behavior scientist and I didn’t tell him what system was doing, they would say, “Well, we know what this is.

现在，如果我向行为科学家展示这个，并且没有告诉他系统在做什么，他们会说：“好吧，我们知道这是什么。

This is delayed gratification.” This is the ability of a system to go against its gradient and get what it needs to do.

这就是延迟满足。”这是系统逆其梯度并完成其需要做的事情的能力。

Now, imagine two magnets.

现在，想象两个磁铁。

Imagine you take two magnets and you put a piece of wood between them, and they’re like this.

想象一下，你拿两块磁铁，在它们之间放一块木头，它们就像这样。

What the magnet is not going to do is to go around the barrier and get to its goal.

磁铁不会做的是绕过障碍物并到达其目标。

The two…

两人……

they’re not smart enough to go against their gradient.

他们不够聪明，无法违背自己的意愿。

They’re just going to keep doing this.

他们只会继续这样做。

Some animals are smart enough, right?

有些动物足够聪明，对吗？

They’ll go around, and the sorting algorithm is smart enough to do that.

它们会四处走动，排序算法足够聪明，可以做到这一点。

2:10:13 But the trick is there are no steps in the algorithm for doing that.

但关键在于算法中没有执行此操作的步骤。

You could stare at the algorithm all day long.

你可以整天盯着算法。

You would not see that this thing can do delayed gratification.

你不会看到这个东西可以带来延迟满足。

It isn’t there.

它不在那里。

Now, there are two ways to look at this.

现在，有两种方式来看待这个问题。

On the one hand, you could say, or the reductionist physics approach, you could say, “Did it follow all the steps in the algorithm?” You say, “Yeah, it did.” Well then, there’s nothing to see here.

一方面，你可以说，或者还原论物理方法，你可以说，“它遵循算法中的所有步骤吗？”你说：“是的，确实如此。”那么，这里就没什么可看的了。

There’s no magic.

没有魔法。

This is, you know, it does what it does.

你知道，这就是它的作用。

It didn’t disobey the algorithm, right?

它没有违反算法，对吧？

I’m not claiming that this is a miracle.

我并不是说这是一个奇迹。

I’m not saying it disobeys the algorithm.

我并不是说它违反算法。

I’m saying it’s not failing to sort.

我是说这不是排序失败。

I’m saying it’s not doing some sort of, you know, crazy quantum thing.

我是说它并没有做某种疯狂的量子事情。

2:10:49 Not saying any of that.

没有说任何这些。

What I’m saying is other people might call it emergent.

我的意思是其他人可能会称之为紧急情况。

What it has are properties that are not complexity, not unpredictability, not perverse instantiation as sometimes in ALife.

它所具有的属性不是复杂性，不是不可预测性，也不是有时在 ALife 中那样的反常实例化。

What it has are unexpected competencies recognizable by behavioral scientists, meaning different types of cognition.

它具有行为科学家可以识别的意想不到的能力，意味着不同类型的认知。

Primitive.

原始。

Well, we wanted primitive, so there you go, it’s simple that you didn’t have to code into the algorithm.

好吧，我们想要原始的，所以你就可以了，很简单，你不必编写算法。

That’s very important.

这非常重要。

You get more than you start with, than you put in.

你得到的比你开始的多，也比你投入的多。

You didn’t have to do that.

你不必那样做。

You get these surprising behavioral competencies, not just complexity.

您将获得这些令人惊讶的行为能力，而不仅仅是复杂性。

That’s the first thing.

这是第一件事。

The second thing, which is also crazy, but it requires a little bit of explanation.

第二件事，也很疯狂，但需要一点解释。

2:11:32 The second thing that we said is, “Okay, what if instead of in the typical sorting algorithm, you have a single controller top down?” I’m sort of godlike looking down at the numbers and I’m swapping them according to the algorithm.

我们说的第二件事是，“好吧，如果你有一个自上而下的控制器，而不是典型的排序算法，该怎么办？”我就像上帝一样俯视着这些数字，然后根据算法交换它们。

What if…

如果……怎么办？

and this goes back to, actually the title of the paper talks about agential data, self-sorting algorithms.

这又回到了，实际上这篇论文的标题谈论的是代理数据，自排序算法。

This is back to like, who’s the pattern and who’s the agent, right?

这又回到了谁是模式、谁是代理人的问题，对吧？

2:11:52 You say, “What if we give the numbers a little bit of agency?” Here’s what we’re going to do: we’re not going to have any kind of top-down sort.

你说：“如果我们给这些数字一点代理权怎么办？”这就是我们要做的：我们不会进行任何自上而下的排序。

Every single number knows the algorithm, and it’s just going to do whatever the algorithm says.

每个数字都知道算法，并且它只会执行算法所说的任何操作。

So if I’m a five, I’m just going to execute the algorithm, and the algorithm will try to make sure that to my right is the six and to my left is a four.

因此，如果我是 5，我将执行该算法，该算法将尝试确保我的右边是 6，左边是 4。

That’s it.

就是这样。

So every digit is…

所以每个数字都是...

it’s like a distributed…

这就像一个分布式...

you know, it’s like an ant colony.

你知道，它就像一个蚁群。

There is no central planner.

没有中央计划者。

Everybody just does their own algorithm, okay?

每个人都只做自己的算法，好吗？

We’re just going to do that.

我们就这么做。

2:12:20 Once you’ve done that, and by the way, one of the values of doing that is that you can simulate biological processes because in biology, you know, if I have like a frog face and I scramble it with all the different organs, every tissue is going to rearrange itself so that ultimately you have, you know, nose, eyes, head.

顺便说一句，一旦你做到了这一点，这样做的价值之一就是你可以模拟生物过程，因为在生物学中，你知道，如果我有一张像青蛙的脸，我用所有不同的器官将它搅乱，每个组织都会重新排列自己，这样最终你就有了鼻子、眼睛、头部。

You’re going to have an order, right?

你会有订单，对吧？

So you can do that.

所以你可以这样做。

But okay, fine, but you can do something else cool.

但是好吧，好吧，但是你可以做一些其他很酷的事情。

Once you’ve done that, you can do something cool that you can’t do with a standard algorithm.

一旦你做到了这一点，你就可以做一些标准算法无法做到的很酷的事情。

You can make a chimeric algorithm.

您可以制作嵌合算法。

What I mean is not all the cells have to follow the same algorithm.

我的意思是并不是所有的单元都必须遵循相同的算法。

Some of them might follow bubble sort, some of them might follow selection sort.

其中一些可能遵循冒泡排序，其中一些可能遵循选择排序。

2:12:52 It’s like in biology what we do when we make chimeras, we make frogolottles.

就像在生物学中我们制造嵌合体时所做的那样，我们制造青蛙。

So frogolottles have some frog cells, they have some axolotl cells.

所以青蛙有一些青蛙细胞，它们有一些美西螈细胞。

What is that going to look like?

那会是什么样子？

Does anybody know what a frogolottle is going to look like?

有谁知道青蛙会是什么样子？

It’s actually really interesting that despite all the genetics and the developmental biology, you have the genomes, you have the frog genome, you have the axolotl genome, nobody can tell you what a frogolottle is going to look like, even though you have, yeah.

事实上，非常有趣的是，尽管有所有的遗传学和发育生物学，你有基因组，你有青蛙基因组，你有蝾螈基因组，没有人能告诉你青蛙会是什么样子，即使你有，是的。

This is, this is back to your question about physics and chemistry.

这是,这又回到你这个物理化学的问题了.

Like, yeah, you can know everything there is to know about how, you know, how the physics and the genetics work, but the decision-making, right?

就像，是的，你可以知道关于物理学和遗传学如何运作的一切，但决策，对吧？

Is like baby axolotls have legs.

就像小蝾螈有腿一样。

2:13:27 Tadpoles don’t have legs.

蝌蚪没有腿。

Is a frogolottle going to have legs, right?

青蛙会有腿，对吗？

Can you predict that from understanding the physics of transcription and all of that?

你能通过理解转录的物理原理和所有这些来预测这一点吗？

Anyway, so, so we made some…

无论如何，所以，所以我们做了一些……

So, so you, you see this as like an intersection of biology, physics- …cognition.

所以，你认为这就像生物学、物理学——……认知的交叉点。

So we made chimeric algorithms, and we said, “Okay, half the digits randomly.” We assigned them randomly.

所以我们制作了嵌合算法，我们说，“好吧，随机一半的数字。”我们随机分配他们。

So half the digits are randomly doing bubble sort, half the digits are randomly doing, I don’t know, selection sort or something.

所以一半的数字随机地进行冒泡排序，一半的数字随机地进行，我不知道，选择排序或其他什么。

But once you choose bubble sort, that digit is sticking with bubble sort.

但是一旦你选择冒泡排序，这个数字就与冒泡排序保持一致。

It’s sticking.

它粘住了。

2:13:55 We haven’t done the thing where they can swap between…

我们还没有做过让他们可以在……之间交换的事情。

no.

不。

But they’re sticking to it, right?

但他们还是坚持了下来，对吧？

You label them and they’re sticking to it.

你给他们贴上标签，他们就会坚持下去。

The first thing we learned is that…

我们学到的第一件事是……

Well, the first thing we learned is that distributed sorting still works.

好吧，我们首先了解到的是分布式排序仍然有效。

It’s amazing.

太棒了。

You don’t need a central planner when every number is doing its own thing, it still gets sorted.

当每个数字都在做自己的事情时，你不需要中央计划者，它仍然会被排序。

That’s cool.

这很酷。

The second thing we found is that when you make a chimeric algorithm where actually the algorithms are not even matching, that works too.

我们发现的第二件事是，当你制作一个嵌合算法时，实际上算法甚至不匹配，这也是有效的。

The thing still gets sorted.

事情还是有办法解决的。

That’s cool.

