Dr. Terry Sejnowski: How to Improve at Learning Using Neuroscience & AI

Terry Sejnowski 博士：如何利用神经科学和人工智能提高学习能力

2024-11-18 | 官方页面 YouTube 官方音频

Andrew Huberman:

安德鲁·休伯曼：

Welcome to the Huberman Lab podcast, where we discuss science and science-based tools for everyday life.

欢迎来到休伯曼实验室播客，我们在这里讨论科学和基于科学的日常生活工具。

I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine.

我是安德鲁·胡伯曼，斯坦福大学医学院神经生物学和眼科教授。

My guest today is Dr. Terry Sejnowski.

今天我的嘉宾是 Terry Sejnowski 博士。

Dr. Terry Sejnowski is a professor at the Salk Institute for Biological Studies, where he directs the Computational Neurobiology Laboratory.

Terry Sejnowski 博士是索尔克生物研究所的教授，负责指导计算神经生物学实验室。

And as his title suggests, he is a computational neuroscientist.

That is, he uses math as well as artificial intelligence and computing methods to understand this overarching, ultra-important question of how the brain works.

也就是说，他使用数学、人工智能和计算方法来理解大脑如何工作这个首要的、极其重要的问题。

Now, I realize that when people hear terms like computational neuroscience, algorithms, large language models, and AI, that it can be a bit overwhelming and even intimidating.

现在，我意识到，当人们听到计算神经科学、算法、大型语言模型和人工智能等术语时，可能会有点不知所措，甚至令人生畏。

But I assure you that the purpose of Dr. Sejnowski's work, and indeed today's discussion, is all about using those methods to clarify how the brain works, and indeed, to simplify the answer to that question.

但我向你们保证，Sejnowski 博士的工作以及今天讨论的目的都是为了使用这些方法来阐明大脑是如何工作的，并且实际上是为了简化该问题的答案。

So for instance, today you will learn that regardless of who you are, regardless of your experience, that all your motivation in all domains of life is governed by a simple algorithm or equation.

例如，今天您将了解到，无论您是谁，无论您的经验如何，您在生活各个领域的所有动机都受一个简单的算法或方程控制。

Dr. Sejnowski explains how a single rule, a single learning rule, drives all of our motivation-related behaviors.

Sejnowski 博士解释了一条规则、一条学习规则如何驱动我们所有与动机相关的行为。

And it, of course, relates to the neuromodulator dopamine.

当然，它与神经调节剂多巴胺有关。

And if you're familiar with dopamine as a term, today you will really understand how dopamine works to drive your levels of motivation or, in some cases, lack of motivation, and how to overcome that lack of motivation.

如果您熟悉多巴胺这个术语，那么今天您将真正了解多巴胺如何提高您的动力水平，或者在某些情况下提高动力缺乏，以及如何克服动力缺乏。

Today, we also discuss how best to learn.

Dr. Sejnowski shares not just information about how the brain works, but also practical tools that he and colleagues have developed, including a zero-cost online portal that teaches you how to learn better based on your particular learning style, the way that you, in particular, forage for information and implement that information.

Sejnowski 博士不仅分享有关大脑如何工作的信息，还分享他和同事开发的实用工具，包括一个零成本的在线门户，教你如何根据你的特定学习风格更好地学习，特别是你寻找信息和应用这些信息的方式。

Dr. Sejnowski also explains how he himself uses physical exercise of a particular type in order to enhance his cognition.

Sejnowski 博士还解释了他自己如何使用特定类型的体育锻炼来增强他的认知能力。

That is, his brain's ability to learn information and to come up with new ideas.

也就是说，他的大脑学习信息和提出新想法的能力。

Today, we also discuss both the healthy brain and the diseased brain in conditions like Parkinson's and Alzheimer's, and how particular tools that relate to mitochondrial function can perhaps be used in order to treat various diseases, including Alzheimer's dementia.

今天，我们还讨论了帕金森氏症和阿尔茨海默氏症等疾病的健康大脑和患病大脑，以及如何使用与线粒体功能相关的特定工具来治疗各种疾病，包括阿尔茨海默氏痴呆症。

I'm certain that by the end of today's episode, you will have learned a tremendous amount of new knowledge about how your brain works and practical tools that you can implement in your daily life.

我确信，在今天的节目结束时，您将学到大量有关大脑如何工作的新知识以及可以在日常生活中使用的实用工具。

Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford.

在开始之前，我想强调一下，这个播客与我在斯坦福大学的教学和研究角色是分开的。

It is, however, part of my desire and effort to bring zero-cost to consumer information about science and science-related tools to the general public.

然而，我的愿望和努力的一部分是向公众提供有关科学和科学相关工具的零成本消费者信息。

In keeping with that theme, I'd like to thank the sponsors of today's podcast.

为了与这个主题保持一致，我要感谢今天播客的赞助商。

Our first sponsor is BetterHelp.

我们的第一个赞助商是 BetterHelp。

BetterHelp offers professional therapy with a licensed therapist carried out completely online.

BetterHelp 提供由持照治疗师完全在线进行的专业治疗。

I've been doing weekly therapy for well over 30 years.

三十多年来我每周进行一次治疗。

Initially, I didn't have a choice.

最初，我别无选择。

It was a condition of being allowed to stay in school.

这是被允许留在学校的一个条件。

But pretty soon I realized that therapy is an extremely important component to one's overall health.

但很快我就意识到治疗对于一个人的整体健康来说是极其重要的组成部分。

In fact, I consider doing regular therapy just as important as getting regular exercise, including cardiovascular exercise and resistance training, which of course, I also do every single week.

事实上，我认为定期治疗与定期锻炼一样重要，包括心血管锻炼和阻力训练，当然，我每周都会进行这些锻炼。

Now, there are essentially three things that great therapy provides.

现在，伟大的治疗基本上可以提供三件事。

First of all, it provides a good rapport with somebody that you can trust and talk to about essentially all issues that you want to.

首先，它与您可以信任的人建立了良好的融洽关系，并且可以与您谈论几乎所有您想要讨论的问题。

Second of all, great therapy provides support in the form of emotional support or simply directed guidance, what to do or what not to do in given areas of your life.

其次，伟大的治疗以情感支持或简单的定向指导的形式提供支持，告诉你在生活的特定领域该做什么或不该做什么。

And third, expert therapy can provide you useful insights that you would not have been able to arrive at on your own.

第三，专家治疗可以为您提供您自己无法获得的有用见解。

BetterHelp makes it very easy to find an expert therapist who you really resonate with and that can provide you the benefits I just mentioned that come with effective therapy.

BetterHelp 可以让您轻松找到与您真正产生共鸣的专家治疗师，并且可以为您提供我刚才提到的有效治疗所带来的好处。

If you'd like to try BetterHelp, go to betterhelp.com/huberman to get 10% off your first month.

如果您想尝试 BetterHelp，请访问 betterhelp.com/huberman，第一个月可享受 10% 的折扣。

Again, that's betterhelp.com/huberman.

再说一次，这是 betterhelp.com/huberman。

Today's episode is also brought to us by Helix Sleep.

今天的节目也是由 Helix Sleep 为我们带来的。

Helix Sleep makes mattresses and pillows that are customized to your unique sleep needs.

Helix Sleep 生产根据您独特的睡眠需求定制的床垫和枕头。

Now, I've spoken many times before on this and other podcasts about the fact that getting a great night's sleep is the foundation of mental health, physical health, and performance.

现在，我之前已经在这个播客和其他播客中多次谈到这样一个事实：睡个好觉是心理健康、身体健康和表现的基础。

Now, the mattress you sleep on makes a huge difference in terms of the quality of sleep that you get each night.

现在，您所睡的床垫会对您每晚的睡眠质量产生巨大影响。

How soft it is or how firm it is, how breathable it is, all play into your comfort and need to be tailored to your unique sleep needs.

它的柔软程度、硬度、透气程度都会影响您的舒适度，并且需要根据您独特的睡眠需求进行定制。

If you go to the Helix website, you can take a brief two-minute quiz, and it asks you questions such as, do you sleep on your back, your side, or your stomach?

如果你访问 Helix 网站，你可以做一个两分钟的简短测验，它会问你一些问题，比如你是仰卧、侧卧还是俯卧？

Do you tend to run hot or cold during the night?

你晚上容易感到热还是冷？

Things of that sort.

诸如此类的事情。

Maybe you know the answers to those questions, maybe you don't.

也许您知道这些问题的答案，也许您不知道。

Either way, Helix will match you to the ideal mattress for you.

无论哪种方式，Helix 都会为您匹配理想的床垫。

For me, that turned out to be the Dusk mattress, D-U-S-K.

对我来说，这就是 Dusk 床垫，D-U-S-K。

I started sleeping on a Dusk mattress about three and a half years ago, and it's been far and away the best sleep that I've ever had.

大约三年半前，我开始睡在 Dusk 床垫上，这无疑是我睡过的最好的睡眠。

If you'd like to try Helix, you can go to helixsleep.com/huberman.

如果您想尝试 Helix，可以访问 helixsleep.com/huberman。

Take that two-minute sleep quiz, and Helix will match you to a mattress that is customized for your unique sleep needs.

For the month of November 2024, Helix is giving up to 25% off on all mattress orders and two free pillows.

2024 年 11 月，Helix 为所有床垫订单提供高达 25% 的折扣，并免费提供两个枕头。

Again, that's helixsleep.com/huberman to get up to 25% off and two free pillows.

再次强调，helixsleep.com/huberman 提供高达 25% 的折扣和两个免费枕头。

And now for my discussion with Dr. Terry Sejnowski.

现在我将与 Terry Sejnowski 博士进行讨论。

Dr. Terry Sejnowski, welcome.

Terry Sejnowski 博士，欢迎光临。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Great to be here.

很高兴来到这里。

Andrew Huberman:

安德鲁·休伯曼：

We go way back, and I'm a huge fan of your work because you've worked on a great many different things in the field of neuroscience.

我们可以追溯到很久以前，我是你工作的超级粉丝，因为你在神经科学领域从事过很多不同的工作。

You're considered by many a computational neuroscience, so you bring mathematical models to an understanding of the brain and neural networks.

许多人认为您是计算神经科学领域的专家，因此您利用数学模型来理解大脑和神经网络。

And we're also going to talk about AI today, and we're going to make it accessible for everybody, biologist or no, math background or no. To kick things off, I want to understand something.

今天我们还将讨论人工智能，我们将使每个人都可以使用它，无论是否是生物学家，无论是否有数学背景。首先，我想了解一些事情。

I understand a bit about the parts list of the brain, and most listeners of this podcast will understand a little bit of the parts list of the brain, even if they've never heard an episode of this podcast before, because they understand there are cells, those cells are neurons, those neurons connect to one another in very specific ways that allow us to see, to hear, to think, et cetera.

我对大脑的组成部分有一点了解，这个播客的大多数听众都会了解一点大脑的组成部分，即使他们以前从未听过这个播客的一集，因为他们知道有细胞，这些细胞是神经元，这些神经元以非常特定的方式相互连接，使我们能够看到、听到、思考等等。

But I've come to the belief that even if we know the parts list, it doesn't really inform us how the brain works.

但我开始相信，即使我们知道零件清单，它也并不能真正告诉我们大脑是如何工作的。

This is the big question, how does the brain work?

这是一个大问题，大脑是如何工作的？

What is consciousness?

什么是意识？

All of this stuff.

所有这些东西。

So where and how does an understanding of how neurons talk to one another start to give us a real understanding about how the brain works?

那么，了解神经元如何相互交谈从哪里以及如何开始让我们真正了解大脑的工作原理呢？

What is this piece of meat in our heads?

Because it can't just be, okay, the hippocampus remembers stuff, and the visual cortex perceives stuff.

因为它不可能只是海马体记住东西，视觉皮层感知东西。

When you sit back and you remove the math from the mental conversation, if that's possible for you, how do you think about, quote unquote, "how the brain works?" At a very basic level, what is this piece of meat in our heads really trying to accomplish?

当你坐下来，把数学从心理对话中剔除时，如果这对你来说是可能的，你会如何思考，直接引用“大脑是如何工作的？”从最基本的层面来看，我们大脑中的这块肉真正想要完成什么？

From, let's just say the time when we first wake up in the morning and we're a little groggy, till we make it to that first cup of coffee or water.

从我们早上第一次醒来，有点昏昏沉沉的时间开始，直到我们喝第一杯咖啡或水。

Or maybe even just to urinate first thing in the morning.

或者甚至可能只是早上第一件事就是小便。

What is going on in there?

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

What a great question.

多么好的问题啊。

And, Pat Churchland and I wrote a book, "Computational Brain," and in it, there's this levels diagram.

而且，帕特·丘奇兰和我写了一本书，《计算大脑》，里面有这个层次图。

And levels of investigation at different spatial scales from the molecular at the very bottom to synapses and neurons, circuits, neural circuits, how they're connected with each other, and then brain areas in the cortex, and then the whole central nervous system span 10 orders of magnitude, 10th to the 10th in spatial scale.

不同空间尺度上的研究，从最底层的分子到突触和神经元，神经回路，神经回路，它们是如何相互连接的，然后是皮层的大脑区域，然后是整个中枢神经系统，跨越了10个数量级，空间尺度上的10到10。

So, where is consciousness in all of that?

So, there are two approaches that neuroscientists have taken.

因此，神经科学家采取了两种方法。

I shouldn't say neuroscientists, I should say that scientists have taken.

我不应该说神经科学家，我应该说科学家已经采取了。

And the one you described, which is let's look at all the parts, that's the bottom-up approach.

你所描述的，让我们看看所有的部分，这是自下而上的方法。

Take it apart and do a reductionist approach.

And you make a lot of progress.

You can figure out how things are connected and understand how development works, how neurons connect.

你可以弄清楚事物是如何连接的，并了解发育是如何进行的，神经元是如何连接的。

But it's very difficult to really make progress because quickly you get lost in the forest.

但真正取得进展是非常困难的，因为你很快就会在森林中迷路。

Now, the other approach, which has been successful, but at the end, unsatisfying, is the top-down approach.

现在，另一种方法已经成功，但最终并不令人满意，那就是自上而下的方法。

And this is the approach that psychologists have taken looking at behavior and trying to understand the laws of behavior.

这就是心理学家观察行为并试图理解行为规律的方法。

This is the behaviorists.

But even people in AI were trying to do a top-down to write programs that could replicate human behavior, intelligent behavior.

但即使是人工智能领域的人也试图自上而下地编写可以复制人类行为、智能行为的程序。

And I have to say that both of those approaches, bottom up or top down, have really not gotten to the core of answering any of those questions, the big questions.

我不得不说，这两种方法，无论是自下而上还是自上而下，都没有真正触及回答这些问题的核心，即大问题。

But there's a whole new approach now that is emerging in both neuroscience and AI at exactly the same time.

但现在神经科学和人工智能领域同时出现了一种全新的方法。

At this moment in history, it's really quite remarkable.

在历史的这个时刻，这确实是非常了不起的。

So there's an intermediate level between the implementation level at the bottom, how you implement some particular mechanism, and the actual behavior of the whole system.

It's called the algorithmic level.

It's in between.

它介于两者之间。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So algorithms are like recipes.

They're like when you bake a cake.

You have to have ingredients, and you have to say the order in which they're put together and how long, and if you get it wrong, it doesn't work.

It's just a mess.

这只是一团糟。

Now, it turns out that we're discovering algorithms.

现在，事实证明我们正在发现算法。

We've made a lot of progress with understanding the algorithms that are used in neural circuits, and this speaks to the computational level of how to understand the function of the neural circuit.

But I'm going to give you one example of an algorithm, which is one we worked on back in the 1990s when Peter Dayan and Reed Montague were post-docs in the lab.

但我将给你举一个算法的例子，这是我们在 20 世纪 90 年代研究的算法，当时 Peter Dayan 和 Reed Montague 在实验室做博士后。

And it had to do with a part of the brain below the cortex called the basal ganglia, which is responsible for learning sequences of actions in order to achieve some goal.

它与大脑皮层下方的一个叫做基底神经节的部分有关，它负责学习一系列动作以实现某个目标。

For example, if you want to play tennis, you have to be able to coordinate many muscles, and a whole sequence of actions has to be made if you want to be able to serve accurately, and you have to practice.

Well, what's going on there is that the basal ganglia basically is taking over from the cortex and producing actions that get better and better.

嗯，发生的事情是基底神经节基本上正在接管皮质并产生越来越好的动作。

And that's true not just of the muscles, but it's also true of thinking.

这不仅适用于肌肉，也适用于思维。

If you want to become good in any area, if you want to become a good financier, if you want to become a good doctor or a neuroscientist, you have to be practicing in terms of understanding the details of the profession and what works, what doesn't work, and so forth.

And it turns out that this basal ganglia interacts with the cortex, not just in the back, which is the action part, but also with the prefrontal cortex, which is the thinking part.

Andrew Huberman:

安德鲁·休伯曼：

Can I ask you a question about this briefly?

The basal ganglia, as I understand, are involved in the organization of two major types of behaviors: go, meaning to actually perform a behavior, but the basal ganglia also instruct no go.

Don't engage in that behavior.

And learning an expert golf swing or even a basic golf swing or tennis racket swing involves both of those things, go and no go.

学习专业的高尔夫挥杆动作，甚至基本的高尔夫挥杆动作或网球拍挥杆动作，都涉及到这两件事：走和不走。

Given what you just said, which is that the basal ganglia are also involved in generating thoughts of particular kinds, I wonder therefore if it's also involved in suppression of thoughts of particular kinds.

鉴于你刚才所说，基底神经节也参与产生特定类型的想法，因此我想知道它是否也参与抑制特定类型的想法。

You don't want your surgeon cutting into a particular region and just thinking about their motor behaviors, what to do and what not to do.

您不希望您的外科医生切入特定区域并只考虑他们的运动行为、该做什么和不该做什么。

They presumably need to think about what to think about, but also what to not think about.

他们大概需要考虑什么该考虑，但也需要考虑什么不该考虑。

You don't want that surgeon thinking about how their kid was a brat that morning and they're frustrated because the two things interact.

你不希望外科医生想到那天早上他们的孩子是个小孩子，他们会因为这两件事相互作用而感到沮丧。

So is there go, no-go in terms of action and learning, and is there go, no-go in terms of thinking?

那么，行动和学习方面有可否，思维方面有可否吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, I mentioned the prefrontal cortex, and that part, the loop with the basal ganglia, that is one of the last to mature in early adulthood.

嗯，我提到了前额皮质，以及基底神经节环路，它是成年早期最后成熟的部分之一。

And the problem is that for adolescents, it's not the no-go part for planning an action.

问题是，对于青少年来说，这并不是计划行动的禁忌部分。

This isn't quite there yet.

And so often it doesn't kick in to prevent you from doing things that are not in your best interest.

通常它不会阻止你做不符合你最佳利益的事情。

So yes, absolutely right.

But one of the things, though, is that learning is involved, and this is really a problem that we cracked, first theoretically in the '90s, and then experimentally later, by recording from neurons and also brain imaging in humans.

So it turns out we know the algorithm that is used in the brain for how to learn sequences of actions to achieve a goal.

事实证明，我们知道大脑中使用的算法，用于如何学习一系列动作以实现目标。

And it's the simplest possible algorithm you can imagine.

这是你能想象到的最简单的算法。

It's simply to predict the next reward you're going to get.

只是预测您将获得的下一个奖励。

If I do an action, will it give me something of value?

如果我采取行动，它会给我带来一些有价值的东西吗？

And you learn every time you try something, whether you got the amount of reward you expected or less, you use that to update the synapses, synaptic plasticity, so that the next time you'll have a better chance of getting a better reward, and you build up what's called a value function.

And so the cortex now, over your lifetime, is building up a lot of knowledge about things that are good for you, things that are bad for you.

因此，在你的一生中，大脑皮层正在积累大量关于对你有益和有害的事物的知识。

Like you go to a restaurant, you order something, how do you know what's good for you, right?

就像你去餐馆，你点了一些东西，你怎么知道什么对你有好处，对吧？

You've had lots of meals in a lot of places, and now that is part of your value function.

您在很多地方吃过很多餐，现在这是您价值函数的一部分。

This is the same algorithm that was used by AlphaGo.

这与 AlphaGo 使用的算法相同。

This is the program that DeepMind built.

这是 DeepMind 构建的程序。

This is an AI program that beat the world Go champion.

这是一个击败了围棋世界冠军的人工智能程序。

And Go is the most complex game that humans have ever played on a regular basis.

围棋是人类经常玩的最复杂的游戏。

Andrew Huberman:

安德鲁·休伯曼：

Far more complex than chess, as I understand.

据我了解，比国际象棋复杂得多。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, that's right.

是的，没错。

So Go is to chess what chess is to something like checkers.

所以，围棋之于国际象棋，就像国际象棋之于跳棋之类的东西一样。

In other words, the level of difficulty is way off above it because you have to think in terms of battles going on all over the place at the same time, and the order in which you put the pieces down are going to affect what's going to happen in the future.

Andrew Huberman:

安德鲁·休伯曼：

So this value function is super interesting, and I think you answered this, but I wonder whether this value function is implemented over long periods of time.

So you talked about the value function in terms of learning a motor skill.

所以你谈到了学习运动技能方面的价值函数。

Let's say swinging a tennis racket to do a perfect tennis serve, or even just a decent tennis serve.

假设挥动网球拍来完成一次完美的网球发球，甚至只是一次像样的网球发球。

When somebody goes back to the court, let's say on the weekend, once a month over the course of years, are they able to tap into that same value function every time they go back, even though there's been a lot of intervening time and learning?

That's question number one.

And then the other question is, do you think that this value function is also being played out in more complex scenarios, not just motor learning, such as, let's say, a domain of life that for many people involves some trial and error.

It would be like human relationships.

We learn how to be friends with people.

我们学习如何与人成为朋友。

We learn how to be a good sibling.

我们学习如何成为一个好兄弟。

We learn how to be a good romantic partner.

我们学习如何成为一个好的浪漫伴侣。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

We get some things right, we get some things wrong.

我们做对了一些事情，也做错了一些事情。

So is the same value function being implemented?

那么是否正在实现相同的价值函数？

We're paying attention to what was rewarding, but what I didn't hear you say also was what was punishing.

我们关注的是奖励，但我没有听到你说的是惩罚。

So are we only paying attention to what is rewarding?

那么我们是否只关注有回报的事情呢？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, no.

哦，不。

Andrew Huberman:

安德鲁·休伯曼：

Or are we also integrating punishment?

或者我们是否也整合了惩罚？

We don't get an electric shock when we get the serve wrong, but we can be frustrated.

当我们发球失误时，我们不会感到触电，但我们可能会感到沮丧。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

What you identified is a very important feature, which is that rewards-- By the way, every time you do something, you're updating this value function, every time, and it accumulates.

And to answer your first question, the answer is that it's always going to be there.

回答你的第一个问题，答案是它永远存在。

It doesn't matter.

没关系。

It's a very permanent part of your experience and who you are.

这是你的经历和你是谁的一个非常永久的部分。

And interestingly, and behaviorists knew this back in the 1950s, that you can get there two ways of trial and error.

有趣的是，行为学家早在 20 世纪 50 年代就知道这一点，你可以通过两种尝试和错误的方法来实现这一目标。

Small rewards are good because you're constantly coming closer and closer to getting what you're seeking, better tennis player, or being able to make a friend.

But the negative punishment is much more effective.

但消极惩罚的效果要好得多。

One trial learning.

一试学习。

You don't need to have 100 trials, which you need when you're training a rat to do some task with small food rewards.

您不需要进行 100 次试验，而当您训练老鼠以少量食物奖励完成某些任务时则需要进行 100 次试验。

But if you just shock the rat, boy, that rat doesn't forget that.

但如果你只是电击老鼠，孩子，那只老鼠不会忘记这一点。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

One really bad relationship will have you learning certain things forever.

一段非常糟糕的关系会让你永远学习某些东西。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And this is also PTSD.

这也是创伤后应激障碍。

Post-traumatic stress disorder is another good example of that.

创伤后应激障碍是另一个很好的例子。

That can screw you up for the rest of your life.

这可能会毁掉你的余生。

So, but the other thing, and you pointed out something really important, which is that a large part of the prefrontal cortex is devoted to social interactions.

And this is how humans, when you come into the world, you don't know what language you're going to be speaking.

这就是人类，当你来到这个世界时，你不知道你会说什么语言。

You don't know what the cultural values are that you're going to have to be able to become a member of this society and things that are expected of you.

你不知道你必须具备什么样的文化价值观才能成为这个社会的一员，也不知道人们对你的期望是什么。

All of that has to become through experience, through building this value function.

所有这一切都必须通过经验、通过构建这个价值函数来实现。

And this is something we discovered in the 20th century.

这是我们在20世纪发现的。

And now it's going into AI, it's called reinforcement learning in AI.

现在它进入了人工智能领域，这被称为人工智能中的强化学习。

It's a form of procedural learning, as opposed to the cognitive level where you think and you do things.

这是一种程序性学习的形式，与你思考和做事的认知水平相反。

Cognitive thinking is much less efficient, because you have to go step by step.

认知思维的效率要低得多，因为你必须一步一步来。

With procedural learning, it's automatic.

通过程序学习，它是自动的。

Andrew Huberman:

安德鲁·休伯曼：

Can you give me an example of procedural learning in the context of a comparison to cognitive learning?

您能给我举一个与认知学习进行比较的程序性学习的例子吗？

Like, is there an example of perhaps how to make a decent cup of coffee using purely knowledge-based-

比如，有没有一个例子可以说明如何使用纯粹基于知识的方式制作一杯像样的咖啡？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

哦

Andrew Huberman:

安德鲁·休伯曼：

...

learning versus procedural learning?

学习与程序学习？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, okay.

哦，好吧。

Andrew Huberman:

安德鲁·休伯曼：

Where procedural learning wins.

程序性学习获胜的地方。

And I can imagine one, but you're the true expert here.

我可以想象一个，但你是这里真正的专家。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, you know a lot of examples, but since we've been talking about tennis, can you imagine learning how to play tennis through a book?

嗯，你知道很多例子，但是既然我们一直在谈论网球，你能想象通过一本书学习如何打网球吗？

Reading a book?

看书？

Andrew Huberman:

安德鲁·休伯曼：

That's so funny.

太有趣了。

On the plane back from Nashville yesterday, the guy sitting across the aisle from me was reading a book about maybe he was working on his pilot's license or something.

昨天从纳什维尔回来的飞机上，坐在我对面过道的那个人正在读一本关于他可能正在考取飞行员执照之类的书。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And I looked over and couldn't help but notice these diagrams of the plane flying, and I thought, "I'm just so glad that this guy is a passenger and not a pilot." And then I thought about how the pilots learned, and presumably it was a combination of practical learning and textbook learning.

我看了看，忍不住注意到这些飞机飞行的图表，我想，“我很高兴这个人是一名乘客而不是飞行员。”然后我想到飞行员是怎么学习的，想必是实践学习和课本学习相结合。

I mean-

我的意思是——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

when you scuba dive, this is true.

当你水肺潜水时，这是真的。

I'm scuba dive certified, and when you get your certification-

我获得了水肺潜水认证，当你获得认证时-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

you learn your dive tables and you learn why you have to wait between dives, et cetera, and gas exchange and a number of things.

你了解你的潜水表，你了解为什么你必须在潜水之间等待，等等，以及气体交换和许多事情。

But there's really no way to simulate what it is to take your mask off underwater, put it back on, and then blow the water out of your mask.

但确实没有办法模拟在水下摘下面罩、戴上面罩，然后将面罩中的水吹掉的情况。

You just have to do that in a pool, and you actually have to do it when you need to-

你只需要在泳池里做这件事，而且你实际上必须在需要的时候做——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

for it to really get drilled in.

让它真正被钻进去。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

It's really essential for things that have to be executed quickly and expertly to get that really down pat so you don't have to think.

对于那些必须快速而熟练地执行的事情来说，真正做到这一点非常重要，这样你就不必思考。

Mm-hmm.

嗯嗯。

And this happens in school, right?

这发生在学校里，对吗？

In other words, you have classroom lessons where you're given explicit instruction, but then you go do homework.

换句话说，你在课堂上接受明确的指导，然后你就去做作业。

That's procedural learning.

这就是程序性学习。

You do problems, you solve problems.

你制造问题，你解决问题。

And I'm a PhD physicist, so I went through all of the classes in theoretical physics, and it was really the problems that really were the core of becoming a good physicist.

我是一名物理学博士，所以我学完了理论物理学的所有课程，这些问题确实是成为一名优秀物理学家的核心。

You could memorize the equations-

你可以记住方程式 -

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm

嗯嗯

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

but that doesn't mean you understand how to use the equations.

但这并不意味着您了解如何使用方程式。

Andrew Huberman:

安德鲁·休伯曼：

I think it's worth highlighting something.

我认为值得强调一些事情。

A lot of times on this podcast, we talk about what I call protocols.

在这个播客中，我们多次讨论我所说的协议。

It would be like get some morning sunlight in your eyes to stimulate your suprachiasmatic nucleus by way of your retinal ganglion cells.

这就像早晨的阳光射入您的眼睛，通过视网膜神经节细胞刺激您的视交叉上核。

Audiences of this podcast will recognize those terms.

该播客的观众会认识这些术语。

It's basically get sunlight in your eyes in the morning and set your circadian clock.

基本上就是早上让阳光照射到您的眼睛并设置您的生物钟。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Andrew Huberman:

安德鲁·休伯曼：

And you can hear that a trillion times, but I do believe that there's some value to both knowing what the protocol is, the underlying mechanisms, there are these things in your eye that encode the sunrise qualities of light, et cetera, and then send them to your brain, et cetera.

你可以听到一万亿次，但我确实相信，了解协议是什么、底层机制、你眼睛里的这些东西编码光的日出质量等等，然后将它们发送到你的大脑等等，都是有价值的。

But then once we link knowledge, pure knowledge, to a practice, I do believe that the two things merge someplace in a way that, let's say, reinforces both the knowledge and the practice.

但是，一旦我们将知识（纯粹的知识）与实践联系起来，我确实相信这两件事会在某个地方融合在一起，也就是说，会强化知识和实践。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So these things are not necessarily separate, they bridge.

所以这些东西不一定是分开的，它们是桥梁。

In other words, doing your theoretical physics-

换句话说，做你的理论物理学-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

problem sets reinforces the examples that you learned in lecture and in your textbooks, and vice versa.