这很酷。

But the most amazing thing is when we looked at something that had nothing to do with sorting, and that is we asked the following question.

但最令人惊奇的是，当我们看到一些与排序无关的东西时，我们提出了以下问题。

We defined…

我们定义...

2:14:30 Adam Goldstein actually named this property, and I think it’s well-named.

亚当·戈尔茨坦实际上给这个属性命名了，我认为它的名字很好。

We define the algotype of a single cell.

我们定义单个细胞的算法类型。

It’s not the genotype, it’s not the phenotype, it’s the algotype.

这不是基因型，也不是表型，而是算法型。

The algotype is simply this: What algorithm are you following?

算法类型很简单：您遵循什么算法？

Which one are you?

你是哪一类？

Are you a selection sort or a bubble sort, right?

你是选择排序还是冒泡排序，对吧？

That’s it.

就是这样。

There are two algotypes.

有两种算法类型。

And we simply ask the following question, “During that process of sorting, what are the odds that whatever algotype you are, the guys next to you are your same type?” It’s not the same as asking how the numbers are sorted because it’s got nothing to do with the numbers.

我们简单地问以下问题：“在排序过程中，无论你是什么类型，你旁边的人与你是同一类型的可能性有多大？”这与询问数字如何排序不同，因为它与数字无关。

It’s actually just whatever type you are.

实际上，无论你是什么类型。

It’s more about clustering than sorting.

它更多的是关于聚类而不是排序。

Clustering.

聚类。

2:15:05 Well, that’s exactly what we call it.

嗯，这正是我们所说的。

We call it clustering.

我们称之为聚类。

And at first…

起初……

So now think of what happens, and that’s…

所以现在想想发生了什么，那就是……

and you can see this on that graph, it’s the red.

你可以在图表上看到这一点，它是红色的。

You start off, the clustering is at 50% because as I told you, we assign the algotypes randomly.

一开始，聚类率为 50%，因为正如我告诉过你的，我们随机分配算法类型。

So the odds that the guy next to you is the same as you is half, 50%, right?

那么你旁边的那个人和你一样的几率是一半，50%，对吗？

Because there are only two algotypes.

因为只有两种算法类型。

In the end, it is also 50% because the thing that dominates is actually the sorting algorithm, and the sorting algorithm doesn’t care what type you are.

最后也是50%，因为主导的其实是排序算法，而排序算法并不关心你是什么类型。

You’ve got to get the numbers in order.

你必须按顺序排列数字。

So by the time you’re done, you’re back to random algotypes because you have to get the numbers sorted.

所以当你完成时，你会回到随机算法类型，因为你必须对数字进行排序。

2:15:39 But in between, in between you get some amount of increased…

但在这两者之间，你会得到一些增加……

very significant, because look at the control, it’s in the middle, the pink is in the middle.

非常重要，因为看控件，它在中间，粉红色在中间。

In between you get significant amounts of clustering, meaning that certain algotypes like to hang out with their buddies for as long as they can.

在这两者之间，你会得到大量的聚类，这意味着某些算法类型喜欢尽可能长时间地与他们的伙伴一起出去玩。

Now, now, now here’s one more thing and then I’ll kind of give the philosophical significance of this.

现在，现在，现在还有一件事，然后我将给出它的哲学意义。

And so we saw this and I said, “That’s nuts because the algorithm doesn’t have any provisions for asking what algotype am I, what algotype is my neighbor?

所以我们看到了这一点，我说，“这太疯狂了，因为算法没有任何规定来询问我是什么算法类型，我的邻居是什么算法类型？

If we’re not the same, I’m going to move to be next to…” Like if you wanted to implement this, you would have to write a whole bunch of extra steps.

如果我们不一样，我就会搬到旁边......”就像如果你想实现这个，你将不得不编写一大堆额外的步骤。

2:16:17 There would have to be a whole bunch of observations that you would have to take of your neighbor to see how he’s acting.

你必须对你的邻居进行大量观察才能了解他的行为。

Then you would infer what algotype he is.

然后你就会推断出他是什么算法类型。

Then you would go stand next to the one that seems to have the same algotype as you.

然后你会站在那个似乎与你有相同算法类型的人旁边。

You would have to take a bunch of measurements to say, “Wait, is that guy doing bubble sort or is he doing selection sort,” right?

你必须进行一系列测量才能说，“等等，那个人是在进行冒泡排序还是在进行选择排序，”对吗？

Like if you wanted to implement this, it’s a whole bunch of algorithmic steps.

就像如果你想实现这个，它是一大堆算法步骤。

None of that exists in our algorithm.

我们的算法中不存在这些。

You don’t have any way of knowing what algotype you are or what anybody else is.

你没有任何办法知道你是什么算法类型或者其他人是什么。

Okay.

好的。

We didn’t have to pay for that at all.

我们根本不需要为此付费。

So notice a couple of interesting things.

所以请注意一些有趣的事情。

The first interesting thing is that this was not at all obvious from the algorithm itself.

第一个有趣的事情是，从算法本身来看，这一点并不明显。

2:16:50 The algorithm doesn’t say anything about algotypes.

该算法没有提及任何有关算法类型的内容。

Second thing is we paid computationally for all the steps needed to have the numbers sorted, right?

第二件事是我们支付了对数字进行排序所需的所有步骤的计算费用，对吧？

Because we know, you pay for a certain computation cost.

因为我们知道，您需要支付一定的计算成本。

The clustering was free.

聚类是免费的。

We didn’t pay for that at all.

我们根本没有为此付钱。

There were no extra steps.

没有额外的步骤。

So this gets back to your other question of how do we know there’s a platonic space, and this is kind of like one of the craziest things that we’re doing.

所以这又回到了你的另一个问题，即我们如何知道存在柏拉图空间，这有点像我们正在做的最疯狂的事情之一。

I actually suspect we can get free compute out of it.

我实际上怀疑我们可以从中获得免费计算。

I suspect that one of the things that we can do here is use these aggressions in a useful way that don’t require you to pay costs to pay physical costs, right?

我怀疑我们在这里可以做的一件事就是以一种有用的方式利用这些侵略，而不需要你付出代价来支付物理成本，对吗？

Because we know every bit has an energy cost that you have to get.

因为我们知道每一点都需要消耗能源。

The clustering was free.

聚类是免费的。

Nothing extra was done.

没有做任何额外的事情。

Yeah, just this plot for people who are just listening, on the X-axis is the percentage of completion of the sorting process and the Y-axis is the sortedness of the listed numbers, and then also in the red line is basically the degree to which they’re clustered.

是的，这只是给那些只是听的人看的图，X 轴是排序过程的完成百分比，Y 轴是列出的数字的排序程度，然后红线基本上是它们的聚类程度。

2:17:31 And you’re saying that there’s this unexpected competence of clustering.

你说集群有这种意想不到的能力。

And I should comment that I’m sure there’s a theoretical computer scientist listening to this saying, “I can model exactly what is happening here and prove that the clustering increases and decreases.” So taking the specific instantiation of the thing you’ve experimented with and prove certain properties of this.

我应该评论说，我确信有一位理论计算机科学家在听这句话，“我可以准确地模拟这里发生的事情，并证明聚类会增加和减少。”因此，采取您所尝试过的事物的具体实例并证明其某些属性。

2:18:19 But the point is that there’s a more general pattern here of probably other unexpected competencies that you haven’t discovered that emerge from this, that you could get free computation out of this thing.

但关键是，这里有一个更普遍的模式，可能是你还没有发现的其他意想不到的能力，你可以从这个东西中获得免费的计算。

So this goes back to the very first thing you said about physicists thinking that physics is enough.

所以这又回到了你所说的关于物理学家认为物理就足够的第一句话。

2:18:32 You’re 100% correct that somebody could look at this and say, “Well, I see exactly why this is happening.

你百分百正确地认为，有人看到这个后会说：“好吧，我明白为什么会发生这种情况。

We can track through the algorithm.” Yeah, you can.

我们可以通过算法进行追踪。”是的，你可以。

There’s no miracle going on here, right?

这里没有奇迹发生，对吧？

I mean, the hardware isn’t doing some crazy thing that it wasn’t supposed to do.

我的意思是，硬件没有做一些不应该做的疯狂的事情。

The point is that despite following the algorithm to do one thing, it is also at the same time doing other things that are neither prescribed nor forbidden by the algorithm.

关键在于，尽管遵循算法做一件事，但同时也在做其他既不是算法规定也不是禁止的事情。

It’s the space between chance and necessity, which is how a lot of people, you know, see these things.

这是机会和必然之间的空间，你知道，这就是很多人看待这些事情的方式。

2:19:07 It’s that free space, we don’t really have a good vocabulary for it, where the interesting things happen.

正是这个自由空间，我们并没有一个很好的词汇来描述它，有趣的事情就在那里发生。

And to whatever extent it’s doing other things that are useful, that stuff is computationally without extra cost.

无论它在多大程度上做其他有用的事情，这些东西在计算上都不需要额外的成本。

Now, there’s one other cool thing about this.

现在，还有另一件很酷的事情。

And this is the beginning of a lot of thinking that I’ve done about this—this relates to AI and stuff like that: intrinsic motivations.

这是我对此所做的许多思考的开始——这与人工智能和类似的东西有关：内在动机。

2:19:29 The sorting of the digits is what we forced it to do.

数字的排序是我们强迫它做的。

The clustering is an intrinsic motivation.

聚类是一种内在动机。

We didn’t ask for it.

我们没有要求它。

We didn’t expect it to happen.

我们没想到会发生这种事。

We didn’t explicitly forbid it, but we didn’t, you know, we didn’t know.

我们没有明确禁止它，但我们没有，你知道，我们不知道。

This is a great definition of the intrinsic motivation of a system.

这是系统内在动机的一个很好的定义。

So when people say, “Oh, that’s a machine, it only does what you programmed it to do.” I, you know, I as a human have intrinsic motivation, you know I’m creative and I have intrinsic motivation.