问题集强化了您在讲座和教科书中学到的示例，反之亦然。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So this is a battle that's going on right now in schools.

所以这是一场正在学校里进行的战斗。

What you've just said is absolutely right.

你刚才说的完全正确。

You need both.

你两者都需要。

We have two major learning systems.

我们有两个主要的学习系统。

We have a cognitive learning system, which is cortical.

我们有一个认知学习系统，它是皮质的。

We have a procedural learning system, which is subcortical.

我们有一个程序性学习系统，它是皮层下的。

Basal ganglia.

基底神经节。

And the two go hand in hand.

两者齐头并进。

If you want to become good at anything, the two are going to help each other.

如果你想擅长某件事，两个人就会互相帮助。

And what's going on right now in schools, in California at least, is that they're trying to get rid of the procedural.

现在学校里正在发生的事情，至少在加州，他们正试图摆脱程序。

Andrew Huberman:

安德鲁·休伯曼：

That's ridiculous.

这太荒谬了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

They don't want students to practice because you're stressing them.

他们不希望学生练习，因为你给他们带来了压力。

You don't want them to feel that they're having difficulty.

你不希望他们觉得自己遇到了困难。

But we can do everything-

但我们可以做一切——

Andrew Huberman:

安德鲁·休伯曼：

For those listening, I'm covering my eyes because this would be like saying, goodness, there's so many examples, like here's a textbook on swimming, and then you're going to go out to the ocean someday, and you will have never actually swum.

对于那些听的人，我会捂住眼睛，因为这就像在说，天哪，有这么多例子，比如这是一本关于游泳的教科书，然后有一天你要去海边，但你实际上从未游泳过。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And now you're expected to be able to survive?

现在你有望活下来吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's crazy.

太疯狂了。

Andrew Huberman:

安德鲁·休伯曼：

Let alone swim well.

更不用说游得好。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's crazy.

太疯狂了。

But I'll tell you, Barbara Oakley and I have a MOOC, massive open online course, on learning how to learn, and it helps students.

但我会告诉你，芭芭拉·奥克利（Barbara Oakley）和我有一个 MOOC，大规模开放在线课程，关于学习如何学习，它对学生有帮助。

We aimed it at students, but it actually has been taken by four million people in 200 countries, ages 10 to 90.

我们的目标受众是学生，但实际上已经有 200 个国家、10 岁至 90 岁的 400 万人参加了它。

Andrew Huberman:

安德鲁·休伯曼：

What is this called?

这叫什么？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Learning How to Learn.

学习如何学习。

Andrew Huberman:

安德鲁·休伯曼：

Is there a paywall?

有付费墙吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, it's free.

不，它是免费的。

Completely free.

完全免费。

Andrew Huberman:

安德鲁·休伯曼：

Amazing.

太棒了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And I get incredible feedback, fan letters almost every day.

我几乎每天都会收到令人难以置信的反馈和粉丝来信。

Andrew Huberman:

安德鲁·休伯曼：

Well, you're about to get a few more.

好吧，你还会再得到一些。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Wow.

哇。

Andrew Huberman:

安德鲁·休伯曼：

I did an episode on learning how to learn, and my understanding of the research is that we need to test ourselves on the material.

我做了一个关于学习如何学习的节目，我对这项研究的理解是我们需要在材料上测试自己。

That testing is not just a form of evaluation.

该测试不仅仅是一种评估形式。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

It is a form of identifying the errors that help us then compensate for the errors and learn.

它是一种识别错误的形式，可以帮助我们弥补错误并学习。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Exactly.

正是如此。

Andrew Huberman:

安德鲁·休伯曼：

But it's very procedural.

但这是非常程序化的。

It's not about just listening and regurgitating.

这不仅仅是倾听和反省。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

You've put your finger on it, which is that, and this is what we teach the students, is that The way the brain works, it doesn't memorize things like a computer, but it has to be active learning.

你已经把手指放在上面了，就是这样，这就是我们教给学生的，就是大脑的工作方式，它不像计算机那样记住东西，但它必须是主动学习。

You have to be actively engaged.

你必须积极参与。

In fact, when you're trying to solve a problem on your own, this is where you're really learning by trial and error, and that's the procedural system.

事实上，当你试图自己解决问题时，这才是你真正通过反复试验来学习的地方，这就是程序系统。

But if someone tells you what the right answer is, that's just something that is a fact that it gets stored away somewhere, but it's not going to automatically come up if you actually are faced with something that's not exactly the same problem, but is similar.

但是，如果有人告诉你正确的答案是什么，那只是一个事实，它被存储在某个地方，但如果你实际上遇到的问题不完全相同，但很相似，它就不会自动出现。

And by the way, this is the key to AI, completely essential for the recent success of these large language models, that the public now is beginning to use, is that they're not parrots.

顺便说一句，这是人工智能的关键，对于公众现在开始使用的这些大型语言模型最近的成功完全至关重要，因为它们不是鹦鹉学舌。

They just don't memorize the data that they've taken in.

他们只是不记住他们所接收的数据。

They have to generalize.

他们必须概括。

That means to be able to do well on new things that come in that are similar to the old things that you've seen, but allow you to solve new problems.

这意味着能够在新事物上做得很好，这些新事物与你见过的旧事物相似，但可以让你解决新问题。

That's the key to the brain.

这就是大脑的钥匙。

The brain is really, really good at generalizing.

大脑真的非常擅长概括。

In fact, in many cases, you only need one example to generalize.

事实上，很多情况下，只需要一个例子就可以概括。

Andrew Huberman:

安德鲁·休伯曼：

Like going to a restaurant for the first time, there are a number of new interactions.

就像第一次去餐厅一样，有很多新的互动。

There might be a host or a hostess.

可能有男主人或女主人。

You sit down at these tables you've never sat at.

你坐在这些你从未坐过的桌子旁。

Somebody asks you questions.

有人问你问题。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

You read it.

你读了它。

Okay, maybe it's a QR code these days, but-

好吧，也许现在是二维码，但是-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

forever after, you understand the process of going into a restaurant.

从此以后，您就了解了进入餐厅的过程。

Doesn't matter what the genre of food happens to be or what city, sitting inside or outside, you can pretty much work it out.

无论食物类型是什么，无论是哪个城市，无论是坐在室内还是室外，您几乎都能找到答案。

Sit at the counter, sit outside, sit at the table.

坐在柜台旁，坐在外面，坐在桌子旁。

There are a number of key action steps that I think pretty much translate to everywhere, unless you go to some super high-end thing or some super-

我认为有许多关键的行动步骤几乎适用于任何地方，除非你去一些超级高端的东西或一些超级的东西。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

low-end thing where it's a buffet or whatever.

低端的东西，比如自助餐什么的。

You can start to fill in the blanks here.

您可以从这里开始填写空白。

If I understand correctly, there's an action function that's learned from the knowledge and the experience.

如果我理解正确的话，有一个从知识和经验中学到的动作函数。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes, exactly.

是的，完全正确。

Andrew Huberman:

安德鲁·休伯曼：

And then where is that action function stored?

那么这个动作函数存储在哪里呢？

Is it in one location in the brain, or is it-

它是在大脑的某个位置，还是——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

啊

Andrew Huberman:

安德鲁·休伯曼：

...

kind of an emergent property of multiple brain areas?

多个大脑区域的一种新兴特性？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So you're right at the cusp here of where we are in neuroscience right now.

所以你现在正处于神经科学的风口浪尖。

We don't know the answer to that question.

我们不知道这个问题的答案。

In the past, it had been thought that the cortex were like countries, that each part of the cortex was dedicated to one function.

过去，人们认为大脑皮层就像国家一样，大脑皮层的每个部分都专注于一种功能。

Right?

正确的？

And interestingly, you record from the neurons, and it certainly looks that way, right?

有趣的是，你从神经元记录下来，它看起来确实是这样，对吧？

In other words, there's a visual cortex in the back, and there's a whole series of areas, and then there's the auditory cortex here in the middle, and then the prefrontal cortex for social interaction.

换句话说，后面有一个视觉皮层，还有一系列区域，然后是中间的听觉皮层，然后是用于社交互动的前额叶皮层。

And so it looked really clear-cut that it's modular.

所以它看起来非常明确，它是模块化的。

And now what we're facing is, we have a new way to record from neurons optically.

现在我们面临的是，我们有一种新的方法来从神经元进行光学记录。

We can record from tens of thousands, from dozens of areas simultaneously.

我们可以同时记录数十个区域的数万个数据。

And what we're discovering is that if you want to do any task, you're engaging not just the area that you might think has the input coming in, say, the visual system, but the visual system is getting input from the motor system.

我们发现，如果你想做任何任务，你不仅会参与你可能认为有输入的区域，例如视觉系统，而且视觉系统也会从运动系统获取输入。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right?

对吗？

In fact, there's more input coming from the motor system than from the eye.

事实上，来自运动系统的输入比来自眼睛的输入更多。

Andrew Huberman:

安德鲁·休伯曼：

Really?

真的吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Yeah, Ann Churchland at UCLA has shown that in the mouse.

是的，加州大学洛杉矶分校的安·丘奇兰 (Ann Churchland) 在老鼠身上证明了这一点。

So now we're looking at global interactions between all these areas, and that's where real complex cognitive behaviors emerge, is from those interactions.

因此，现在我们正在研究所有这些领域之间的全局相互作用，而真正复杂的认知行为正是从这些相互作用中出现的。

And now we have the tools for the first time to actually be able to see them in real time.

现在我们第一次拥有了真正能够实时看到它们的工具。

And we're doing that now first on mice and monkeys, but we now can do this in humans.

我们现在首先在老鼠和猴子身上做这件事，但现在我们可以在人类身上做这件事。

So I've been collaborating with a group at Mass General Hospital to record from people with epilepsy, and they have to have an operation, for people who are drug resistant, to be able to find out where it starts in the cortex, and where it is initiated, where the seizure starts, and then you have to go in and record simultaneously from a lot of parts of the cortex for weeks until you find out where it is, and then you go in and you try to take it out.

所以我一直在和麻省总医院的一个小组合作，记录癫痫患者的情况，他们必须对那些有耐药性的人进行手术，才能找出癫痫在大脑皮层的哪里开始，从哪里开始，从哪里开始癫痫发作，然后你必须进去并同时记录大脑皮层的很多部分，持续数周，直到你找出它在哪里，然后你进去并试图把它取出来。

And often that helps.

这通常会有所帮助。

Very, very invasive, but for two weeks, we have access to all those neurons in that cortex that are being recorded from constantly.

非常非常具有侵入性，但是在两周的时间里，我们可以接触到皮层中不断被记录的所有神经元。

And so I started out because I was interested in sleep, and I wanted to understand what happens in the cortex of a human during sleep.

所以我开始是因为我对睡眠感兴趣，我想了解人类睡眠期间大脑皮层会发生什么。

But then we realized that, people who have these debilitating problems with seizures, they're there for two weeks, and they have nothing to do, so they just love the fact that scientists are interested in helping them and teaching them things and finding out where in the cortex things are happening when they learn something.

但后来我们意识到，患有癫痫发作等令人衰弱的问题的人，他们在那里呆了两周，无事可做，所以他们只是喜欢这样一个事实：科学家有兴趣帮助他们，教他们东西，并在他们学到东西时找出大脑皮层中发生的事情。

This is a goldmine.

这是一座金矿。

It's unbelievable.

真是难以置信。

And I've learned things from humans that I could've never gotten from any other species.

我从人类身上学到了从其他物种那里无法学到的东西。

Andrew Huberman:

安德鲁·休伯曼：

Amazing.

太棒了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Obviously, language is one of them, but there are other things in sleep that we discovered having to do with traveling waves.

显然，语言是其中之一，但我们发现睡眠中还有其他与行波有关的东西。

There are circular traveling waves that go on during sleep, which is astonishing.

睡眠时会出现圆形行波，令人惊讶。

Nobody ever really saw that before, but now-

以前没有人真正见过这一点，但现在——

Andrew Huberman:

安德鲁·休伯曼：

If you were to ascribe one or two major functions to these traveling waves, what do you think they are accomplishing for us in sleep?

如果您将这些行波赋予一两个主要功能，您认为它们在睡眠中为我们完成了什么？

And by the way, are they associated with deep sleep, slow-wave sleep, or with rapid eye movement sleep, or both?

顺便问一下，它们是否与深度睡眠、慢波睡眠或快速眼动睡眠有关，或两者都有关？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

This is non-REM sleep.

这是非快速眼动睡眠。

This is jargon, but this is during intermediate

这是行话，但这是在中间阶段

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Transition states.

过渡状态。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Transition state.

过渡状态。

Andrew Huberman:

安德鲁·休伯曼：

Okay.

好的。

Our audience will probably be keep up.

我们的观众可能会跟上。

They've heard a lot about slow-wave sleep from me and Matt Walker-

他们从我和马特·沃克那里听到了很多关于慢波睡眠的信息——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, okay.

哦，好吧。

Yeah

是啊

Andrew Huberman:

安德鲁·休伯曼：

...

and from rapid eye movements.

以及快速的眼球运动。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

This is light slow-wave sleep, yeah.

是的，这就是轻度慢波睡眠。

Andrew Huberman:

安德鲁·休伯曼：

And so what do these traveling waves accomplish for us?

那么这些行波能为我们带来什么呢？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay, so in the case of the, they're called sleep spindles.

好的，就这种情况而言，它们被称为睡眠纺锤体。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

The waves last for about a second or two, and they travel, like I say, in a circle around the cortex.

这些波持续大约一两秒，就像我说的那样，它们围绕皮层绕一圈传播。

And it's known that these spindles are important for consolidating experiences you've had during the day into your long-term memory storage.

众所周知，这些心轴对于将白天的经历整合到长期记忆存储中非常重要。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So, it's a very important function, and if you take out-- See, it's the hippocampus that is replaying the experiences.

所以，这是一个非常重要的功能，如果你拿出来——看，海马体正在重播这些经历。

It's a part of the brain that's very important for long-term memory.

它是大脑的一部分，对于长期记忆非常重要。

If you don't have a hippocampus, you can't learn new things.

如果你没有海马体，你就无法学习新事物。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That is to say, you can't remember what you did yesterday, or for that matter, even an hour earlier.

也就是说，你不记得昨天或一小时前做了什么。

But the hippocampus plays back your experiences, causes the sleep spindles now to knead that into the cortex, and it's important you do that right, because you don't want to overwrite the existing knowledge you have.

但是海马体会回放你的经历，导致睡眠纺锤体将其揉捏到皮质中，正确地做到这一点很重要，因为你不想覆盖你现有的知识。

You just want to basically incorporate the new experience into your existing knowledge base in an efficient way that doesn't interfere with what you already know.

您只想以一种有效的方式将新体验基本上融入到您现有的知识库中，而不会干扰您已经知道的内容。

So that's an example of a very important function that these traveling waves have.

这是这些行波具有的非常重要功能的一个例子。

Andrew Huberman:

安德鲁·休伯曼：

I'd like to take a quick break and acknowledge our sponsor, AG1.

我想稍微休息一下并感谢我们的赞助商 AG1。

AG1 is a vitamin mineral probiotic drink that includes prebiotics and adaptogens.