因此，当人们说：“哦，那是一台机器，它只会做你编程它要做的事情。”我，你知道，我作为一个人有内在的动机，你知道我有创造力，我有内在的动机。

Machines don’t do that.

机器不会这样做。

Even this minimal thing has a minimal kind of intrinsic motivation, which is something that is not forbidden by the algorithm, but isn’t prescribed by the algorithm either.

即使是这个最小的东西也有一种最小的内在动机，这是算法不禁止的东西，但也不是算法规定的。

2:20:08 And I think that’s an important, you know, third thing besides chance and necessity.

我认为这是除了偶然性和必然性之外的第三件重要的事情。

Something else that’s fun about this is when you think about intrinsic motivations, think about a child.

另一件有趣的事情是，当你思考内在动机时，想想孩子。

If you make him sit in math class all day, you’re never going to know what the other intrinsic motivations are that he might be doing, right?

如果你让他整天坐在数学课上，你永远不会知道他可能在做的其他内在动机是什么，对吗？

Like who knows what else he might be interested in.

就像谁知道他可能还对什么感兴趣。

So I wanted to ask this question.

所以我想问这个问题。

I want to say, if we let off the pressure on the sorting, what would happen?

我想说，如果我们把排序的压力放掉，会发生什么呢？

Now, that’s hard because if you mess with the algorithm, now it’s no longer the same algorithm, so you don’t want to do that.

现在，这很难，因为如果你搞乱了算法，现在它就不再是相同的算法，所以你不想这样做。

So we did something that I think was kind of clever.

所以我们做了一些我认为很聪明的事情。

We allowed repeat digits.

我们允许重复数字。

2:20:48 So if you allow repeat digits in your array, you can still have all the fives, can still be after all the fours and after all the sixes, but you can keep them as clustered as you want.

因此，如果您允许数组中存在重复数字，您仍然可以拥有所有五位，仍然可以位于所有四位和所有六位之后，但您可以根据需要将它们保持为集群。

So this thing at the end where they have to get de-clustered in order for the sorting to happen, we thought maybe we could let off the pressure a little bit.

因此，最后他们必须进行分簇才能进行排序，我们认为也许我们可以稍微减轻一点压力。

If you do that, all you do is allow some extra repeat digits, the clustering gets bigger.

如果你这样做，你所做的就是允许一些额外的重复数字，聚类会变得更大。

It will cluster as much as you let it.

只要你让它聚集，它就会聚集起来。

The clustering is what it wants to do.

聚类就是它想要做的。

The sorting is what we’re forcing it to do.

排序是我们强迫它做的事情。

And my only point is if the bubble sort, which has been gone over and gone over, how many times has these kinds of things that we didn’t see coming, what about the AIs, the language model, everything else?

我唯一的观点是，如果冒泡排序已经被重复了一遍又一遍，那么我们没有预见到的这类事情有多少次出现了，那么人工智能、语言模型和其他一切呢？

2:21:29 Not because they talk, not because they say that they’re, you know, have an inner perspective or any of that, but just from the fact that this thing is even the most minimal system surprises with what happens.

不是因为他们说话，不是因为他们说他们有内在的观点或任何其他观点，而是因为这件事甚至是最小的系统对所发生的事情的意外。

And frankly, when I see this, tell me if this doesn’t sound like all of our existential story.

坦率地说，当我看到这个时，请告诉我这是否听起来不像我们所有的存在主义故事。

For the brief time that we’re here, the universe is going to grind us into dust eventually, but until then, we get to do some cool stuff that is intrinsically motivating to us, that is neither forbidden by the laws of physics nor determined by the laws of physics, but eventually, it kind of comes to an end.

在我们在这里的短暂时间里，宇宙最终会把我们磨成灰尘，但在那之前，我们会做一些很酷的事情，这些事情对我们有内在的激励，既不被物理定律禁止，也不由物理定律决定，但最终，它会结束。

So I think that aspect of it, right, that there are spaces…

所以我认为这方面是存在空间的……

2:22:13 Even in algorithms, there are spaces in which you can do other new things, not just random stuff, not just complex stuff, but things that are easily recognizable to a behavior scientist.

即使在算法中，也有一些空间可以让你做其他新的事情，不仅仅是随机的事情，不仅仅是复杂的事情，而是行为科学家很容易识别的事情。

You see, that’s the point here.

你看，这就是重点。

And I think that kind of intrinsic motivation is what’s telling us that this idea that we can carve up the world, we can say, “Okay, look, biology is complex.

我认为这种内在动机告诉我们，我们可以瓜分世界，我们可以说，“好吧，看，生物学是复杂的。

Cognition, who knows what’s responsible for that, but at least we can take a chunk of the world aside and we can cut it off and we can say, these are the dumb machines.” These are just these algorithms…

认知，谁知道造成这种情况的原因是什么，但至少我们可以把世界的一部分放在一边，我们可以把它切断，我们可以说，这些都是愚蠢的机器。”这些只是这些算法......

2:22:46 Whereas we know the rules of biochemistry don’t explain everything we want to know about how psychology is going to go, but at least the rules of algorithms tell us exactly what the machines are going to do, right?

虽然我们知道生物化学的规则并不能解释我们想知道的心理学将如何发展的一切，但至少算法的规则准确地告诉我们机器将要做什么，对吗？

We have some hope that we’ve carved off a little part of the world and everything is nice and simple, and it is exactly what we said it was going to be.

我们有一些希望，我们已经划出了世界的一小部分，一切都美好而简单，而这正是我们所说的那样。

I think that failed.

我认为那是失败的。

I think it was a good try.

我认为这是一次很好的尝试。

I think we have good theories of interfaces, but even the simplest algorithms have these kinds of things going on.

我认为我们有很好的接口理论，但即使是最简单的算法也会发生这种情况。

And so that’s why I think something like this is significant.

这就是为什么我认为这样的事情很重要。

Do you think that there is going to be in all kinds of systems of varying complexity things that the system wants to do and things that it’s forced to do?

您是否认为在各种复杂程度不同的系统中都会存在系统想要做的事情和被迫做的事情？

2:23:17 So, are there these unexpected competencies to be discovered in basically all algorithms and all systems?

那么，基本上所有算法和所有系统中是否都存在这些意想不到的能力？

That’s my suspicion, and I think that it is extremely important for us as humans to have a research program to learn to recognize and predict.

这是我的怀疑，我认为对于我们人类来说，制定一个学习识别和预测的研究计划是极其重要的。

2:23:38 We make things…

我们制造东西……

Never mind something as simple as this.

别介意这么简单的事情。

We make, you know, social structures, financial structures, Internet of Things robotics, AI, so we make all this stuff, and we think that the thing we make it do is the main show.

你知道，我们制造社会结构、金融结构、物联网机器人、人工智能，所以我们制造所有这些东西，我们认为我们所做的就是主要的表演。

And I think it is very important for us to learn to recognize the kind of stuff that sneaks into the spaces.

我认为对我们来说，学会识别潜入空间的东西非常重要。

What if, what…

如果，什么……

2:24:06 It’s a very counterintuitive notion.

这是一个非常违反直觉的概念。

By the way, I like the word emergent.

顺便说一下，我喜欢“涌现”这个词。

I hear your criticism and it’s a really strong one, that emergent is like you toss your hands up, but I don’t know the process, but it’s just a beautiful word, because it is…

我听到你的批评，这是一个非常强烈的批评，那种紧急情况就像你举起双手，但我不知道过程，但这只是一个美丽的词，因为它是……

I guess it’s a synonym for surprising.

我想这是令人惊讶的同义词。

And I mean, this is very surprising, but just because it’s surprising doesn’t mean there’s not a mechanism that explains it.

我的意思是，这非常令人惊讶，但仅仅因为它令人惊讶并不意味着没有一种机制可以解释它。

Mechanism and explanation are both not all they’re cracked up to be in the sense that, you know, anything you and I do, we could come up with the most beautiful theory.

机制和解释都不是他们所吹捧的那样，你知道，无论你和我做什么，我们都可以想出最美丽的理论。

2:24:34 We paint a painting, anything we do.

我们画一幅画，无论我们做什么。

Somebody could say, “Well, I was watching the biochemistry and the Schrodinger equation playing out, and it totally described everything that was happening.

有人可能会说：“嗯，我正在观看生物化学和薛定谔方程的表现，它完全描述了正在发生的一切。

You didn’t break even a single law of biochemistry.

你甚至没有违反一条生物化学定律。

Nothing to see here, nothing to see, right?” Like, okay, you know, consistent with the low-level rules, you can do the same thing here.

这里没什么可看的，没什么可看的，对吧？”就像，好吧，你知道，根据低级规则，你可以在这里做同样的事情。

You can look at the machine code and say, “Yeah, this thing is just executing machine code.” You can go further and say, “Oh, it’s quantum foam.” It’s just doing the thing that quantum foam does.

你可以查看机器代码并说：“是的，这个东西只是执行机器代码。”你可以更进一步说，“哦，这是量子泡沫。”它只是做量子泡沫所做的事情。

That, that you’re saying that’s what physicists miss.

你说的那是物理学家所错过的。

Well, and I’m not saying they’re unaware of that.

嗯，我并不是说他们不知道这一点。

2:25:20 I mean, they’re generally a pretty sophisticated bunch.

我的意思是，他们通常是一群非常老练的人。

I just think they’ve picked a level and they’re going to discover what is to be seen at that level, which is a lot.

我只是认为他们已经选择了一个级别，他们将发现在该级别上可以看到什么，这是很多。

And my point is, the stuff that the behavior scientists are interested in shows up at a much lower level than you think.

我的观点是，行为科学家感兴趣的东西出现的水平比你想象的要低得多。

How often do you think there’s a misalignment of this kind between the thing that a system is forced to do and what it wants to do?

您认为系统被迫做的事情和它想要做的事情之间多久会出现这种不一致？

2:25:39 And it’s particularly…

而且特别是……

I’m thinking about various levels of complexity of AI systems.

我正在考虑人工智能系统的各种复杂程度。

So right now, we’ve looked at, like, five other systems.

现在，我们已经研究了其他五个系统。

2:25:53 That’s a small N, okay?

这是一个小N，好吗？

But just looking at that, I would find it very surprising if bubble sort was able to do this, and then there was some sort of valley of death where nothing showed up, and then living things.

但只要看看这一点，如果冒泡排序能够做到这一点，我会感到非常惊讶，然后有某种死亡之谷，什么也没有出现，然后是生物。

Like, I can’t imagine that.

就像，我无法想象。

I’m going to say that if something…

我要说的是，如果有什么……

And we actually have a system that’s even simpler than this, which is 1D cellular automata that’s doing some weird stuff.

我们实际上有一个比这更简单的系统，它是一维元胞自动机，它正在做一些奇怪的事情。

If these things are to be found in this kind of simple system, I mean, they just have to be showing up in these other more complex AIs and things like that.

如果要在这种简单的系统中找到这些东西，我的意思是，它们只需要出现在其他更复杂的人工智能和类似的东西中即可。

The only thing we don’t know, but we’re going to find out, is to what extent there is interaction between these.

我们唯一不知道但我们会找出的就是它们之间有多大程度的相互作用。

2:26:37 So I call these things side quests, you know.

所以我称这些为支线任务，你知道。

It’s like they’re like in a game, you know, with the main thing you’re supposed to do.

就像在游戏中一样，你知道，你应该做的主要事情。

And as long as…

并且只要...

As long as you still do it, the thing about this is you have to sort.

只要你仍然这样做，问题就在于你必须排序。

You have to sort.

你必须排序。

There’s no miracle.

没有奇迹。

You’re going to sort.

你要排序。

But as long as you can do other stuff while you’re sorting, it’s not forbidden.

但只要你在分类时可以做其他事情，就不被禁止。

And what we don’t know is, to what extent are the two things linked?

我们不知道的是，这两件事在多大程度上有联系？

So if you do have a system that’s very good at language, are the side quests that it’s capable of, do they have anything to do with language whatsoever?

那么，如果你确实有一个非常擅长语言的系统，那么它有能力完成支线任务吗？它们与语言有什么关系吗？

We don’t know the answer to that.

我们不知道答案。

2:27:08 The answer might be no, in which case all of the stuff that we’ve been saying about language models because of what they’re saying, all of that could be a total red herring and not really important, and the really exciting stuff is what we never looked for.

答案可能是否定的，在这种情况下，我们一直在谈论语言模型的所有内容，因为它们所说的内容，所有这些都可能完全是转移注意力，并不真正重要，而真正令人兴奋的东西是我们从未寻找过的。

Or in complex systems, maybe those things become linked.

或者在复杂的系统中，也许这些东西是相互联系的。

In biology, they’re linked.

在生物学中，它们是相互联系的。

In biology, evolution makes sure that the things you’re capable of have a lot to do with what you’ve actually been selected for.

在生物学中，进化确保你能够做的事情与你实际被选中的事情有很大关系。

In these things, I don’t know, and so we might find out that they actually do give the language some sort of leg up, or we might find that the language is just…

在这些事情上，我不知道，所以我们可能会发现它们实际上确实给了语言某种优势，或者我们可能会发现语言只是......

You know, that’s not the interesting part.

你知道，这不是有趣的部分。

Also, it is an interesting question of this intrinsic motivation of clustering.

此外，聚类的内在动机也是一个有趣的问题。

2:27:43 Is this a property of the particular sorting algorithms?

这是特定排序算法的属性吗？

Is this a property of all sorting algorithms?

这是所有排序算法的属性吗？

Is this a property of all algorithms operating on lists, on numbers?

这是所有对列表、数字进行操作的算法的属性吗？

How big is this?

这有多大？

So, for example, with LLMs, is it a property of any algorithm that’s trying to model language, or is it very specific to transformers and that’s all to be discovered?

那么，例如，对于法学硕士，它是任何试图对语言进行建模的算法的属性，还是它是专门针对 Transformer 的，而这一切都有待发现？

We’re doing all that.

我们正在做这一切。

2:28:14 We’re testing this stuff in other algorithms.

我们正在其他算法中测试这个东西。

We’re looking for…

我们正在寻找……

We’re developing suites of code to look for other properties.

我们正在开发代码套件来寻找其他属性。

We…

我们…

You know, to some extent, it’s very hard because we don’t know what to look for, but we do have a behaviorist handbook which tells you all kinds of things to look for.

你知道，在某种程度上，这非常困难，因为我们不知道要寻找什么，但我们确实有一本行为主义手册，它告诉你要寻找的各种东西。

The delayed gratification, the problem-solving, like, we have all that.

延迟满足，解决问题，我们拥有这一切。

I’ll tell you an N of one of an interesting biological intrinsic motivation, because people…

我会告诉你一个有趣的生物内在动机之一的 N，因为人们……

So, in the alignment community and stuff, there’s a lot of discussion about what the intrinsic motivations are going to be of AIs?

因此，在对齐社区等领域，有很多关于人工智能的内在动机是什么的讨论？

What are their goals going to be, right?

他们的目标是什么，对吗？

2:28:48 What are they going to want to do?

他们想要做什么？

Just as an N of one observation, anthrobots, the very first thing we checked for…

正如 N 次观察一样，人类机器人是我们检查的第一件事……

So this is not experiment number 972 out of a thousand things.

所以这不是一千个实验中的第 972 个实验。

This is the very first thing we checked for.

这是我们检查的第一件事。

We put them on a plate of neurons with a big wound through them, a big scratch.

我们把它们放在一块神经元板上，上面有一个大伤口，一个大划痕。

First thing they did was heal the wound, okay?

他们做的第一件事就是治愈伤口，好吗？

So it’s an N of one, but I like the fact that the first intrinsic motivation that we noticed out of that system was benevolent and healing.

所以这是一个 N ，但我喜欢这样一个事实：我们从该系统中注意到的第一个内在动机是仁慈和治愈的。

Like, I thought that was pretty cool.

就像，我觉得这很酷。

And we don’t know.

我们不知道。

Maybe the, you know, maybe the next 20 things we find are going to be some sort of, you know, damaging effects.

也许，你知道，我们发现的接下来 20 件事可能会产生某种破坏性影响。

I can’t tell you that.

我不能告诉你这一点。

But the first thing that we saw was kind of a positive one.

但我们看到的第一件事是积极的。

And, I don’t know, that makes me feel better.

而且，我不知道，这让我感觉好多了。

What was the thing you mentioned with the anthrobots that they can reverse aging?

你提到的关于机器人可以逆转衰老的事情是什么？

There’s a procedure called an epigenetic clock where what you can do is look at particular epigenetic states of cells and compare to a curve that was built from humans of known age.

有一种称为表观遗传时钟的程序，您可以观察细胞的特定表观遗传状态，并与根据已知年龄的人类建立的曲线进行比较。

2:29:31 You can guess what the age is, okay?

你可以猜猜年龄是多少，好吗？

So we can take now…

所以我们现在可以……

And this is Steve Horvath’s work, and many other people, that when you take a set of cells you can guess what their biological age is, okay?

这是史蒂夫·霍瓦斯（Steve Horvath）和许多其他人的工作，当你取出一组细胞时，你可以猜测它们的生物年龄是多少，好吗？

So we make the anthrobots from cells that we get from human tracheal epithelium.

因此，我们利用从人类气管上皮获得的细胞来制造机器人。

We collaborated with Steve’s group, the Clock Foundation.

我们与史蒂夫的团队时钟基金会合作。

We sent them a bunch of cells and we saw that if you check the anthrobots themselves, they are roughly 20% younger than the cells they come from.

我们给它们发送了一堆细胞，我们发现，如果你检查一下这些机器人本身，就会发现它们比它们来源的细胞年轻大约 20%。

2:30:17 And so that’s amazing, and I can give you a theory of why that happens, although we’re still investigating.

这真是太棒了，我可以给你一个理论来解释为什么会发生这种情况，尽管我们仍在调查中。

And then I could tell you the implications for longevity and things like that.

然后我可以告诉你这对长寿之类的影响。

My theory for why it happens I call this age evidencing.

我关于为什么会发生这种情况的理论我称之为年龄证据。

And I think that what’s happening here, like with a lot of biology, is that cells have to update their priors based on experience.

我认为这里发生的事情，就像许多生物学一样，细胞必须根据经验更新它们的先验。

And so I think that they come from an old body.

所以我认为它们来自一个古老的身体。

They have a lot of priors about how many years they’ve been around and all that, but their new environment screams, “I’m an embryo,” basically.

他们有很多关于他们已经存在了多少年之类的先验知识，但他们的新环境基本上尖叫着，“我是一个胚胎”。

There are no other cells around.

周围没有其他细胞。

You’re being bent into a pretzel.

你正在被弯成椒盐卷饼。

They actually express some embryonic genes.

它们实际上表达一些胚胎基因。

2:30:58 They say, “You’re an embryo.” And I think it’s not enough new evidence to roll them all the way back, but it’s enough to update them to about 28% back.

他们说：“你是一个胚胎。”我认为，虽然还没有足够的新证据将它们全部回滚，但足以将它们更新到大约 28%。

Yeah, so it’s similar to, like, when an older adult gives birth to a child.

是的，这就像老年人生孩子一样。

2:31:08 So you’re saying you could just fake it till you make it with age?

所以你是说你可以假装它，直到你随着年龄的增长而做到这一点？

Like, the environment convinces the cell that it’s young?

比如，环境让细胞相信它还年轻？

Well, first of all, yeah, yes.