AG1 是一种维生素矿物质益生菌饮料，含有益生元和适应原。

I've been drinking AG1 since 2012, and I started doing it at a time when my budget was really limited.

我从 2012 年开始喝 AG1，当时我的预算非常有限。

In fact, I only had enough money to purchase one supplement, and I'm so glad that I made that supplement AG1.

事实上，我的钱只够购买一种补充剂，我很高兴我制作了这款补充剂 AG1。

The reason for that is even though I strive to eat whole foods and unprocessed foods, it's very difficult to get enough vitamins and minerals, micronutrients, and adaptogens from diet alone in order to make sure that I'm at my best, meaning have enough energy for all the activities I participate in from morning until night, sleeping well at night, and keeping my immune system strong.

原因是，尽管我努力吃天然食品和未加工食品，但仅从饮食中获取足够的维生素和矿物质、微量营养素和适应原是非常困难的，以确保我处于最佳状态，这意味着我有足够的能量来进行从早到晚参加的所有活动，晚上睡得好，并保持我的免疫系统强大。

Now, when I take AG1 daily, I find that all aspects of my health, my physical health, my mental health, my performance, recovery from exercise, all of those improve.

现在，当我每天服用 AG1 时，我发现我的健康的各个方面，我的身体健康，我的心理健康，我的表现，运动恢复，所有这些都得到改善。

And I know that because I've had lapses when I didn't take my AG1, and I certainly felt the difference.

我知道这一点，因为当我没有带上 AG1 时，我曾犯过错误，而且我确实感受到了差异。

I also noticed, and this makes perfect sense given the relationship between the gut microbiome and the brain, that when I regularly take AG1, that I have more mental clarity and more mental energy.

我还注意到，考虑到肠道微生物组和大脑之间的关系，当我定期服用 AG1 时，我的思维更加清晰，精力更加充沛，这是完全有道理的。

If you'd like to try AG1, you can go to drinkag1.com/huberman to claim a special offer.

如果您想尝试 AG1，可以访问 Drinkag1.com/huberman 申请特别优惠。

For this month only, November 2024, AG1 is giving away a free one-month supply of omega-3 fatty acids from fish oil, in addition to their usual welcome kit of five free travel packs and a year's supply of vitamin D3K2.

仅在 2024 年 11 月这个月，AG1 将免费赠送一个月的来自鱼油的 omega-3 脂肪酸，此外还有他们通常的欢迎套装，包括五个免费旅行包和一年的维生素 D3K2。

As I've discussed many times before on this podcast, omega-3 fatty acids are critical for brain health, mood, cognition, and more.

正如我之前在此播客中多次讨论过的那样，omega-3 脂肪酸对于大脑健康、情绪、认知等至关重要。

Again, go to drinkag1.com/huberman to claim this special offer.

请再次访问 Drinkag1.com/huberman 领取此特别优惠。

Today's episode is also brought to us by David.

今天的节目也是大卫给我们带来的。

David makes a protein bar unlike any other.

大卫制作的蛋白质棒与众不同。

It has 28 grams of protein, only 150 calories, and zero grams of sugar.

它含有 28 克蛋白质，仅 150 卡路里，零克糖。

That's right, 28 grams of protein, and 75% of its calories come from protein.

没错，28克蛋白质，它的热量75%来自于蛋白质。

These bars from David also taste amazing.

大卫的这些酒吧味道也很棒。

My favorite flavor is chocolate chip cookie dough.

我最喜欢的口味是巧克力饼干面团。

But then again, I also like the chocolate fudge-flavored one, and I also like the cake-flavored one.

不过话说回来，我也喜欢巧克力软糖口味的，也喜欢蛋糕口味的。

Basically, I like all the flavors.

基本上所有的口味我都喜欢。

They're incredibly delicious.

它们非常美味。

For me personally, I strive to eat mostly whole foods.

就我个人而言，我努力主要吃天然食品。

However, when I'm in a rush or I'm away from home, or I'm just looking for a quick afternoon snack, I often find that I'm looking for a high-quality protein source.

然而，当我很赶时间或者我不在家，或者我只是想吃点下午茶时，我经常发现我正在寻找高质量的蛋白质来源。

With David, I'm able to get 28 grams of protein with the calories of a snack, which makes it very easy to hit my protein goals of one gram of protein per pound of body weight each day.

有了 David，我就能用一份零食的热量获取 28 克蛋白质，这使得我很容易达到每天每磅体重 1 克蛋白质的蛋白质目标。

And it allows me to do that without taking in excess calories.

它使我能够在不摄入过多卡路里的情况下做到这一点。

I typically eat a David bar in the early afternoon or even mid-afternoon if I want to bridge that gap between lunch and dinner.

如果我想弥补午餐和晚餐之间的差距，我通常会在下午早些时候甚至下午中旬吃大卫酒吧。

I like that it's a little bit sweet, so it tastes like a tasty snack, but it's also giving me that 28 grams of very high-quality protein with just 150 calories.

我喜欢它有点甜，所以它尝起来像美味的零食，但它也为我提供了 28 克优质蛋白质，而热量仅为 150 卡路里。

If you would like to try David, you can go to davidprotein.com/huberman.

如果您想尝试 David，可以访问 david Protein.com/huberman。

Again, the link is davidprotein.com/huberman.

同样，链接是 david Protein.com/huberman。

As I recall, there are one or two things that one can do in order to ensure that one gets sufficient sleep spindles at night, and thereby incorporate this new knowledge.

我记得，为了确保晚上获得足够的睡眠纺锤波，人们可以做一两件事，从而吸收这一新知识。

This was from the episode that we did with Gina Poe from UCLA, I believe, and others, including Matt Walker.

我相信这是我们与加州大学洛杉矶分校的吉娜·坡以及包括马特·沃克在内的其他人一起拍摄的一集。

My recollection is that the number one thing is to make sure you get enough sleep at night, so you experience enough of these spindles.

我的记忆是，第一件事是确保你晚上有足够的睡眠，这样你就能体验到足够的纺锤波。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And we're all familiar with the cognitive challenges, including memory challenges and learning challenges associated with lack of sleep, insufficient sleep.

我们都熟悉认知挑战，包括与睡眠不足、睡眠不足相关的记忆挑战和学习挑战。

But the other was that there was some interesting relationship between daytime exercise and nighttime prevalence of sleep spindles.

但另一个问题是，白天锻炼和夜间睡眠纺锤波患病率之间存在一些有趣的关系。

Are you familiar with that literature?

你熟悉那些文献吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Oh, yes.

哦是的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, this is a fascinating literature, and it's all pointing the same direction, which is that we always neglect to appreciate the importance of sleep.

不，这是一本引人入胜的文献，而且它们都指向同一个方向，那就是我们总是忽视了睡眠的重要性。

I mean, obviously, you're refreshed when you wake up, but there's a lot of things happening.

我的意思是，显然，当你醒来时你会精神焕发，但同时发生了很多事情。

It's not that your brain turns off, it's that it goes into a completely different state, and memory consolidation is just one of those things that happens when you fall asleep.

这并不是说你的大脑关闭了，而是它进入了一种完全不同的状态，而记忆巩固只是你入睡时发生的事情之一。

And of course, there's dreams and so forth.

当然，还有梦想等等。

We don't fully appreciate or understand exactly how all the different sleep stages work together.

我们并没有完全理解或理解所有不同的睡眠阶段是如何协同工作的。

But exercise is a particularly important part of getting the motor system tuned up, and it's thought that the REM, rapid eye movement sleep, may be involved in that, so that's yet another part of the sleep stages.

但运动是调整运动系统的一个特别重要的部分，人们认为快速眼动睡眠（REM）可能与此有关，所以这是睡眠阶段的另一个部分。

You go through, you go back and forth between dream sleep and the slow-wave sleep, back and forth, back and forth during the night, and then when you wake up, you're in the REM stage, more and more REM.

你会经历，在梦睡眠和慢波睡眠之间来回，在夜间来回，然后当你醒来时，你处于快速眼动阶段，越来越多的快速眼动阶段。

But that's all observation.

但这只是观察。

But as a scientist, what you want to do is perturb the system and see if you can Maybe if you had more sleep spindles, maybe you'd be able to remember things better.

但作为一名科学家，你想做的是扰乱系统，看看你是否可以。也许如果你有更多的睡眠纺锤波，也许你能够更好地记住事情。

So it turns out Sarah Mednick, who's at UC Irvine, did this fantastic experiment.

事实证明，加州大学欧文分校的莎拉·梅德尼克做了这个奇妙的实验。

So it turns out there's a drug called Zolpidem, which goes by the name Ambien.

原来有一种药物叫做唑吡坦，它的名字是安必恩（Ambien）。

You may have some experience with that if you-

您可能对此有一些经验，如果您-

Andrew Huberman:

安德鲁·休伯曼：

I've never taken it, but I'm aware of what it is.

我从未服用过它，但我知道它是什么。

People use it as a sleep aid.

人们用它作为睡眠辅助剂。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

A lot of people take it in order to sleep.

很多人服用它是为了睡觉。

Okay.

好的。

Well, it turns out that it causes more sleep spindles.

事实证明，它会导致更多的睡眠纺锤波。

Andrew Huberman:

安德鲁·休伯曼：

Really?

真的吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

It doubles the number of sleep spindles if you take the drug.

如果服用该药物，睡眠纺锤波的数量会增加一倍。

You take the drug after you've done the learning, right?

学习完之后就可以吃药了，对吗？

You do the learning at night, and then you take the drug, and you have twice as many spindles.

你晚上学习，然后服用药物，你的纺锤数就会增加一倍。

You wake up in the morning, you can remember twice as much from what you learned.

当你早上醒来时，你能记住的东西是你所学知识的两倍。

Andrew Huberman:

安德鲁·休伯曼：

And the memories are stable over time?

而且记忆随着时间的推移是稳定的吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

It's in there.

它就在那里。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

No, it consolidates it.

不，它巩固了它。

That's the point is-

重点是——

Andrew Huberman:

安德鲁·休伯曼：

What's the downside of Ambien?

安必恩有什么缺点？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay, here's the downside.

好吧，这是缺点。

Okay.

好的。

So people who take the drug, say, if you're going to Europe and you take it, and then you sleep really soundly, but often you find yourself in the hotel room and you completely have no clue, you have no memory of how you got there.

所以服用这种药物的人，比如说，如果你要去欧洲，你服用了它，然后你睡得很香，但你经常发现自己在酒店房间里，你完全不知道，你不记得你是如何到达那里的。

Andrew Huberman:

安德鲁·休伯曼：

I've had that experience without Ambien or any other drugs, where I am very badly jet lagged.

我有过这样的经历，没有使用安必恩或任何其他药物，我的时差反应非常严重。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

And I wake up and for a few seconds, but what feels like eternity, I have no idea where I am.

我醒来了，有几秒钟的时间，但感觉就像永恒一样，我不知道自己在哪里。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

It's terrifying.

太可怕了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, that's another problem that you have with jet lag.

嗯，这是时差带来的另一个问题。

Jet lag really screws things up.

时差确实把事情搞砸了。

But this is something where it could be an hour.

但这可能需要一个小时。

You took the train or you took a taxi or something, and now this seems crazy.

你坐火车或者出租车什么的，现在这看起来很疯狂。

How could it be a way to improve learning and recall on one hand, and then forgetfulness on the other hand?

它怎么可能是一种一方面改善学习和记忆，另一方面改善健忘的方法呢？

Well, it turns out what's important is that when you take the drug, right?

嗯，事实证明，重要的是你什么时候服药，对吧？

In other words, it helps consolidate experiences you've had in the past before you took the drug, but it'll wipe out experiences you have in the future after you take the drug, right?

换句话说，它有助于巩固你过去服药前的经历，但它会抹掉你服药后未来的经历，对吗？

You still-

你还是——

Andrew Huberman:

安德鲁·休伯曼：

Sorry I'm not laughing.

抱歉我没有笑。

It must be a terrifying experience, but I'm laughing because there's some beautiful pharmacology and indeed some wonderfully useful pharmaceuticals out there.

这一定是一次可怕的经历，但我笑了，因为那里有一些美丽的药理学，而且确实有一些非常有用的药物。

Some people may cringe to hear me say that, but there are some very useful drugs out there that save lives and help people deal with symptoms, et cetera.

有些人听到我这么说可能会感到畏缩，但是有一些非常有用的药物可以挽救生命并帮助人们应对症状等等。

Side effects are always a concern, but this particular drug profile, Ambien, that is, seems to reveal something perhaps even more important than the discussion about spindles or Ambien, or even sleep, which is that you got to pay the piper somehow, as they say.

副作用始终是一个令人担忧的问题，但这种特殊的药物概况，即安必恩，似乎揭示了一些可能比有关纺锤体或安必恩，甚至睡眠的讨论更重要的事情，正如他们所说，你必须以某种方式向吹笛者支付费用。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Andrew Huberman:

安德鲁·休伯曼：

That you tweak one thing in the brain, something else goes.

当你调整大脑中的一件事时，另一件事就会发生。

You don't get anything for free.

你不会免费得到任何东西。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I think that this is something that is true not just of drugs for the brain, but steroids for the body, right?

我认为这不仅适用于大脑药物，也适用于身体类固醇，对吗？

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Sure.

当然。

Yeah.

是的。

Steroids, even low dose testosterone therapy, which is very popular nowadays, will give people more vigor, et cetera, but it is introducing a sort of second puberty, and puberty is perhaps the most rapid phase of aging-

类固醇，甚至现在很流行的低剂量睾酮疗法，都会让人更有活力等等，但它正在引入一种第二青春期，而青春期也许是衰老最快的阶段——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

of the entire lifespan.

的整个生命周期。

Same thing with people take growth hormone would be probably a better example.

与服用生长激素的人一样，这可能是一个更好的例子。

Because certainly those therapies can be beneficial to people, but growth hormone gives people more vigor, but it accelerates aging.

因为这些疗法当然可以对人有益，但生长激素让人更有活力，但却会加速衰老。

Look at the quality of skin that people have when they take growth hormone.

看看人们服用生长激素后的皮肤质量。

It looks more aged.

看起来更显老气了。

They physically change.

他们的身体发生了变化。

And I'm not for or against these things.

我不赞成也不反对这些事情。

It's highly individual.

这是高度个性化的。

But I completely agree with you.

但我完全同意你的观点。

I would also venture that with the growing interest in so-called nootropics, and people taking things like modafinil, not just for narcolepsy, daytime sleepiness-

我还敢说，随着人们对所谓的促智药越来越感兴趣，人们服用莫达非尼等药物，不仅仅是为了治疗发作性睡病、白天嗜睡——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

but also to enhance cognitive function, okay, maybe they can get away with doing that every once in a while for a deadline task or something.

而且还可以增强认知功能，好吧，也许他们可以偶尔为截止日期任务或其他事情这样做。

But my experience is that people who obsess over the use of pharmacology to achieve certain brain states pay in some other way.

但我的经验是，痴迷于利用药理学来实现某些大脑状态的人会以其他方式付出代价。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Absolutely.

绝对的。

Andrew Huberman:

安德鲁·休伯曼：

Whether or not stimulants or sedatives or sleep drugs, and that behaviors will always prevail.

无论是否使用兴奋剂、镇静剂或安眠药，这种行为总是会占上风。

Behaviors will always prevail as tools.

行为作为工具永远会占上风。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yep, and one of the things about the way the body evolved is that it really has to balance a lot of things, and so with drugs, you're basically unbalancing it somehow.

是的，关于身体进化方式的一件事是它确实必须平衡很多东西，所以使用药物，你基本上会以某种方式失去平衡。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And the consequence is, as you point out, is that in order to make one part better, one part of your body, you sacrifice something else somewhere else.

正如您所指出的，结果是，为了使身体的某一部分变得更好，您牺牲了其他地方的其他东西。

Yep.

是的。

Andrew Huberman:

安德鲁·休伯曼：

As long as we're talking about brain states and connectivity across areas, I want to ask a particular question, then I want to return to this issue about how best to learn, especially in kids, but also in adulthood.

只要我们谈论大脑状态和跨区域的连接，我就想问一个特定的问题，然后我想回到这个关于如何最好地学习的问题，尤其是在儿童中，而且在成年期也是如此。

I've become very interested in and spent a lot of time with the literature and some guests on the topic of psychedelics.

我对迷幻药主题的文献和一些嘉宾非常感兴趣，并花了很多时间与他们相处。

Let's leave the discussion about LSD aside because do you know why there aren't many studies with LSD?

我们先把关于 LSD 的讨论放在一边，因为你知道为什么 LSD 的研究不多吗？

This is kind of a fun one.

这是一件有趣的事。

No one is expected to know the answer.

预计没有人知道答案。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, it's against the law, I think.

嗯，我认为这是违法的。

Andrew Huberman:

安德鲁·休伯曼：

Oh, but so is psilocybin or MDMA, and there are lots of studies going on about those.

哦，裸盖菇素或 MDMA 也是如此，并且有很多关于这些的研究正在进行中。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, there are now.

哦，现在有了。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, it's changed.

是的，已经改变了。

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But when I was growing up, as you know-

但当我长大的时候，如你所知——

Andrew Huberman:

安德鲁·休伯曼：

Sure

当然可以

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

it was against the law.

这是违法的。

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

So what I learned is that there are far fewer clinical trials exploring the use of LSD as a therapeutic, because with the exception of Switzerland, none of the researchers are willing to stay in the laboratory as long as it takes for the subject-

所以我了解到的是，探索使用LSD作为治疗方法的临床试验要少得多，因为除了瑞士之外，没有一个研究人员愿意在实验室里待到课题需要的时间——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, to come down?

哦，要下来吗？

Andrew Huberman:

安德鲁·休伯曼：

...

to get through an LSD journey, whereas psilocybin tends to be a shorter-

来度过LSD之旅，而裸盖菇素往往是一个较短的-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

a shorter experience.

较短的经历。

Okay.

好的。

Let's talk about psilocybin for a moment.

我们来谈谈裸盖菇素。

My read of the data on psilocybin is that it's still open to question, but that some of the clinical trials show pretty significant recovery from major depression.

我对裸盖菇素数据的解读是，它仍然有待商榷，但一些临床试验显示，重度抑郁症的恢复相当显着。

It's pretty impressive.

这真是令人印象深刻。

But if we just set that aside and say, okay, more needs to be worked out for safety What is very clear from the brain imaging studies, the sort of before and after, resting state, task related, et cetera, is that you get more resting state global connectivity, more areas talking to more areas than was the case prior to the use of the psychedelic.

但如果我们把这一点放在一边，说，好吧，为了安全，还需要做更多的工作。从大脑成像研究中可以清楚地看出，与使用迷幻剂之前相比，之前和之后、静息状态、任务相关等等，你会获得更多的静息状态全局连接，更多的区域与更多的区域进行对话。

And given the similarity of the psychedelic journey, and here specifically talking about psilocybin, to things like rapid eye movement, sleep, and things of that sort, I have a very simple question.

考虑到迷幻之旅的相似性，这里特别谈论裸盖菇素，与快速眼球运动、睡眠等类似的事情，我有一个非常简单的问题。

Do you think that there's any real benefit to increasing brain-wide connectivity?

您认为增加全脑连接有什么真正的好处吗？

To me, it seems a little bit haphazard, and yet the clinical data are promising, if nothing else, promising.

对我来说，这似乎有点随意，但临床数据至少是有希望的。

And so is what we're seeking in life as we acquire new knowledge, as we learn tennis or golf or take up singing or what have you, as we go from childhood into the late stages of our life, that whole transition, is what we're doing increasing connectivity and communication between different brain areas?

当我们获得新知识时，当我们学习网球或高尔夫球或开始唱歌或其他什么时，当我们从童年进入生命的后期阶段时，整个转变就是我们正在做的事情，即增加不同大脑区域之间的连接和沟通？

Is that what the human experience is really about?

这就是人类经验的真正含义吗？

Or is it that we're getting more modular, we're getting more segregated in terms of this area talking to this area in this particular way?

或者是我们变得更加模块化，我们在这个领域以这种特殊的方式与这个领域交谈变得更加隔离？

Feel free to explore this in any way that feels meaningful.

请随意以任何感觉有意义的方式探索这一点。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Or to say pass if it's not a good question.

或者如果这不是一个好问题，就说“通过”。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, it's a great question.

不，这是一个很好的问题。

You have all these great questions, and we don't have complete answers yet.

您提出了所有这些重要问题，但我们还没有完整的答案。

But, specifically with regard to connectivity, if you look at what happens in an infant's brain during the first two years, there's a tremendous amount of new synapses being formed.

但是，特别是在连通性方面，如果你观察婴儿的大脑在头两年中发生的情况，就会发现大量新突触正在形成。

This is your area, by the way .

顺便说一下，这是你的区域。

You know more about this than I do.

你比我更了解这一点。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

That's true.

这是真的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But then you prune them.

但随后你修剪它们。

There's the second phase is that you have overabundant synapses, and now what you want to do is to prune them.

第二阶段是你有过多的突触，现在你要做的就是修剪它们。

Why would you want to do that?

你为什么要这么做？

Well, synapses are expensive.

嗯，突触很昂贵。

It takes a lot of energy to activate all of the neurons and the synapses especially, because there's the turnover of the neurotransmitter.

激活所有神经元，尤其是突触需要大量能量，因为神经递质会更替。

And so what you want to do is to reduce the amount of energy and only use those synapses that have been proven to be the most important.

所以你要做的就是减少能量，只使用那些被证明是最重要的突触。

Now, unfortunately, as you get older, the pruning slows down but doesn't go away.

现在，不幸的是，随着年龄的增长，修剪的速度会减慢，但不会消失。

So the cortex thins and so forth.

所以皮质变薄等等。

So I think it goes in the opposite direction.

所以我认为事情正朝着相反的方向发展。

I think that as you get older, you're losing connectivity.

我认为随着年龄的增长，你会失去联系。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But interestingly, you retain the old memories.

但有趣的是，你保留了旧的记忆。

The old memories are really rock solid because they were put in when you were young.

旧的记忆真的坚如磐石，因为它们是在你年轻的时候放进去的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah, the foundation.

是的，基础。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

The foundation upon which everything else is built.

其他一切都建立在其之上的基础。

But it's not totally one way in the sense that even as an adult, as you know, you can learn new things, maybe not as quickly.

但这并不完全是一种方式，正如你所知，即使作为一个成年人，你也可以学习新事物，但可能不会那么快。

By the way, this is one of the things that surprised me.

顺便说一句，这是令我惊讶的事情之一。

So Barbara and I have looked at the people who really benefited the most.

因此，芭芭拉和我研究了真正受益最多的人。

It turns out that the peak of the demographic is 25 to 35.

事实证明，人口高峰是25岁至35岁。

Andrew Huberman:

安德鲁·休伯曼：

Barbara?

芭芭拉？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oakley.

奥克利。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, she's really the mastermind.

是的，她确实是幕后黑手。

She's a fabulous educator and background in engineering.

她是一位出色的教育家，拥有工程学背景。

But what's going on?

但到底是怎么回事呢？

So it turns out we aimed our MOOC at kids in high school and college because that's their business.

事实证明，我们的 MOOC 课程主要针对高中和大学的孩子，因为那是他们的事。

They go every day and they go into work, they have to learn.

他们每天都去工作，他们必须学习。

That's their business.

那是他们的事。

But in fact, very few of the students were actually taking the course.

但事实上，真正参加这门课程的学生很少。

Why should they?

他们为什么要这么做？

They spend all day in the class.

他们整天都在课堂上度过。

Why do they want to take another class?

为什么他们想参加另一门课？

Andrew Huberman:

安德鲁·休伯曼：

So this is the learning to learn class.

这就是学习学习的课程。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Learning how to learn.

学习如何学习。

Andrew Huberman:

安德鲁·休伯曼：

Okay.

好的。

So you did this with Barbara.

所以你和芭芭拉一起做了这件事。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So I did it with Barbara.

所以我和芭芭拉一起做了。

Andrew Huberman:

安德鲁·休伯曼：

Okay.

好的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And now 25 to 35, we have this huge peak.

现在25岁到35岁，我们有这个巨大的高峰。

Huge.

巨大的。

So what's going on?

那么到底是怎么回事呢？

Here's what's going on.

这是发生的事情。

It's very interesting.

这很有趣。

So you're 25, you've gone to college.

那么你25岁了，你已经上大学了。

Half the people, by the way, who take the course went to college.

顺便说一句，参加这门课程的人有一半上了大学。

So this it's not like filling in for college.

所以这不像填报大学。

This is like topping it off.

这就像把它加满一样。

But you're in the workforce.

但你在劳动力中。

You have to learn a new skill.

你必须学习一项新技能。

Maybe you have mortgage.

也许你有抵押贷款。

Maybe you have children.

也许你有孩子。

You can't afford to go off and take a course or get another degree.

你无法承担去参加课程或获得另一个学位的费用。

So you take a MOOC and you discover, I'm not quite as agile as I used to be in terms of learning, but it turns out with our course, you can boost your learning and so that even though your brain isn't learning as quickly, you can do it more efficiently.

所以你参加 MOOC 后你会发现，我在学习方面不像以前那么敏捷了，但事实证明，通过我们的课程，你可以提高你的学习能力，这样即使你的大脑学习得不那么快，你也可以更有效地学习。

Andrew Huberman:

安德鲁·休伯曼：

This is amazing.

这太棒了。

I want to take this course.

我想参加这门课程。

I will take this course.

我将参加这门课程。

What sort of time commitment is the course?

该课程需要投入什么样的时间？

You already pointed out that it's zero cost, which is amazing.

您已经指出它是零成本，这太棒了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Okay.

好的。

So, it's bite-sized videos lasting about 10 minutes each, and there's about 50 or 60 over a course of one month.

因此，它是每个持续约 10 分钟的小视频，一个月内大约有 50 或 60 个视频。

Andrew Huberman:

安德鲁·休伯曼：

And are you tested?

你经过测试了吗？

Are you self-tested?

你自测了吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

There are tests, there are quizzes, there are tests at the end, and there are forums where you can go and talk to other students.

有测试，有测验，最后有测试，还有论坛，您可以在那里与其他学生交谈。

You have questions, we have TAs.

你有问题，我们有助教。

Andrew Huberman:

安德鲁·休伯曼：

And anyone can do this?

任何人都可以做到这一点吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Anyone in the world.

世界上任何人。

In fact, we have people in India, housewives, who say, "Thank you, thank you, thank you, because I could have never learned about how to be a better learner.

事实上，在印度，有些家庭主妇会说：“谢谢你，谢谢你，谢谢你，因为我永远无法学会如何成为一个更好的学习者。

And I wish I had known this when I was going to school."

我希望我上学时就知道这一点。”

Andrew Huberman:

安德鲁·休伯曼：

Why do more people not know about this Learning to Learn course?

为什么越来越多的人不知道这门“学会学习”课程？

Although, as people know, if I get really excited about it or about anything, I'm never going to shut up about it.

不过，正如人们所知，如果我对它或任何事情感到非常兴奋，我永远不会对此闭嘴。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, but-

好吧，但是——

Andrew Huberman:

安德鲁·休伯曼：

But I'm going to take the course first because I want to understand the guts of it.

但我会先学习这门课程，因为我想了解它的本质。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

You'll enjoy it.

你会喜欢它的。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

We have like 98% approval.

我们获得了大约 98% 的支持。

It's just phenomenal.

这真是太神奇了。

It's sticky.

它很粘。

Andrew Huberman:

安德鲁·休伯曼：

Is it math, vocabulary?

是数学、词汇吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No math, no vocabulary.

没有数学，没有词汇。

We're not teaching anything specific.

我们不教任何具体的东西。

We're not trying to give you knowledge.

我们并不是想给你知识。

We're trying to tell you how to acquire knowledge and how to deal with exam anxiety, for example.

例如，我们试图告诉您如何获取知识以及如何应对考试焦虑。

We all procrastinate.

我们都会拖延。

We put things off.

我们把事情推迟了。

Andrew Huberman:

安德鲁·休伯曼：

Nah.

不。

No, I'm kidding.

不，我在开玩笑。

We all procrastinate.

我们都会拖延。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

How to avoid that.

如何避免这种情况。

We teach you how to avoid that.

我们教您如何避免这种情况。

Andrew Huberman:

安德鲁·休伯曼：

Fantastic.

太棒了。

Okay, I'm going to skip back a little bit now with the intention of double-clicking on this learning to learn thing.

好的，我现在要跳回一点，目的是双击这个学习学习的东西。

You pointed out that, in particular in California, but elsewhere as well, there isn't as much procedural practice-based learning anymore.

您指出，特别是在加利福尼亚州，但在其他地方也一样，不再有那么多基于程序的实践学习。

I'm going to play devil's advocate here, and I'm going to point out that this is not what I actually believe.

我要在这里唱反调，我要指出这并不是我真正相信的。

But when I was growing up, you had to do your times tables and your division and then your fractions and your exponents, and they build on one another.

但在我成长的过程中，你必须做乘法表、除法，然后是分数和指数，它们是相互构建的。

And then at some point, you take courses where you might need a graphing calculator.

然后在某个时候，您参加的课程可能需要图形计算器。

To some people, they can be like, "What is this?" But the point being that there were a number of things that you had to learn to implement, functions, and you learn by doing.

对于某些人来说，他们可能会问：“这是什么？”但重点是，有很多事情你必须学会实现、发挥作用，并且你可以通过实践来学习。

You learn by doing.

你边做边学。

Likewise, in physics class, we were attaching things to strings and for macro mechanics and learning that stuff.

同样，在物理课上，我们将物体附加到弦上，用于宏观力学并学习这些东西。

Okay.

好的。

And learning from the chalkboard lectures.

并从黑板讲座中学习。

I can see the value of both, certainly.

当然，我可以看到两者的价值。

And you explained that the brain needs both to really understand knowledge and how to implement and back and forth.

你解释说，大脑既需要真正理解知识，又需要如何来回实施。

But nowadays, you'll hear the argument, well, why should somebody learn how to read a paper map unless it's the only thing available because you have Google Maps?

但现在，你会听到这样的争论，好吧，为什么有人应该学习如何阅读纸质地图，除非它是唯一可用的东西，因为你有谷歌地图？

Or if they want to do a calculation, they just put it into the top bar function on the internet, and boom, out comes the answer.

或者，如果他们想要进行计算，他们只需将其放入互联网上的顶部栏功能中，然后“砰”的一声，答案就出来了。

So there is a world where certain skills are no longer required, and one could argue that the brain space and activity and time and energy, in particular, could be devoted to learning new forms of knowledge that are going to be more practical in the school and workforce going forward.