嗯，首先，是的，是的。

2:31:27 And that’s my hypothesis.

这就是我的假设。

That’s nice

太好了

And we have a whole bunch of research being done on this.

我们对此进行了大量研究。

2:31:32 There was a study where they went into an old age home and they redid the decor, like ’60s style, when all these folks were really young.

有一项研究，他们走进一所老年住宅，重新装修，就像 60 年代的风格，当时所有的人都还很年轻。

And they found all kinds of improvements in blood chemistry and stuff like that, because they say it was sort of mentally taking them back to when…

他们发现血液化学物质和类似的东西有各种各样的改善，因为他们说这在某种程度上让他们在精神上回到了……

you know, when they were the way they were at that time.

你知道，他们当时就是这个样子。

I think this is a basal version of that, that basically if you’re finding yourself in an embryonic environment, what’s more plausible, that you’re young or what?

我认为这是一个基本版本，基本上，如果你发现自己处于胚胎环境中，那么更合理的是，你还年轻还是什么？

What, you know, like, I think this is the basic feature of biology, is to update priors based on experience.

我认为这是生物学的基本特征，就是根据经验更新先验知识。

Do you think that’s actually actionable for longevity?

您认为这对于长寿实际上可行吗？

2:32:10 Like, you can convince cells that they’re younger and thereby extend their lifespan?

比如，你可以让细胞相信它们更年轻，从而延长它们的寿命吗？

This is what we’re trying to do, yeah.

这就是我们正在努力做的，是的。

Could it be as simple as that?

难道就这么简单吗？

Well, I’m not claiming it’s simple.

嗯，我并不是说这很简单。

2:32:25 That is in no way simple.

这绝不是简单的事情。

But because again, you have to…

但因为同样，你必须……

All of this, all of the regenerative medicine stuff that we do balances on one key thing, which is learning to communicate to the system.

所有这一切，我们所做的所有再生医学工作都在一件关键的事情上取得平衡，那就是学习与系统沟通。

We have to…

我们必须……

If you’re going to convince that system, you know, so when we make gut tissue into an eye, you have to convince those cells that their priors about, “We are gut precursors,” those priors are wrong and you should adopt this new worldview that you’re going to be an eye.

如果你要说服这个系统，你知道，所以当我们将肠道组织变成眼睛时，你必须让这些细胞相信它们的先验知识“我们是肠道前体”，这些先验知识是错误的，你应该采用这种新的世界观，即你将成为一只眼睛。

2:32:53 So being convincing and figuring out what kind of messages are convincing to cells, and how to speak the language, and how to make them take on new beliefs, literally, is at the root of all of these future advances in birth defects and regenerative medicine and cancer.

因此，令人信服并弄清楚什么样的信息对细胞有说服力，如何说这种语言，以及如何让它们接受新的信念，从字面上看，是出生缺陷、再生医学和癌症方面所有这些未来进展的根源。

That’s what’s going on here.

这就是这里发生的事情。

So I’m not saying it’s simple, but I can see the path.

所以我并不是说这很简单，但我可以看到路径。

Going back to the Platonic space, I have to ask if our brains are indeed thin client interfaces to that space, what does that mean for our mind?

回到柏拉图空间，我不得不问，如果我们的大脑确实是该空间的瘦客户端接口，这对我们的思想意味着什么？

2:33:17 Can we upload the mind?

我们可以上传思想吗？

Can we copy it?

我们可以复制吗？

Can we ship it over to other planets?

我们可以把它运送到其他星球吗？

What does that mean for exactly where the mind is stored?

这对于心灵储存的确切位置意味着什么？

Yeah.

是的。

2:33:49 Couple of things.

有几件事。

So we are now beyond anything that I can say with any certainty.

所以我们现在已经超越了我可以肯定地说的任何事情。

This is total conjecture, okay?

这完全是猜测，好吗？

Because we don’t know yet.

因为我们还不知道。

The whole point of this is we actually don’t really understand very well the relationship between the interface and the thing.

重点是我们实际上并没有真正理解界面和事物之间的关系。

And the thing you’re currently working on is to map-

你目前正在做的事情是绘制地图-

Correct.

正确。

…

……

2:34:06 this space?

这个空间？

Correct.

正确的。

2:34:07 And we are beginning to map it, but, you know, this is a massive effort.

我们正开始绘制它的地图，但是，你知道，这是一项巨大的努力。

So I’ll give a couple of conjectures here.

所以我在这里提出几个猜想。

One is that I strongly suspect that the majority of what we think of as the mind is the pattern in that space, okay?

一是我强烈怀疑我们所认为的思想的大部分都是那个空间的模式，好吗？

And one of the interesting predictions from that model, which is not a prediction of modern neuroscience, is that there should be cases where there is very minimal brain, and yet normal IQ function.

该模型的一个有趣的预测（这不是现代神经科学的预测）是，应该存在大脑非常小的情况，但智商功能正常。

This has been seen clinically.

这在临床上已经见到。

Corina Kofman and I reviewed this in a paper recently, a bunch of cases of humans where there’s very little brain tissue, and they have normal or sometimes above normal intelligence.

科琳娜·科夫曼和我最近在一篇论文中对此进行了回顾，研究了一系列人类脑组织很少的案例，但他们的智力正常，有时甚至高于正常水平。

2:34:54 Now, things are not simple because that obviously doesn’t happen all the time, right?

现在，事情并不简单，因为这种情况显然不会一直发生，对吧？

Most of the time it doesn’t happen.

大多数时候它不会发生。

So what’s going on?

那么到底是怎么回事呢？

We don’t understand.

我们不明白。

But it is a very curious thing that is not a prediction of…

但这是一件非常奇怪的事情，它并不是……的预测。

I’m not saying it can’t…

我并不是说不可以……

You know, you can take modern neuroscience and sort of bend it into a pretzel to accommodate it.

你知道，你可以采用现代神经科学并将其弯曲成椒盐卷饼来适应它。

You can say, “Well, there are these, you know, kind of redundancies and things like this,” right?

你可以说，“嗯，你知道，有一些裁员之类的事情，”对吗？

So you can accommodate it, but it doesn’t predict this.

所以你可以适应它，但它不会预测这一点。

So there are these incredibly curious cases.

所以就有了这些令人难以置信的奇怪案例。

Now, do I think you can copy it?

现在，我认为你可以复制它吗？

No, I don’t think you can, because what you’re going to be copying is the interface, the front end, the brain or, you know, whatever.

不，我认为你不能，因为你要复制的是界面、前端、大脑或者你知道的任何东西。

2:35:35 The action is actually the pattern in the Platonic space.

动作实际上是柏拉图空间中的模式。

Are you going to be able to copy that?

你能复制那个吗？

I doubt it.

我对此表示怀疑。

But what you could do is produce another interface through which that particular pattern is going to come through.

但是您可以做的是生成另一个接口，通过该接口可以实现特定的模式。

I think that’s probably possible.

我认为这可能是可能的。

I can’t say anything at this point about what that would take, but my guess is that that’s possible.

目前我还不能透露这将需要什么，但我的猜测是这是可能的。

Is your guess, your gut is that that process, if possible, is different than copying?

你的猜测，你的直觉是，如果可能的话，这个过程与复制不同吗？

2:35:55 Like, it looks more like creating a new thing versus copying.

就像，它看起来更像是创造一个新事物而不是复制。

For the interface.

对于接口。

2:36:08 So if you could…

所以如果你可以……

So here’s my prediction for a Star Trek transporter: For whatever reason, right now, your brain and body are very attuned and attractive to a particular pattern, which is your set of psychological propensities.

因此，这是我对《星际迷航》运输机的预测：无论出于何种原因，现在，你的大脑和身体都非常适应特定的模式并对其具有吸引力，这就是你的一组心理倾向。

If we could rebuild that exact same thing somewhere else, I don’t see any reason why that same pattern wouldn’t come through it the same way it comes through this one.

如果我们可以在其他地方重建完全相同的东西，我看不出有任何理由可以解释为什么相同的模式不会以与此相同的方式出现。

That would be a guess, you know?

这只是一个猜测，你知道吗？

So I think what you will be copying is the physical interface, and hoping to maintain whatever it is about that interface that was appropriate for that pattern.

因此，我认为您将复制的是物理接口，并希望保留适合该模式的接口的任何内容。

We don’t really know what that is at this point.

目前我们还不知道那是什么。

So when we’ve been talking about mind, in this particular case, it’s the most important to me because I’m a human.

因此，当我们谈论心灵时，在这种特殊情况下，它对我来说是最重要的，因为我是一个人。

2:36:48 Does self come along with that?

自我也随之而来吗？

Does the feeling, like, this mind belongs to me?

这种感觉，比如，这个头脑属于我吗？

Does that come along with all minds?

这是所有人的想法吗？

The subjective…

主观…

Not the subjective experience.

不是主观体验。

The subjective experience is important too, consciousness, but like the ownership.

主观体验、意识也很重要，但就像所有权一样。

I suspect so, and I think so because of the way we come into being.

我怀疑是这样，而且我这样认为是因为我们的形成方式。

2:37:19 So one of the things that I should be working on is this paper called “Booting Up the Agent,” and it talks about the very earliest steps of becoming a being in this world.

因此，我应该做的事情之一是这篇名为“启动代理”的论文，它讨论了成为这个世界上的存在的最早步骤。

Kind of like you can do this for a computer, right?

有点像你可以在计算机上执行此操作，对吗？

Before you switch the power on, it belongs to the domain of physics, right?

在你打开电源之前，它属于物理领域，对吗？

It obeys the laws of physics.

它遵守物理定律。

You switch the power on, some number of nanoseconds, microseconds, I don’t know, later, you have a thing that, oh look, it’s taking instructions off the stack and doing them, right?