因此，在这个世界上，某些技能不再被需要，人们可以说，大脑空间、活动、时间和精力，特别是可以用来学习新形式的知识，这些知识在未来的学校和劳动力中将更加实用。

So how do we reconcile these things?

那么我们如何协调这些事情呢？

I'm of the belief that the brain is doing math, and you and I agree.

我相信大脑正在做数学，你和我都同意。

It's electrical signals and chemical signals, and it's doing math, and it's running algorithms.

它是电信号和化学信号，它正在做数学，它正在运行算法。

I think you convinced us of that, certainly.

我想你当然让我们相信了这一点。

But how are we to discern what we need to learn versus what we don't need to learn in terms of building a brain that's capable of learning the maximum number of things, or even enough things, so that we can go into this very uncertain future?

但是，我们如何辨别我们需要学习什么和不需要学习什么，以构建一个能够学习最大数量的事物，甚至足够的事物的大脑，以便我们能够进入这个非常不确定的未来呢？

Because as far as you know and I know, neither of us have a crystal ball.

因为据你和我所知，我们都没有水晶球。

So what is essential to learn?

那么学习什么是必须的呢？

And for those of us that didn't learn certain things in our formal education, what should we learn how to learn?

对于我们这些在正规教育中没有学到某些东西的人来说，我们应该学会如何学习？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, this is generational.

嗯，这是一代人的。

Okay.

好的。

So technologies provide us with tools.

所以技术为我们提供了工具。

You mentioned the calculator, right?

你提到了计算器，对吗？

Well, a calculator didn't eliminate the education you need to get in math, but it made certain things easier.

嗯，计算器并没有消除你需要接受的数学教育，但它使某些事情变得更容易。

It made it possible for you to do more things and more accurately.

它使您可以更准确地做更多事情。

However, interestingly, students in my class often come up with answers that are off by eight orders of magnitude, and that's a huge amount.

然而，有趣的是，我班上的学生经常得出八个数量级的答案，这是一个巨大的数字。

It's clear that they didn't key in the calculator properly, but they didn't recognize that it was completely way off the beam because they didn't have a good feeling for the numbers.

很明显，他们没有正确输入计算器，但他们没有意识到这完全偏离了目标，因为他们对数字没有良好的感觉。

They don't have a good sense of exactly how big it should have been, order of magnitude, basic understanding.

他们不太清楚它到底应该有多大、数量级、基本了解。

So the benefit is that you can do things faster, better, but then you also lose some of your intuition if you don't have the procedural system in place.

所以好处是你可以更快更好地做事，但如果你没有适当的程序系统，你也会失去一些直觉。

Andrew Huberman:

安德鲁·休伯曼：

I'm thinking about a kid that wants to be a musician who uses AI to write a song about a bad breakup that then is kind of recovered when they find new love, and I'm guessing that you could do this today and get a pretty good song out of AI, but would you call that kid a songwriter or a musician?

我正在考虑一个想成为一名音乐家的孩子，他使用人工智能写一首关于糟糕的分手的歌曲，然后当他们找到新的爱情时，这首歌就恢复了，我猜你今天可以做到这一点，并从人工智能中得到一首非常好的歌曲，但你会称那个孩子为词曲作者或音乐家吗？

On the face of it, yeah, the AI's helping, and then you'd say, well, that's not the same as sitting down with a guitar and trying out different chords and feeling the intonation in their voice.

从表面上看，是的，人工智能在帮忙，然后你会说，好吧，这和坐下来拿着吉他尝试不同的和弦并感受他们声音的语调不同。

But I'm guessing that for people that were on the electric guitar, they were criticizing people on the acoustic guitar.

但我猜想，对于那些弹电吉他的人来说，他们是在批评弹原声吉他的人。

So we have this generational thing-

所以我们有这个世代相传的东西——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

That's why I said-

这就是为什么我说——

Andrew Huberman:

安德鲁·休伯曼：

...

where we look back and say, "That's not the real thing.

当我们回头看时会说：“那不是真实的事情。

You need to get the..." So what are the key fundamentals is really a critical question.

你需要得到......”所以什么是关键的基础确实是一个关键问题。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

So I'm going to come back to that because the way you put it at the beginning had to do with how your brain is allocating resources, okay?

所以我要回到这个话题，因为你一开始的说法与你的大脑如何分配资源有关，好吗？

So when you're younger, you can take in things.

所以当你年轻的时候，你可以接受一些东西。

Your brain is more malleable.

你的大脑更具可塑性。

For example, how good are you on social media?

例如，您在社交媒体上的表现如何？

Andrew Huberman:

安德鲁·休伯曼：

Well, I do all my own Instagram and Twitter, and those accounts have grown in proportion to the amount of time I've been doing it.

好吧，Instagram 和 Twitter 都是我自己做的，而且这些账户的增长与我使用时间的增加成正比。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

So yeah, I would say pretty good.

所以是的，我会说非常好。

I'm not the biggest account on social media, but for a science health account, we're doing okay.

我不是社交媒体上最大的账户，但对于科学健康账户来说，我们做得还不错。

Thanks to the audience.

感谢观众。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, this speaks well for the fact that you've managed to go beyond the generation gap because-

嗯，这很好地说明了你们已经成功超越了代沟，因为——

Andrew Huberman:

安德鲁·休伯曼：

I can type with my thumbs, Terry.

我可以用拇指打字，特里。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

There you go.

就这样吧。

That's a manual skill that you learned.

这是您学到的手动技能。

Andrew Huberman:

安德鲁·休伯曼：

That's a new phenomenon in human evolution.

这是人类进化中的一个新现象。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I couldn't believe it.

我简直不敢相信。

I saw people doing that, and now I can do it, too.

我看到人们这样做，现在我也能做到。

But the thing is that if you learned how to do that early in life, you're much more good at it.

但问题是，如果你在很小的时候就学会了如何做到这一点，你就会更擅长。

You move your thumbs much more quickly.

你的拇指移动得更快。

Also, you can have many more tweets going and whatnot.

此外，您还可以发布更多推文等等。

What are they called now?

他们现在叫什么？

They're not called tweets.

它们不被称为推文。

Andrew Huberman:

安德鲁·休伯曼：

It's on X.

是在 X 上。

I think they still call them tweets because it's hard to verb the-

我认为他们仍然称其为推文，因为很难用动词来表达-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

The word X

单词X

Andrew Huberman:

安德鲁·休伯曼：

...

the letter X.

字母 X。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Andrew Huberman:

安德鲁·休伯曼：

Elon didn't think of that one.

埃隆没有想到这一点。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

I like X because it's cool.

我喜欢X，因为它很酷。

It's kind of punk, and it's got a black kind of format, and it fits with kind of the engineer, like black X, and that kind of thing.

它有点朋克风格，有一种黑色的格式，很适合工程师的风格，比如黑色的 X 之类的。

But yeah, we'll still call them tweets.

但是，是的，我们仍然称它们为推文。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay, we'll call them tweets.

好吧，我们称它们为推文。

Okay, that's good.

好吧，那很好。

But I walk across campus, and I see everybody, like half the people are tweeting.

但我走过校园，看到每个人，好像有一半的人在发推文。

Or they're doing something with their cell phone.

或者他们正在用手机做某事。

It's unbelievable.

真是难以置信。

Andrew Huberman:

安德鲁·休伯曼：

And you have beautiful sunsets at the Salk Institute.

在索尔克研究所可以欣赏到美丽的日落。

We'll put a link to one of them.

我们将放置其中之一的链接。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

It is truly spectacular, awe-inspiring to see a sunset at the Salk Institute.

在索尔克研究所观看日落确实非常壮观、令人惊叹。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Every day is different.

每一天都是不同的。

Andrew Huberman:

安德鲁·休伯曼：

And everyone's on their phones these days.

如今每个人都在使用手机。

Sad.

伤心。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And they're looking down at their phone and they're walking along, even people who are skateboarding.

他们低头看着手机，一边走一边走，即使是玩滑板的人也是如此。

Unbelievable.

难以置信。

It's amazing what the human being can do when they get into something.

当人类投入某件事时，他们能做出什么令人惊奇的事情。

But what happens is the younger generation picks up whatever technology it is, and the brain gets really good at it.

但发生的情况是，年轻一代接受了无论是什么技术，并且大脑变得非常擅长。

And you pick it up later, but you're not quite as agile, not quite as maybe obsessive.

后来你又拿起它，但你没有那么敏捷，也没有那么痴迷。

Andrew Huberman:

安德鲁·休伯曼：

It fatigues me.

这让我很疲惫。

I will point this out, that doing anything on my phone feels fatiguing in a way that reading a paper book or even just writing on a laptop or a desktop computer is fundamentally different.

我要指出的是，在手机上做任何事情都会让人感到疲劳，这与阅读纸质书或什至只是在笔记本电脑或台式电脑上书写有着根本的不同。

I can do that for many hours.

我可以这样做好几个小时。

If I'm on social media for more than a few minutes, I can literally feel the energy draining out of my body.

如果我在社交媒体上呆的时间超过几分钟，我真的能感觉到能量从我的身体中流失。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Interesting.

有趣。

Andrew Huberman:

安德鲁·休伯曼：

I could do sprints or deadlifts for hours and not feel the kind of fatigue that I feel from doing social media.

我可以连续几个小时进行短跑或硬拉，而不会像使用社交媒体时那样感到疲劳。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So this is fascinating.

所以这很有趣。

I'd like to know what's going on in your brain.

我想知道你脑子里在想什么。

And also, I'd like to know from younger people whether they have the same.

而且，我想知道年轻人是否也有同样的情况。

I think not.

我认为不是。

I think my guess is that they don't feel fatigue because they got into this early enough.

我想我的猜测是他们不会感到疲劳，因为他们进入得足够早。

And this is actually a very, very-- I think that it has a lot to do with the foundation you put into your brain.

这实际上是一个非常非常-我认为这与你为大脑打下的基础有很大关系。

In other words, things that you learn when you're really young are foundational, and they make things easier, some things easier later on.

换句话说，你在年轻时学到的东西是基础性的，它们会让事情变得更容易，有些事情以后会变得更容易。

Andrew Huberman:

安德鲁·休伯曼：

Yeah, I spent a lot of time in my room as a kid, either playing with Legos or action figures, or building fish tanks, or reading about fish.

是的，我小时候花了很多时间在我的房间里，要么玩乐高积木或人偶，要么建造鱼缸，要么阅读有关鱼类的文章。

I tended to read about things and then do a lot of procedural-based activities.

我倾向于阅读相关内容，然后进行许多基于程序的活动。

I would read skateboard magazines and skateboard.

我会阅读滑板杂志和滑板。

I was never one to really just watch a sport and not play it.

我从来都不是一个只观看一项运动而不参与其中的人。

So bridging across these things.

所以跨越这些事情。

So social media, to me, feels like an energy sink.

所以对我来说，社交媒体感觉就像一个能量池。

But of course, I love the opportunity to be able to teach to people and learn from people at such scale.

当然，我很高兴有机会能够向人们进行如此大规模的教学并向人们学习。

But at an energetic level, I feel like I don't have a foundation for it.

但在能量层面上，我觉得我没有基础。

It's like I'm trying to-

就好像我正在尝试-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

jerry-rig my cognition into doing something that it wasn't designed to do.

偷工减料地操纵我的认知去做一些它本来就不该做的事情。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, there you go, and it's because you don't have the foundation.

好吧，那是因为你没有基础。

You didn't do it when you were younger, and now you have to sort of use the cognitive powers to do a lot of what was being done now in a younger person procedurally.

当你年轻的时候你没有这样做，现在你必须使用认知能力来按程序做很多现在年轻人正在做的事情。

Andrew Huberman:

安德鲁·休伯曼：

I'd like to take a quick break and thank one of our sponsors, LMNT.

我想稍微休息一下并感谢我们的赞助商之一 LMNT。

LMNT is an electrolyte drink that has everything you need and nothing you don't.

LMNT 是一种电解质饮料，拥有您需要的一切，没有您不需要的东西。

That means the electrolytes, sodium, magnesium, and potassium in the correct ratios, but no sugar.

这意味着电解质、钠、镁和钾的比例正确，但没有糖。

We should all know that proper hydration is critical for optimal brain and body function.

我们都应该知道，适当的水分对于最佳的大脑和身体功能至关重要。

In fact, even a slight degree of dehydration can diminish your cognitive and physical performance to a considerable degree.

事实上，即使是轻微程度的脱水也会在很大程度上降低您的认知和身体表现。

It's also important that you're not just hydrated, but that you get adequate amounts of electrolytes in the right ratios.

同样重要的是，您不仅要补充水分，还要以正确的比例获得足量的电解质。

Drinking a packet of LMNT dissolved in water makes it very easy to ensure that you're getting adequate amounts of hydration and electrolytes.

喝一包溶解在水中的 LMNT 可以很容易地确保您获得足够的水分和电解质。

To make sure that I'm getting proper amounts of both, I dissolve one packet of LMNT in about 16 to 32 ounces of water when I wake up in the morning, and I drink that basically first thing in the morning.

为了确保我摄入适量的两者，当我早上醒来时，我将一包 LMNT 溶解在大约 16 至 32 盎司的水中，并且我基本上早上第一件事就是喝它。

I'll also drink a packet of LMNT dissolved in water during any kind of physical exercise that I'm doing, especially on hot days when I'm sweating a lot and losing water and electrolytes.

在进行任何体育锻炼时，我还会喝一包溶解在水中的 LMNT，尤其是在炎热的日子里，当我大量出汗并失去水分和电解质时。

There are a bunch of different great-tasting flavors of LMNT.

LMNT 有多种不同的美味口味。

I like the watermelon, I like the raspberry, I like the citrus.

我喜欢西瓜，我喜欢覆盆子，我喜欢柑橘。

Basically, I like all of them.

基本上，我都喜欢。

If you'd like to try LMNT, you can go to drinklmnt.com/huberman to claim an LMNT sample pack with the purchase of any LMNT drink mix.

如果您想尝试 LMNT，可以访问 Drinklmnt.com/huberman，购买任何 LMNT 混合饮料即可领取 LMNT 样品包。

Again, that's Drink LMNT, spelled L-M-N-T, so it's drinklmnt.com/huberman to claim a free sample pack.

同样，这是 Drink LMNT，拼写为 L-M-N-T，因此可以通过 Drinklmnt.com/huberman 索取免费样品包。

Today's episode is also brought to us by Joovv.

今天的节目也是Joovv给我们带来的。

Joovv makes medical-grade red light therapy devices.

Joovv 生产医疗级红光治疗设备。

Now, if there's one thing that I've consistently emphasized on this podcast, is the incredible impact that light can have on our biology.

现在，如果我在这个播客中一直强调一件事，那就是光对我们的生物学产生的令人难以置信的影响。

Now, in addition to sunlight, red light and near-infrared light have been shown to have positive effects on improving numerous aspects of cellular and organ health, including faster muscle recovery, improved skin health and wound healing, improvements in acne, reduced pain and inflammation, improved mitochondrial function, and even improving vision itself.