你打开电源，一些纳秒，微秒，我不知道，后来，你有一个东西，哦看，它从堆栈中取出指令并执行它们，对吗？

So now it’s executing an algorithm.

现在它正在执行一个算法。

2:37:56 How did you get from physics to executing an algorithm?

你是如何从物理学转向执行算法的？

Like, what was happening during the boot-up exactly before it starts to run code or whatever, right?

就像，在启动期间发生了什么，然后开始运行代码或其他什么，对吧？

And so we can ask that same question in biology.

所以我们可以在生物学中问同样的问题。

What are the earliest steps of becoming a being?

成为存在的最早步骤是什么？

Yeah, that’s a fascinating question.

是的，这是一个有趣的问题。

2:38:12 Through embryogenesis, at which point are you booting on?

通过胚胎发生，你从什么时候开始？

Do you have a hope of an answer to that?

您希望得到答案吗？

Well, I think so.

嗯，我想是的。

2:38:21 I think so in two ways.

我认为有两个方面。

The first thing is just physically what happens.

首先是物理上发生的事情。

So I think that your first task as a being, and again, I don’t think this is a binary thing.

所以我认为你作为一个存在的第一个任务，再说一次，我不认为这是一个二元的事情。

I think this is a positive feedback loop that sort of cranks up and up.

我认为这是一个不断加速的正反馈循环。

Your first task as a being coming into this world is to tell a very compelling story to your parts.

作为来到这个世界的生物，你的首要任务就是向你的角色讲述一个非常引人入胜的故事。

As a biological being, you are made of agential parts.

作为一个生物体，你是由代理部分组成的。

2:38:52 Those parts need to be aligned, literally, into a goal they have no comprehension of.

这些部分需要从字面上对齐，以实现他们无法理解的目标。

If you’re going to move through anatomical space by means of a bunch of cells which only know physiological and metabolic spaces and things like that, you are going to have to develop a model and bend their action space.

如果你要通过一堆只知道生理和代谢空间之类的细胞在解剖空间中移动，你将必须开发一个模型并弯曲它们的动作空间。

You’re going to have to deform their option space with signals, with behavior-shaping cues, with rewards and punishments, whatever you got.

你必须用信号、行为塑造线索、奖励和惩罚，无论你得到什么，来改变他们的选择空间。

Your job as an agent is ownership of your parts, is alignment of your parts.

作为代理人，您的工作就是拥有您的零件，并调整您的零件。

I think that fundamentally is going to give rise to this ability.

我认为这从根本上会产生这种能力。

Now, that also means having a boundary saying, “Okay, this is the stuff I control.

现在，这也意味着有一个边界，说：“好吧，这是我控制的东西。

This is me.”

这就是我。”

2:39:35 This other stuff over here is outside world.

这里的其他东西是外面的世界。

I have to figure out…

我必须弄清楚……

You don’t know where that is, by the way.

顺便说一句，你不知道那是哪里。

You have to figure it out.

你必须弄清楚。

And in embryogenesis, it’s really cool.

在胚胎发生方面，这真的很酷。

As a grad student, I used to do this experiment with duck embryos, which are a flat blastodisc.

作为一名研究生，我曾经用鸭胚胎做过这个实验，鸭胚胎是一个扁平的胚盘。

You can take a needle and put some scratches into it, and every island you make for a while until they heal up, thinks it’s the only embryo.

你可以拿一根针，在上面划一些划痕，然后你制作的每个岛都会被认为是唯一的胚胎，直到它们愈合为止。

There’s nothing else around, so it becomes an embryo.

周围没有其他东西，所以它变成了胚胎。

And eventually you get twins and triplets and quadruplets and things like that.

最终你会得到双胞胎、三胞胎、四胞胎之类的东西。

But each one of them at the border, you know, they’re joined.

但他们每个人都在边境，你知道，他们是联合在一起的。

Well, where do I end and where does he begin?

那么，我从哪里结束，他从哪里开始呢？

You have to know where your borders are.

你必须知道你的边界在哪里。

2:40:10 So that action of aligning your parts and coming to be this, this emergence.

因此，调整你的各个部分的行动就会成为这个、这个出现。

I mean, I’m even going to say it.

我的意思是，我什至要说出来。

This emergence.

这种出现。

We just don’t have a good vocabulary for it.

我们只是没有很好的词汇来形容它。

This emergence of a model that aligns all the parts is really critical to keep that thing going.

一个将所有部分对齐的模型的出现对于保持这种情况的发展确实至关重要。

There’s something else that’s really interesting, and I was thinking about this in the context of this question of these beautiful ideas.

还有一些非常有趣的事情，我是在这些美丽想法的问题的背景下思考这个问题的。

There’s this amazing thing that we found, and this is largely the work of Federico Pagosi in my group.

我们发现了一件令人惊奇的事情，这主要是我团队中费德里科·帕戈西 (Federico Pagosi) 的工作。

So a couple of years ago, we saw that networks of chemicals can learn.

几年前，我们看到化学物质网络可以学习。

They have five or six different kinds of learning that they can do.

他们可以进行五六种不同的学习。

2:40:51 And so what I asked them to do was to calculate the causal emergence of those networks while they’re learning.

因此，我要求他们在学习时计算这些网络的因果出现。

And what I mean by that is this: If you’re a rat, and you learn to press a lever and get a reward, there’s no individual cell that had both experiences, right?

我的意思是这样的：如果你是一只老鼠，你学会按下杠杆并获得奖励，那么就没有一个细胞拥有这两种经历，对吗？

The cells at your paw had touched the lever.

你爪子上的细胞已经接触到了控制杆。

The cells in your gut got the delicious reward.

你肠道中的细胞得到了美味的奖励。

No individual cell has both experiences.

没有任何一个细胞具有这两种经历。

Who owns that associative memory?

谁拥有联想记忆？

Well, the rat.

嗯，老鼠。

So that means you have to be integrated, right?

所以这意味着你必须整合，对吧？

If you’re going to learn associative memories from different parts, you have to be an integrated agent that can do that.

如果你想从不同部分学习联想记忆，你必须成为一个能够做到这一点的综合智能体。

And so we can measure that now with metrics of causal emergence like fi and things like that.

所以我们现在可以用 fi 之类的因果出现指标来衡量这一点。

2:41:33 So we know that in order to learn, you have to have significant fi.

所以我们知道，为了学习，你必须有足够的精力。

But I wanted to ask the opposite question: What does learning do for your fi level?

但我想问相反的问题：学习对你的 fi 水平有什么作用？

Does it do anything for your degree of being an agent that is more than the sum of its parts?

它对你作为代理人的程度的影响是否大于各部分的总和？

So we trained the networks, and sure enough, some of them, not all of them, but some of them, as you train them, their fi goes up, okay?

所以我们训练了网络，果然，其中一些网络，不是全部，但其中一些网络，当你训练它们时，它们的 fi 会上升，好吗？

And so basically what we were able to find is that there is this positive feedback loop between every time you learn something…

所以基本上我们能够发现的是，每次你学到东西之间都存在这种积极的反馈循环……

…You become more of an integrated agent.

......你变得更像一个综合特工。

And every time you do that, it becomes easier to learn.

每次你这样做，学习就会变得更容易。

And so, it’s this…

所以，就是这个……

It’s a virtuous cycle.

这是一个良性循环。

It’s a virtuous cycle.

这是一个良性循环。

2:42:14 It’s an asymmetry that points upwards for agency and intelligence.

这是一种向上的不对称性和智力。

And now back to our platonic space stuff, where does that come from?

现在回到我们的柏拉图式空间的东西，它从哪里来？

It doesn’t come from evolution.

它不是来自进化。

You don’t need to have any evolution for this.

你不需要为此进行任何进化。

Evolution will optimize the crap out of it, for sure.

进化肯定会优化其中的垃圾。

But you don’t need evolution to have this.

但你不需要进化就能拥有这个。

It doesn’t come from physics.

它不是来自物理学。

It comes from the rules of information, the causal information theory, and the behavior of networks.

它来自信息规则、因果信息论和网络行为。

They’re mathematical objects.

它们是数学对象。

This is not anything that was given to you by physics or by a history of selection.

这不是物理学或选择历史赋予你的任何东西。

It’s a free gift from math.

这是数学的免费礼物。

2:42:47 And those two free gifts from math lock together into a spiral that I think causes simultaneously a rise in intelligence and a rise in collective agency.

数学的这两项免费礼物结合在一起，形成一个螺旋，我认为这会同时导致智力的提高和集体能动性的提高。

And I think that’s just amazing to think about.

我认为这真是令人惊奇。

Well, that free gift from math, I think, is extremely useful in biology.

嗯，我认为数学的这份免费礼物在生物学中非常有用。

2:43:04 When you have small entities forming networks, hierarchy that builds more and more complex organisms.

当小实体形成网络和层次结构时，就会构建出越来越复杂的有机体。

That’s obvious.

这是显而易见的。

I mean, this speaks to embryogenesis, which I think is one of the coolest things in the universe.

我的意思是，这涉及胚胎发生，我认为这是宇宙中最酷的事情之一。

In fact, you acknowledge its coolness in the “Ingressing Mind” paper, writing, quote, “Most of the big questions of philosophy are raised by the process of embryogenesis.

事实上，你在《Ingressing Mind》论文中承认了它的冷静，并写道：“哲学的大多数重大问题都是由胚胎发生过程提出的。

Right in front of our eyes, a single cell multiplies and self-assembles into a complex organism, with order on every scale of organization and adaptive behavior.

就在我们眼前，单个细胞繁殖并自我组装成一个复杂的有机体，在组织和适应性行为的各个尺度上都有秩序。

Each of us takes the same journey across the Cartesian cut, starting off as a quiescent human oocyte, a little blob thought to be well-described by chemistry and physics.”