现在，除了阳光之外，红光和近红外光已被证明对改善细胞和器官健康的许多方面具有积极作用，包括更快的肌肉恢复、改善皮肤健康和伤口愈合、改善痤疮、减少疼痛和炎症、改善线粒体功能，甚至改善视力本身。

Now, what sets Joovv lights apart, and why they're my preferred red light therapy devices, is that they use clinically proven wavelengths.

现在，Joovv 灯的与众不同之处以及它们成为我首选红光治疗设备的原因是它们使用经过临床验证的波长。

Meaning they use specific wavelengths of red light and near-infrared light in combination to trigger the optimal cellular adaptations.

这意味着它们结合使用特定波长的红光和近红外光来触发最佳的细胞适应。

Personally, I use the Joovv whole body panel about three to four times a week, and I use the Joovv handheld light both at home and when I travel.

就我个人而言，我每周大约使用 Joovv 全身面板三到四次，在家和旅行时我都会使用 Joovv 手持灯。

If you'd like to try Joovv, you can go to Joovv, spelled J-O-O-V-V .com/huberman.

如果您想尝试 Joovv，可以访问 Joovv，拼写为 J-O-O-V-V .com/huberman。

Joovv is offering Black Friday discounts of up to $1,300 now through December 2nd, 2024.

Joovv 即日起至 2024 年 12 月 2 日提供黑色星期五折扣，最高可达 1,300 美元。

Again, that's Joovv, J-O-O-V-V .com/huberman to get up to $1,300 off select Joovv products.

同样，这就是 Joovv，J-O-O-V-V .com/huberman，精选 Joovv 产品可享受高达 1,300 美元的折扣。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I'm going to tell you something which is going to help all of your listeners.

我要告诉你一些对所有听众都有帮助的事情。

My book, "ChatGPT and the Future of AI," I went through and I looked at other people's experiences with ChatGPT.

我阅读了我的书《ChatGPT 和人工智能的未来》，并查看了其他人使用 ChatGPT 的体验。

I just wanted to know what people were thinking.

我只是想知道人们在想什么。

And I came across, it was an article, I think it was in The New York Times, of a technical writer who decided she would spend one month using it to help her write things, her articles.

我偶然发现，这是一篇文章，我想是在《纽约时报》上，一篇技术作家的文章，她决定花一个月的时间用它来帮助她写东西，她的文章。

And she said that when she started out, at the end of the day she was drained, completely drained, and it was like working on a machine, like a tractor or something.

她说，当她开始工作时，一天结束时，她精疲力尽，完全精疲力尽，就像在一台机器上工作，比如拖拉机什么的。

You're struggling to get it to work.

你正在努力让它发挥作用。

And then she said, "Well, wait a second.

然后她说：“好吧，等一下。

What if I treat it like a human being?

如果我像对待人一样对待它怎么办？

What if I'm polite instead of being curt?" She said, "Suddenly, I started getting better answers by being polite and back and forth the way you would with a human."

如果我有礼貌而不是生硬怎么办？”她说：“突然间，我开始通过礼貌和来回的方式得到更好的答案，就像对待人类一样。”

Andrew Huberman:

安德鲁·休伯曼：

So saying, "Could you please give me information about so and so?"

所以说，“你能给我一些关于某某的信息吗？”

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

"Please, I'm really having trouble.

“拜托，我真的遇到麻烦了。

And oh, that answer you gave me was fabulous, is exactly what I was looking for.

哦，你给我的答案太棒了，这正是我正在寻找的。

And now I need you to go on to the next part and help me with that too." In other words, the way you talk to a human, right, if an assistant that you have.

现在我需要你继续下一部分并帮助我。”换句话说，就是你与人交谈的方式，对吧，如果你有助手的话。

Andrew Huberman:

安德鲁·休伯曼：

Or is it that she was talking to the AI, to ChatGPT, it sounds like in this case, in the way that her brain was familiar with asking questions to a human?

或者她是在与人工智能、ChatGPT 交谈，在这种情况下听起来像是她的大脑熟悉向人类提问的方式？

In other words-

换句话说——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

so is the AI learning her and therefore giving her the sorts of answers that are more facile for her to integrate with?

那么人工智能是否正在学习她，从而为她提供更容易融入的答案？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I think it's both.

我认为两者都是。

Well, first of all, the ChatGPT is mirroring the way you treat it, it will mirror that back.

嗯，首先，ChatGPT 反映了你对待它的方式，它也会反映出来。

You treat it like a machine, it will treat you like a machine, okay?

你把它当作一台机器，它也会把你当作一台机器，好吗？

Because that's what it's good at.

因为这就是它所擅长的。

But here's the surprise.

但令人惊讶的是。

The surprise is she said, "Once I started treating it like a human, at the end of the day, I wasn't fatigued anymore." Why?

令人惊讶的是，她说：“一旦我开始像人一样对待它，一天结束时，我就不再感到疲劳了。”为什么？

Well, it turns out that all your life, you interact with humans in a certain way, and your brain is wired to do that, and it doesn't take any effort.

事实证明，在你的一生中，你都以某种方式与人类互动，你的大脑天生就会这样做，而且不需要任何努力。

And so by treating the ChatGPT as if it were a human, you're taking advantage of all the brain circuits in your brain.

因此，通过将 ChatGPT 视为人类，您就可以利用大脑中的所有大脑回路。

Andrew Huberman:

安德鲁·休伯曼：

This is incredible, and I'll tell you why, because I think many people, not just me, but many people really enjoy social media, learn from it.

这太不可思议了，我会告诉你原因，因为我认为很多人，不仅仅是我，还有很多人都非常喜欢社交媒体，并从中学习。

Yesterday I learned a few things that I thought were just fascinating about how we perceive our own identity according to whether or not we're filtering it through the responses of others, or whether or not we take a couple of minutes and really just sit and think about how we actually feel about ourselves.

昨天，我学到了一些我认为很有趣的事情，关于我们如何感知自己的身份，根据我们是否通过他人的反应过滤它，或者我们是否花几分钟坐下来思考我们对自己的实际感受。

Very interesting ideas about locus of self-perception and things like that.

关于自我感知之类的非常有趣的想法。

I also looked at a really cool video of a baby raccoon popping bubbles while standing on its hind limbs, and that was really cool, and social media could provide me both those things within a series of minutes.

我还观看了一段非常酷的视频，视频中一只小浣熊用后肢站立，弹出泡泡，这真的很酷，社交媒体可以在几分钟内为我提供这两件事。

And I was thinking to myself, "This is crazy." Right?

我心里想：“这太疯狂了。”正确的？

The raccoon is kind of trivial, but it delighted me, and that's not trivial.

浣熊有点微不足道，但它让我很高兴，这并不微不足道。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

There you go.

就这样吧。

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

But here's the question.

但问题是这样的。

Could it be that one of the detrimental aspects of social media is that if we're complimenting one another, or if we are giving hearts, or we're giving thumbs downs, or we're in an argument with somebody, or we're doing a clap back, or they're clapping back on us, or dunking, as it's called, on X, that it isn't necessarily the way that we learned to argue.

社交媒体的有害方面之一是否是，如果我们互相称赞，或者我们给予爱心，或者我们表示反对，或者我们与某人争论，或者我们反击，或者他们反击我们，或者在X上扣篮，这不一定是我们学会争论的方式。

It's not necessarily the way that we learn to engage in healthy dispute.

这不一定是我们学习进行健康争论的方式。

And so, as a consequence, it feels like, and this is my experience, that certain online interactions feel really good, and others feel like they kind of grate on me, because there's almost like an action step that isn't allowed.

因此，感觉就像，这是我的经验，某些在线互动感觉非常好，而其他人则觉得他们有点让我恼火，因为几乎有一个行动步骤是不允许的。

You can't fully explain yourself or understand the other person.

你无法完全解释自己或理解对方。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And I am somebody who believes in the power of real face-to-face dialogue, or at least on the phone dialogue.

我相信真正的面对面对话，或者至少是电话对话的力量。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And I feel the same way about text messaging.

我对短信也有同样的感觉。

I hate text messaging.

我讨厌短信。

When text messaging first came out, I remember thinking, I was not a kid that passed notes in class.

当短信第一次出现时，我记得我在想，我不是一个在课堂上传纸条的孩子。

This feels like passing notes in class.

这感觉就像在课堂上传递笔记一样。

In fact, this whole text messaging thing is beneath me.

事实上，这整个短信的事情对我来说是不重要的。

That's how I felt.

我就是这么感觉的。

And over the years, of course, I became a text messenger.

当然，多年来，我成为了一名文字通讯员。

And it's very useful for certain things, be there in five minutes, running a few minutes late.

它对于某些事情非常有用，五分钟内到达，迟到几分钟。

In my case, that's a common one.

就我而言，这是一种常见的情况。

But I think this notion of what grates on us, and as it relates to whether or not it matches our childhood-developed template of how our brain works, is really key because it touches on something that I definitely want to talk about today that I know you've worked on quite a bit, which is this concept of energy.

但我认为这个让我们恼火的概念，以及它是否符合我们童年时期开发的大脑工作模式，非常关键，因为它触及了我今天肯定想谈论的东西，我知道你已经做了很多工作，这就是能量的概念。

What we're talking about here is energy.

我们这里讨论的是能量。

Not woo biology, woo science, wellness energy.

不是追求生物学、追求科学、健康能源。

We're talking about we only have a finite amount of energy.

我们谈论的是我们只有有限的能量。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Mm-hmm.

嗯嗯。

Andrew Huberman:

安德鲁·休伯曼：

And years ago, the great Ben Barris sadly passed away, our former colleague and my postdoc advisor, came to me one day in the hallway, and he stopped me, and he said, he called me Andy, like you do, and he said, "Andy, how come we get such a rundown of energy as we get older?

几年前，伟大的本·巴里斯不幸去世了，我们的前同事和我的博士后导师有一天在走廊里来找我，他拦住了我，他说，他叫我安迪，就像你一样，他说，“安迪，为什么随着年龄的增长，我们的精力会如此枯竭呢？

Why am I more tired today than I was 10 years ago?" I was like, "I don't know.

为什么我今天比十年前更累？”我当时想，“我不知道。

How are you sleeping?" He's like, "I'm sleeping fine." Ben never slept much in the first place, but he had a ton of energy.

你睡得怎么样？”他说：“我睡得很好。”本一开始就睡得不多，但他精力充沛。

And I thought to myself, I don't know.

我心想，我不知道。

What is this energy thing that we're talking about?

我们所说的能量是什么？

I want to make sure that we close the hatch on this notion of a template neural system that then you either find the experience is invigorating or depleting.

我想确保我们关闭模板神经系统概念的舱口，然后你会发现体验是令人振奋的还是耗尽的。

I want to make sure we close the hatch on that, but I want to make sure that we relate it at some point to this idea of energy, and why is it that with each passing year of our life, we seem to have less of it?

我想确保我们关闭了这个问题，但我想确保我们在某个时候将其与能量的概念联系起来，为什么随着我们生命的流逝，我们拥有的能量似乎越来越少？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

You ask these great questions, and I wish that I had great answers.

你问了这些很棒的问题，我希望我能得到很好的答案。

Andrew Huberman:

安德鲁·休伯曼：

Well, so far you really do have great answers.

好吧，到目前为止你确实已经有了很好的答案。

They're certainly novel to me in the sense that I've not heard answers of this sort.

它们对我来说确实很新颖，因为我还没有听到过此类答案。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Ah, okay.

啊，好吧。

Andrew Huberman:

安德鲁·休伯曼：

So there's a tremendous amount of learning for me today, and I know for the audience.

所以今天我学到了很多东西，我也知道观众。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Cool.

凉爽的。

Andrew Huberman:

安德鲁·休伯曼：

But let's say somebody is 20 years old versus 50 years old.

但假设某人的年龄是 20 岁，而另一个人是 50 岁。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

What should they do?

他们应该做什么？

We need to integrate with the modern world.

我们需要融入现代世界。

We also need to relate across generations.

我们还需要跨代联系。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, yeah.

哦，是的。

No, this is true.

不，这是真的。

Andrew Huberman:

安德鲁·休伯曼：

People aren't retiring as much.

人们没有那么多退休。

They're living longer.

他们活得更久了。

Birth rates are down.

出生率下降。

But we have to all get along, as they say.

但正如他们所说，我们必须和睦相处。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So, it is interesting, and I think it's true that we all, as we get older, have less of the vigor.

所以，这很有趣，我认为随着年龄的增长，我们所有人的活力确实会减弱。

Vigor, if I could use a somewhat different word from energy.

活力，如果我可以使用与能量有所不同的词的话。

We'll come back to that.

我们稍后会回来讨论这一点。

But I think there are some who manage to keep an active life.

但我认为有些人设法保持积极的生活。

And here's- Something that, again, in our MOOC, we really emphasize.

这是——在我们的 MOOC 中，我们再次强调的一点。

Andrew Huberman:

安德鲁·休伯曼：

Could you explain a MOOC?

您能解释一下 MOOC 吗？

I think most people won't know what a MOOC is, just for their sake.

我认为大多数人不会知道 MOOC 是什么，只是为了他们自己。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

They've been around for about...

他们已经存在了大约...

Actually it started at Stanford, Andrew Ng and Daphne Koller.

事实上，它始于斯坦福大学的吴恩达 (Andrew Ng) 和达芙妮·科勒 (Daphne Koller)。

So they have a company called Coursera, and what happens is that you get professors and, in fact, anybody who has knowledge or professional expertise to give lectures that are available to anybody in the world who have access to the internet, and there's probably tens of thousands now.

因此，他们有一家名为 Coursera 的公司，所发生的事情是，你会得到教授，事实上，任何拥有知识或专业知识的人都可以为世界上任何可以访问互联网的人提供讲座，现在可能有数以万计。

Any specialty, history, science, music, you name it, there's somebody who's an expert on that and wants to tell you because they're excited about what they're doing.

任何专业，历史、科学、音乐，凡是你能想到的，都会有人是这方面的专家，并且想告诉你，因为他们对自己正在做的事情感到兴奋。

Okay.

好的。

So what we wanted to do was to help people with learning.

所以我们想做的就是帮助人们学习。

And so part of the problem is that it gets more difficult, it takes more effort as you get older.

所以问题的一部分在于，随着年龄的增长，它会变得更加困难，需要付出更多的努力。

Andrew Huberman:

安德鲁·休伯曼：

It depletes your vigor more, if we're going to stay with this language of energy and vigor.

如果我们继续使用这种充满能量和活力的语言，它会进一步消耗你的活力。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

That's right.

这是正确的。

So let's actually use the word energy.

因此，让我们实际使用“能量”这个词。

As you know, in the cell, there is a physical power plant called the mitochondrion, which is supplying us with ATP, which is the coin of the realm for the cell to be able to operate all of its machinery, right?

如您所知，在细胞中，有一个称为线粒体的物理发电厂，它为我们提供 ATP，这是细胞能够运行其所有机器的王国的硬币，对吗？

And so one of the things that happens when you get older is that your mitochondrial run down.

因此，当你变老时发生的事情之一就是你的线粒体耗尽。

Andrew Huberman:

安德鲁·休伯曼：

You have fewer of them and they're less efficient.

他们的数量较少，而且效率也较低。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

They're less efficient.

他们效率较低。

And actually, drugs can do that to you, too.

事实上，药物也会对你造成这种影响。

They can harm mitochondria.