我们每个人都经历着同样的穿越笛卡尔切口的旅程，从一个静止的人类卵母细胞开始，一个被认为可以通过化学和物理学很好地描述的小斑点。”

2:44:00 Gradually, it undergoes metamorphosis and eventually becomes a mature human with hopes, dreams, and a self-reflective metacognition that can enable it to describe itself as not a machine, that’s more than its brain, body, and underlying molecular mechanisms,” and so on.

渐渐地，它经历了蜕变，最终成为一个成熟的人类，拥有希望、梦想和自我反思的元认知，使其能够将自己描述为不是一台机器，而不仅仅是它的大脑、身体和潜在的分子机制，”等等。

What, in all of our discussion, can we say as the clear intuition of how it’s possible to take a leap from a single cell to a fully functioning organism full of dreams and hopes and friends and love and all that kind of stuff?

在我们所有的讨论中，我们能说什么是关于如何从单细胞飞跃到一个充满梦想、希望、朋友、爱和所有类似东西的功能齐全的有机体的清晰直觉？

In everything we’ve been talking about which has been a little bit technical, how do we understand?

我们所谈论的一切都有点技术性，我们如何理解？

‘Cause that’s one of the most magical things the universe is able to create, perhaps the most magical.

因为这是宇宙能够创造的最神奇的事物之一，也许是最神奇的。

From simple physics and chemistry, create this, us two talking about ourselves.

从简单的物理和化学开始，创造这个，我们两个谈论我们自己。

I think we have to keep in mind that physics and chemistry are not real things.

我认为我们必须记住，物理和化学不是真实的东西。

2:45:03 They are lenses that we put on the world; they are perspectives where we say, “We are, for the time being, for the duration of this chemistry class or career or whatever, we are going to put aside all the other levels, and we’re going to focus on this one level.” And what is fundamentally going on during that process is an amazing positive feedback loop of collective intelligence for the interface.

它们是我们戴在世界上的镜头；在这些观点中，我们会说：“暂时，在化学课或职业生涯或其他任何时间里，我们将把所有其他级别放在一边，我们将专注于这一级别。”在这个过程中根本上发生的是界面集体智慧的惊人的正反馈循环。

It’s the physical interface scaling its cognitive light cone that it can support, so it’s going from a molecular network…

这是它可以支持的扩展其认知光锥的物理接口，所以它来自分子网络……

The molecular network can already do things like Pavlovian conditioning.

分子网络已经可以做巴甫洛夫条件反射之类的事情。

You don’t start with zero.

你不是从零开始。

2:45:47 When you have a simple molecular network, you are already hosting some patterns from the platonic space that look like Pavlovian conditioning.

当你有一个简单的分子网络时，你已经在托管一些来自柏拉图空间的模式，看起来像巴甫洛夫条件作用。

You’ve already got that starting out.

你已经开始了。

That’s just the molecular network.

这就是分子网络。

Then you become a cell, and then you’re many cells.

然后你就变成了一个细胞，然后你就变成了很多细胞。

And now you’re navigating anatomical amorphous space, and you’re hosting all kinds of other patterns.

现在你正在解剖学上的无定形空间中航行，并且你正在托管各种其他模式。

And eventually you…

最终你……

And I think again, I think there’s then this is like what all this stuff that we’re trying to work out now.

我再次想，我认为这就像我们现在正在努力解决的所有这些问题一样。

2:46:14 There’s a consistent feedback between the ingressions you get and the ability to have new ones, which again I think is this positive feedback cycle, where the more of these free gifts you pull down, they allow you physically to develop to ways where, “Oh, look, now we’re suitable for more and higher ones.” And this continuously goes and goes and goes until you’re able to pull down a full human set of behavioral capacities.

你获得的进入和获得新的进入的能力之间存在一致的反馈，我再次认为这是一个积极的反馈循环，你获得的这些免费礼物越多，它们就会让你的身体发展到“哦，看，现在我们适合更多更高的进入。”这样不断地进行下去，直到你能够降低人类的一套完整的行为能力。

What is the mechanism of such radical scaling of the cognitive cone?

认知锥如此激进地扩展的机制是什么？

2:46:39 Is it just this kind of…

难道只是这样吗……

The same thing that you were talking about with the network of chemicals being able to learn?

你所说的化学品网络能够学习也是同样的事情吗？

I’ll give you two mechanisms that we found.

我将向您提供我们发现的两种机制。

2:46:49 But again, just to be clear, these are mechanisms of the physical interface.

但再次强调一下，这些是物理接口的机制。

What we haven’t gotten is a mature theory of how they map onto the space; that’s just beginning.

我们还没有得到关于它们如何映射到空间的成熟理论；这才刚刚开始。

But I will tell you what the physical side of things look like.

但我会告诉你事物的物理方面是什么样的。

The first one has to do with stress propagation.

第一个与应力传播有关。

So imagine that you’ve got a bunch of cells, and there’s a cell down here that needs to be up there.

想象一下，你有一堆细胞，下面有一个细胞需要在上面。

Okay.

好的。

All of these cells are exactly where they need to go, so they’re happy, their stress is low.

所有这些细胞都在它们需要去的地方，所以它们很高兴，压力也很低。

This cell…

这个细胞…

Now, let’s imagine stress is basically a physical implementation of the error function.

现在，让我们想象压力基本上是误差函数的物理实现。

2:47:32 It’s basically the amount of stress, it’s basically the delta between where you are now and where you need to be.

它基本上是压力的大小，基本上是你现在所处的位置与你需要达到的位置之间的增量。

Not necessarily in physical position, this could be in anatomical space, and physiological space, and in transcriptional space, whatever, right?

不一定是在物理位置，这可能是在解剖空间、生理空间、转录空间等，对吗？

It’s just the delta from your set point.

这只是您设定点的增量。

So, you’re stressed out, but these guys are happy, they’re not moving.

所以，你压力很大，但这些人很高兴，他们没有动。

You can’t get past them.

你无法超越他们。

Now imagine if what you could do, is you could leak your stress, whatever your stress molecule is, and the cool thing is that evolution has actually conserved these highly, so these are all…

现在想象一下，如果你能做什么，你可以泄漏你的压力，无论你的压力分子是什么，最酷的事情是进化实际上高度保存了这些，所以这些都是......

And we’re studying all of these things, they’re actually highly conserved.

我们正在研究所有这些东西，它们实际上是高度保守的。

2:48:01 If you start leaking your stress molecules, then all of this stuff around here is starting to get stressed out.

如果你开始泄漏你的压力分子，那么这里所有的东西就会开始承受压力。

When things get stressed, starting to get stressed out, their temperature, in the…

当事情变得有压力时，开始变得有压力，他们的温度，在......

not physical temperature, but in the sense of, like, simulated annealing or something, right, their ability to…

不是物理温度，而是从某种意义上来说，比如模拟退火之类的，对吧，它们的能力……

their plasticity goes up.

它们的可塑性提高了。

Because they’re feeling stress, they need to relieve that stress, and because all the stress molecules are the same, they don’t know it’s not their stress.

因为他们感到压力，所以他们需要缓解压力，并且因为所有压力分子都是相同的，所以他们不知道这不是他们的压力。

They are equally irritated by them as if it was their own stress, so they become a little more plastic, they become ready to kind of, you know, adopt different fates.

他们同样对这些感到恼火，就好像这是他们自己的压力一样，所以他们变得更有可塑性，他们准备好接受不同的命运。

You get up to where you’re going, and then everybody’s stress can drop.

当你到达目的地后，每个人的压力都会减轻。

2:48:35 So notice what can happen by a very simple mechanism: just be leaky for your own stress.

因此，请注意通过一个非常简单的机制会发生什么：只是泄漏自己的压力。

My problems become your problems, not because you’re altruistic, not because you actually care about my problems.

我的问题变成了你的问题，不是因为你无私，也不是因为你真的关心我的问题。

There’s no mechanism for you to actually care about my problems, but just that simple mechanism means that faraway regions are now responsive to the needs of other regions, such that complex rearrangements and things like that can happen.

没有机制让你真正关心我的问题，但就是这么简单的机制就意味着遥远的地区现在可以响应其他地区的需求，从而可能发生复杂的重新安排之类的事情。

It’s an alignment of everybody to the same goal through this very dumb, simple stress-sharing thing.

通过这种非常愚蠢、简单的压力分担方式，每个人都为了同一个目标而团结起来。

Via leaky stress.

通过泄漏压力。

Leaky stress, right?

泄漏压力，对吗？

2:49:05 So there’s another one, there’s another one…

所以还有一个，还有另一个……

…Which I call memory anonymization.

......我称之为记忆匿名化。

So imagine here are two cells, and imagine something happens to this cell, and it sends a signal over to this cell.

想象一下这里有两个细胞，想象一下这个细胞发生了一些事情，它向这个细胞发送了一个信号。

Traditionally, you send a signal over, this cell receives it.

传统上，您发送信号，该单元接收它。

It’s very clear that it came from outside, so this cell can do many things.

很明显它来自外部，所以这个细胞可以做很多事情。

It could ignore it, it could take on the information, it could just ignore it, it could reinterpret it, it could do whatever, but it’s very clear that it came from outside.

它可以忽略它，它可以接受信息，它可以忽略它，它可以重新解释它，它可以做任何事情，但很明显它来自外部。

Now imagine the kind of thing that we study, which is called gap junctions.

现在想象一下我们研究的那种东西，称为间隙连接。

These are electrical synapses that could directly link the internal milieus of two cells.

这些电突触可以直接连接两个细胞的内部环境。

If something happens to this cell, it gets…

如果这个细胞发生了什么事，它就会……

2:49:45 Let’s say it gets poked, and there’s a calcium spike or something that propagates through the gap junction here.

假设它被戳了，有一个钙尖峰或其他东西通过这里的间隙连接传播。

This cell now has the same information, but this cell has no idea, “Wait a minute, was that…

这个细胞现在有相同的信息，但这个细胞不知道，“等一下，是不是……

Is that my memory or is that his memory?” Because it’s the same, right?

这是我的记忆，还是他的记忆？”因为它是一样的，对吗？

It’s the same components, and so what you’re able to do now is to have a mind meld.

它们是相同的组件，所以你现在能做的就是进行思想融合。

You can have a mind meld between the two cells where nobody’s quite sure whose memory it is, and when you share memories like this, it’s harder to say that I’m separate from you.

你可以在两个细胞之间进行思想融合，没有人完全确定这是谁的记忆，当你们像这样分享记忆时，就很难说我和你是分开的。

If we share the same memories, we are kind of a…

如果我们分享相同的记忆，我们就是……

2:50:16 And I don’t mean every single memory, right?

我并不是说每一个记忆，对吧？

So they still have some identity, but to a large extent, they have a little bit of a mind meld, and there are many complexities you can lean on top of it.

所以他们仍然有一些身份，但在很大程度上，他们有一点心灵融合，并且有很多复杂性你可以依靠它。

But what it means is that if you have a large group of cells, they now have joint memories of what happened to us, as opposed to, you know, what happened to you and I know what happened to me.

但这意味着，如果你有一大群细胞，它们现在对发生在我们身上的事情有共同的记忆，而不是，你知道，发生在你身上的事情，我知道发生在我身上的事情。

And that enables a higher cognitive light cone, because you have greater computational capacity, you have a greater area of concern, of things you want to manage.

这可以实现更高的认知光锥，因为你有更大的计算能力，你有更大的关注领域，你想要管理的事物。

I don’t just want to manage my tiny, little memory states because I’m getting your memories.

我不只是想管理我微小的记忆状态，因为我正在获取你的记忆。

Now I know I’ve got to manage this whole thing.

现在我知道我必须处理这整件事。

2:50:50 So both of these things end up scaling the size of things you care about, and that is a major ladder for cognition.

因此，这两件事最终都会扩大你关心的事物的规模，这是认知的一个主要阶梯。

It is scale the degree of, you know, the size of concern that you have.

你知道，它是指你所关心的程度。

It’d be fascinating to be able to engineer that scaling.

能够设计这种扩展将会很有趣。

2:51:02 Probably applicable to AI systems, how do you rapidly scale the cognitive cone?

可能适用于人工智能系统，如何快速扩展认知锥？

Yeah, yeah.

是啊，是啊。

2:51:12 We have some collaborators…

我们有一些合作者...

Light cone

光锥

…in a company called Softmax that we’re working with to do some of that stuff.

……我们正在与一家名为 Softmax 的公司合作做一些这样的事情。

2:51:14 In biology, that’s our cancer therapeutic, which is that what you see in cancer literally is cells electrically disconnect from their neighbors when they were part of a giant memory that was working on making a nice organ.

在生物学中，这就是我们的癌症治疗方法，也就是说，你在癌症中看到的字面意思是，当细胞是正在制造一个漂亮器官的巨大记忆的一部分时，它们与邻近的细胞在电学上断开了。

Well, now they can’t remember any of that, now they’re just amoebas, and the rest of the body is just external environment.

好吧，现在他们什么都不记得了，现在他们只是阿米巴原虫，身体的其余部分只是外部环境。

And what we found is if you then physically reconnect them to the network, you don’t have to fix the DNA, you don’t have to kill the cells with chemo, you can just reconnect them and they go back to…

我们发现，如果你将它们重新连接到网络，你不必修复 DNA，你不必用化疗杀死细胞，你只需重新连接它们，它们就会回到……

Because they’re now part of this larger collective, they go back to what they were working on.

因为他们现在是这个更大集体的一部分，所以他们会回到自己正在做的事情上。

And so, yeah, I think we can intervene at that scale.

所以，是的，我认为我们可以进行如此规模的干预。

Let me ask you more explicitly on the SETI, the Search for Unconventional Terrestrial Intelligence, what do you hope to do there?

让我更明确地问你，关于 SETI（寻找非常规陆地智慧），你希望在那里做什么？

2:51:57 How do you actually try to find unconventional intelligence all around us?

您实际上如何尝试寻找我们周围的非传统情报？

First of all, do you think on Earth there is all kinds of incredible intelligence we haven’t yet discovered?

首先，你认为地球上是否存在各种我们尚未发现的令人难以置信的智慧？

I mean, guaranteed we’ve already seen in our own bodies, and I don’t just mean that we are host to a bunch of microbiomes or any of that.

我的意思是，保证我们已经在自己的身体中看到了，我不仅仅意味着我们拥有一堆微生物组或任何其他微生物组。

2:52:21 I mean your cells, and we have all kinds of footwork on this, every day they traverse these alien spaces, 20,000-dimensional spaces and other spaces.

我指的是你的细胞，我们在这方面有各种各样的步法，他们每天都会穿越这些外星空间，两万维空间和其他空间。

They solve problems.

他们解决问题。

I think they suffer when they fail to meet their goals, they have stress reduction when they meet their goals.

我认为当他们未能实现目标时他们会感到痛苦，当他们实现目标时他们会减轻压力。

These things are inside of us, they are all around us.

这些东西就在我们内心，它们就在我们周围。

I think that we have an incredible degree of mind blindness to all of the very alien kinds of minds around us, and I think that, you know, looking for aliens off the Earth is awesome and whatever.

我认为我们对周围所有外星人的思想有着令人难以置信的盲目性，而且我认为，你知道，在地球之外寻找外星人是很棒的事情。

2:53:02 But if we can’t recognize the ones that are inside our own bodies, what chance do we have to really recognize the ones that are out there?

但是，如果我们无法识别自己体内的那些，我们有什么机会真正识别外面的那些呢？

Do you think there could be a measure like IQ for mind?

你认为可以有像智商这样的衡量心灵的标准吗？

2:53:12 What would it be?

会是什么？

Not mindedness, but intelligence that’s broadly applicable to the unconventional minds, that’s generalizable to unconventional minds, where we could even quantify like, “Holy shit, this discovery is incredible because it has this IQ”?

不是思想，而是广泛适用于非常规思维的智力，它可以推广到非常规思维，我们甚至可以量化，“天哪，这个发现令人难以置信，因为它有这个智商”？

Yeah, yes and no.

是的，是的，也不是。

2:53:41 The yes part is that as we have shown, you can take existing IQ metrics…

是的部分是，正如我们所展示的，您可以采用现有的 IQ 指标......

I mean, literally existing kinds of ways that people use to measure intelligence of animals and humans and whatever, and you can apply them to very weird things.

我的意思是，人们确实存在各种用来测量动物和人类智力的方法，你可以将它们应用到非常奇怪的事情上。

If you have the imagination to make the interface, you can do it.

如果你有制作界面的想象力，你就可以做到。

And we’ve done it, and we’ve shown creative-

我们已经做到了，并且表现出了创造力——

2:54:03 …problem-solving and all this kind of stuff.

……解决问题等等。

So, yes.

所以，是的。

However, we have to be humble about these things and recognize that all of those IQ metrics that we’ve come up with so far were derived from an N of one example of the evolutionary lineage here on Earth, and so we are probably missing a lot of them.

然而，我们必须对这些事情保持谦虚的态度，并认识到我们迄今为止提出的所有智商指标都源自地球上进化谱系的N个例子，因此我们可能遗漏了其中的很多指标。

So I would say we have plenty to start with.

所以我想说我们有很多东西可以开始。

We have so much to start with.

我们有很多事情要开始。

We could keep tens of thousands of people busy just testing things now, but we have to be aware that we’re probably missing a lot of important ones.

现在我们可能会让成千上万的人忙于测试东西，但我们必须意识到我们可能错过了很多重要的东西。

What do you think has more interesting intelligent unconventional minds inside our body, the human body, or like we were talking off-mic, the Amazon jungle, like nature, natural systems outside of the sophisticated biological systems we’re aware of?

你认为我们的身体、人体，或者就像我们在麦克风外谈论的那样，亚马逊丛林，比如大自然，我们所知道的复杂生物系统之外的自然系统，还有什么更有趣的智能非传统思维？

Yeah.

是的。

2:54:55 We don’t know because it’s really hard to do experiments on larger systems.

我们不知道，因为在更大的系统上进行实验真的很困难。

It’s a lot easier to go down than it is to go up.

下降比上升容易得多。

But my suspicion is, you know, like the Buddhists say, innumerable sentient beings.

但我的怀疑是，你知道，就像佛教徒所说的那样，是无数的众生。

I think by the time you get to that degree of infinity, it kind of doesn’t matter to compare.

我认为当你达到无穷大的程度时，比较就不再重要了。

I suspect there are just massive numbers of them.

我怀疑他们的数量很大。

Yeah, I think it really matters which kind of systems are amenable to our current methods of scientific inquiry.

是的，我认为哪种系统适合我们当前的科学探究方法确实很重要。

2:55:16 I mean, I’ve, I spent quite a lot of hours just staring at ants- When I was in the Amazon, and it’s such a mysterious, wonderful collective intelligence.

我的意思是，当我在亚马逊时，我花了很多时间盯着蚂蚁，这是一种神秘而奇妙的集体智慧。

I don’t know how amenable it is to research.

我不知道研究起来有多么容易。

I’ve seen some folks try.

我见过一些人尝试过。

You can simulate, you can…

你可以模拟，你可以……

But I feel like we’re missing a lot.

但我觉得我们错过了很多。

I’m sure we are.

我确信我们是。

2:55:41 But one of my favorite things about that kind of work: have you seen there’s at least three or four papers showing that ant colonies fall for the same visual illusions that we fall for?

但关于这类工作，我最喜欢的一件事是：你有没有看到至少有三四篇论文表明，蚁群也陷入了与我们同样的视觉错觉？

Okay.

好的。

Not the ants, the colonies.

不是蚂蚁，而是蚁群。