它们会损害线粒体。

Andrew Huberman:

安德鲁·休伯曼：

Oh, recreational drugs?

噢，消遣性毒品？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, the drugs you take for illness.

不，是你生病时服用的药物。

I'm not sure about recreational drugs, but I know it's the case that there are a lot of drugs that people take because they have to.

我不确定消遣性药物的情况如何，但我知道人们服用很多药物是因为他们不得不这样做。

But the other thing, and that's the bad news.

但另一件事，那就是坏消息。

Here's the good news.

这是好消息。

The good news is that you can replenish your energy by exercise.

好消息是你可以通过锻炼来补充能量。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That exercise is the best drug you could ever take.

这种锻炼是你能服用的最好的药物。

It's the cheapest drug you could ever take that can help every organ in your body.

这是您可以服用的最便宜的药物，可以帮助您体内的每个器官。

It helps, obviously, your heart.

显然，它对你的心脏有帮助。

It helps your brain.

它可以帮助你的大脑。

It rejuvenates your brain.

它可以让你的大脑恢复活力。

It helps your immune system.

它有助于您的免疫系统。

Every single organ system in the body benefits from regular exercise.

身体的每个器官系统都受益于定期锻炼。

I run on the beach every day at the Salk Institute.

我每天在索尔克研究所的海滩上跑步。

And I also, it's on a mesa 340 foot above, so I go down every day, and then I climb up the cliff.

我也是，它在海拔 340 英尺的平顶山上，所以我每天都会下去，然后爬上悬崖。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Those steps down to Black's Beach, they're a good workout.

沿着通往布莱克海滩的台阶，这是一次很好的锻炼。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

They are.

他们是。

And so this is something that has kept me active, and I do hiking.

所以这让我保持活跃，我徒步旅行。

I went hiking in the Alps last fall, in September.

去年秋天九月我去阿尔卑斯山徒步旅行。

So this is, I think, something that people really ought to realize, is that it's like putting away reserves of energy for when you get older.

所以，我认为，人们真正应该意识到，这就像为变老时储备能量一样。

The more you put away, the better off you are.

你存的越多，你的生活就越好。

Here's something else, okay?

这是别的东西，好吗？

Now, this is jumping now to Alzheimer's.

现在，情况正转向阿尔茨海默病。

So a study that was done in China many years ago, when I first came to La Jolla, San Diego, I heard this from the head of the Alzheimer's program.

因此，多年前在中国进行的一项研究，当我第一次来到圣地亚哥拉霍亚时，我从阿尔茨海默氏症项目的负责人那里听到了这一点。

He had done a study in China on onset, and they went and they had three populations.

他在中国做了一项关于发病的研究，他们去了，发现了三个人群。

They had peasants who had almost no education, then they had another group that had high school education, and then there were people who had advanced education.

他们有几乎没有受过教育的农民，然后有另一群受过高中教育的人，然后还有受过高等教育的人。

So it turns out that the onset of Alzheimer's was earlier for the people who had no education, and it was the latest for the people who had the most education.

事实证明，没有受过教育的人患阿尔茨海默病的时间较早，而受教育程度最高的人患阿尔茨海默病的时间最晚。

Now, this is interesting, isn't it?

现在，这很有趣，不是吗？

And presumably, the genes aren't that different, right?

据推测，基因并没有那么不同，对吧？

I mean, they're all Chinese.

我的意思是，他们都是中国人。

So one possibility, and obviously we don't really know why, but one possibility is that the more you exercise your brain with education, the more reserve you have later in life.

所以一种可能性，显然我们并不真正知道为什么，但一种可能性是，你通过教育锻炼你的大脑越多，你在以后的生活中拥有的储备就越多。

Andrew Huberman:

安德鲁·休伯曼：

I believe in the notion, and I don't have a better word for it, maybe you do, or phrase for it, is of kind of a cognitive velocity.

我相信这个概念，我没有更好的词来形容它，也许你相信，或者用短语来形容它，是一种认知速度。

I sometimes will play with this.

我有时也会玩这个。

I'll read slowly, or I'll see where my default pace of reading is at a given time of day, and then I'll intentionally try and read a little bit faster while also trying to retain the knowledge I'm reading.

我会慢慢地阅读，或者我会看看我在一天中的特定时间的默认阅读速度，然后我会有意地尝试阅读得更快一点，同时也尝试保留我正在阅读的知识。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So I'm not just reading the words, I'm trying to absorb the information.

所以我不只是阅读文字，我还试图吸收信息。

And you can feel the energetic demand of that.

你可以感受到它的能量需求。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, yes.

哦，是的。

Andrew Huberman:

安德鲁·休伯曼：

And then I'll play with it.

然后我会玩它。

I'll kind of back off a little bit, and then I'll go forward, and I try and find the sweet spot where I'm not reading at the pace that is reflexive, but just a little bit quicker while also trying to retain the information.

我会稍微后退一点，然后继续前进，我会尝试找到最佳点，即我不以条件反射的速度阅读，而是稍微快一点，同时也试图保留信息。

And I learned this when I had a lot of catching up to do at one phase of my educational career.

当我在教育生涯的某个阶段有很多事情要做时，我学到了这一点。

Fortunately, it was pretty early and I was able to catch up on most things.

幸运的是，时间还早，我能够赶上大部分事情。

Occasionally things slip through and I have to go back and learn how to learn.

有时候事情会溜走，我必须回去学习如何学习。

And if I get anything wrong on the internet, they sure as heck point it out, and then we go back and learn.

如果我在互联网上发现任何错误，他们肯定会指出来，然后我们回去学习。

And guess what?

你猜怎么着？

I never forget that because punishment-

我永远不会忘记这一点，因为惩罚——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Punishment

惩罚

Andrew Huberman:

安德鲁·休伯曼：

...

social punishment is a great signal.

社会惩罚是一个很好的信号。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

So thank you, all, for keeping me learning.

所以谢谢大家让我不断学习。

But I picked that up from my experience of trying to get good at things like skateboarding or soccer when I was younger.

但我从年轻时尝试擅长滑板或足球等事情的经历中学到了这一点。

There's a certain thing that happens when skateboarding, that was my sport growing up, where it's actually easier to learn something going faster.

滑板时会发生一些事情，滑板是我成长过程中的运动，实际上更容易学习速度更快的东西。

Most kids try and learn how to ollie and kickflip standing in the living room on the carpet.

大多数孩子都会尝试站在客厅的地毯上学习如何奥利和踢空翻。

That's the worst way to learn how to do it.

这是学习如何做到这一点的最糟糕的方法。

It's all easier going a bit faster than you're comfortable.

比你舒服的速度更快一点更容易。

It's also The case that if you're not paying attention, you can get hurt.

还有一种情况是，如果你不注意，你可能会受伤。

It's also the case that if you pay too much cognitive attention, you can't perform the motor movements.

还有一种情况是，如果你投入过多的认知注意力，你就无法进行运动。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So there's this sweet spot that eventually I was able to translate into an understanding of when I sit down to read a paper or a news article, or even listen to a podcast, there's a pace of the person's voice, and then I'll adjust the rate of the audio, where I have to engage cognitively, and I know I'm in a mode of retaining the information and learning.

因此，最终我能够将这个最佳点转化为一种理解，即当我坐下来阅读报纸或新闻文章，甚至听播客时，人们的声音有节奏，然后我会调整音频的速率，我必须进行认知参与，并且我知道我处于保留信息和学习的模式。

Whereas if I just go with my reflexive pace, it's rare that I'm in that perfect zone.

然而，如果我只是按照我的反射性步伐前进，我就很少处于那个完美的区域。

So I point this out because perhaps it will be useful to people.

所以我指出这一点是因为也许它对人们有用。

I don't know if it's incorporated into your Learning How to Learn course, but I do think that there is something which I call kind of cognitive velocity, which is ideal for learning, versus kind of leisurely scrolling.

我不知道它是否已纳入您的学习如何学习课程中，但我确实认为有一种我称之为认知速度的东西，这对于学习来说是理想的，而不是悠闲地滚动。

And this is why I think that social media is detrimental.

这就是为什么我认为社交媒体是有害的。

I think that we-

我认为我们——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

train our brain basically to be slow, passive, and multi-context cycling through, and unless something is very high salience, it kind of makes us kind of fat and lazy, forgive the language, but I'm going to be blunt here, fat and lazy cognitively, unless we make it a point-

训练我们的大脑基本上是缓慢的、被动的、多情境循环的，除非某些东西非常显着，否则它会让我们有点肥胖和懒惰，请原谅我们的语言，但我要在这里直言不讳，在认知上肥胖和懒惰，除非我们明确指出——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

to also engage learning.

也参与学习。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And my guess is it's tapping into this mitochondrial system.

我的猜测是它正在利用线粒体系统。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Very likely.

很有可能。

That's one part of it.

这是其中的一部分。

By the way, the way that you've adjusted the speed is very interesting because it turns out that stress, everybody thinks, "Oh, stress is bad," but no, it turns out stress that is transient, that is only for a limited amount of time, that you control, is good for you, is good for your brain, is good for your body.

顺便说一句，你调整速度的方式非常有趣，因为事实证明压力，每个人都认为，“哦，压力是不好的”，但事实并非如此，事实证明压力是短暂的，只在有限的时间内由你控制，对你有好处，对你的大脑有好处，对你的身体有好处。

I run intervals on the beach just the way that you do cognitive intervals when you're reading.

我在海滩上进行间歇跑，就像你在阅读时进行认知间歇跑一样。

In other words, I run like hell for about 10 seconds, and then I-

换句话说，我拼命跑了大约 10 秒钟，然后我——

Andrew Huberman:

安德鲁·休伯曼：

毫米

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

go to a jog, and I run like hell for another 10 seconds, and it's pushing your body into that extra gear that helps the muscles.

去慢跑，我又拼命跑 10 秒钟，这会推动你的身体进入额外的状态，帮助肌肉锻炼。

The muscles need to know that this is what they've got to put out, and that's where you gain muscle mass, not from just doing the same running pace every day.

肌肉需要知道这是他们必须付出的努力，这就是你获得肌肉质量的地方，而不是仅仅通过每天以相同的速度跑步。

Andrew Huberman:

安德鲁·休伯曼：

Well, your intellectual and physical vigor is undeniable.

好吧，你的智力和体力活力是不可否认的。

I've known you a long time.

我认识你很久了。

You've always had a slight forward center of mass in your intellect, and even the speed at which you walk, Terry, dare I say.

我敢说，特里，你的智力，甚至你走路的速度，总是有一个稍微靠前的重心。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

For a Californian, you're a quick walker.

对于加州人来说，你走得很快。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

So, that's a compliment, by the way.

所以，顺便说一句，这是一种恭维。

East Coasters know what I'm talking about, and Californians would be like, "Why not slow down?" The reason to not slow down too much for too long is that these mitochondrial systems, the energy of the brain and body, as you point out, are very linked.

东海岸人知道我在说什么，而加州人会说，“为什么不放慢速度呢？”不能长时间放慢速度的原因是，正如您所指出的，这些线粒体系统、大脑和身体的能量是紧密相连的。

And I do think that below a certain threshold, it makes it very hard to come back, just like below a certain threshold, it's hard to exercise without getting very depleted or even injured.

我确实认为，低于某个阈值，就很难恢复，就像低于某个阈值，很难在不耗尽甚至受伤的情况下进行锻炼。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Andrew Huberman:

安德鲁·休伯曼：

That we need to maintain this.

我们需要维持这一点。

So perhaps now would be a good time to close the hatch on this issue of how to teach young people.

因此，也许现在是结束如何教育年轻人这个问题的好时机。

Everyone should take this Learning to Learn course as a free resource.

每个人都应该将学习学习课程作为免费资源。

Amazing.

惊人的。

As it relates to AI, do you think that young people and older people now, I'm 49, so I'll put myself in the older bracket, should be learning how to use AI?

说到人工智能，你认为现在的年轻人和老年人，我49岁了，所以我把自己放在老年人的范围内，应该学习如何使用人工智能吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

They are already learning how to use AI.

他们已经在学习如何使用人工智能。

And, again, it's just like new technology comes along, who picks it up first?

再说一次，就像新技术出现一样，谁先接受它？

It's the younger people.

这是年轻人。

And it's astonishing.

这真是令人惊讶。

They're using it a lot more than I am.

他们使用它的次数比我多得多。

I use it almost every day, but I know a lot of students who basically...

我几乎每天都使用它，但我认识很多学生基本上...

And by the way, it's like any other tool.

顺便说一句，它就像任何其他工具一样。

It's a tool that you need to know how to use it.

这是一个你需要知道如何使用的工具。

Andrew Huberman:

安德鲁·休伯曼：

Where do you suggest people start?

您建议人们从哪里开始？

So, I have started using Claude AI.

所以，我开始使用Claude AI。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

This was suggested to me by somebody expert in AI as an alternative to ChatGPT.

这是人工智能专家向我建议的，作为 ChatGPT 的替代方案。

I don't have anything against ChatGPT, but I'll tell you, I really like the aesthetic of Claude AI.

我对 ChatGPT 没有任何反对意见，但我告诉你，我真的很喜欢 Claude AI 的美学。

It's a bit of a softer, beige aesthetic.

这是一种更柔和的米色美学。

It feels kind of Apple-like.

感觉有点像苹果。

I like the Apple brand.

我喜欢苹果这个品牌。

And it gives me answers, maybe it's the font, maybe it's the feel, maybe this goes back to the example you used earlier, where I like Claude AI, and I'm a big fan of it, and they don't pay me to say this.

它给了我答案，也许是字体，也许是感觉，也许这又回到了你之前使用的例子，我喜欢 Claude AI，而且我是它的忠实粉丝，他们没有付钱让我说这个。

I've never met them.

我从未见过他们。

I have no relationship to them except that it gives me answers in a bullet-pointed format that feels very aesthetically easy to transfer that information into my brain or onto a page.

我和他们没有任何关系，只是它以项目符号格式给我答案，感觉很容易将这些信息转移到我的大脑或页面上。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So I like Claude AI.

所以我喜欢克劳德·艾伊。

Use ChatGPT.

使用 ChatGPT。

How should people start to explore AI for sake of getting smarter, learning knowledge just for the sake of knowledge, having fun with it?

人们应该如何开始探索人工智能，以变得更聪明，为了知识而学习知识，并从中获得乐趣？

What's the best way to do that?

最好的方法是什么？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, I think exactly what you did, which is, there's now dozens and dozens of different chatbots out there, and different people will feel comfortable with one or the other.

嗯，我认为正是你所做的，那就是，现在有几十种不同的聊天机器人，不同的人会对其中一种感到舒服。

ChatGPT is the first, so that's why it's kind of taken over a lot of the cognitive space, right?

ChatGPT 是第一个，所以这就是为什么它占据了很多认知空间，对吗？

It's become like Kleenex, right?

它变得像面巾纸一样，对吧？

That word.

那句话。

That was why I used it as the first word in my new book, because it's iconic.

这就是为什么我用它作为我的新书中的第一个词，因为它具有标志性。

But some of them, I have to say that, for example, there are some that are really much better at math than others.

但他们中的一些人，我不得不说，比如，有一些人在数学方面确实比其他人好得多。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Such as?

例如？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Google's Gemini recently did some fine-tuning with what's called chain of reasoning.

谷歌的 Gemini 最近对所谓的推理链进行了一些微调。

When you reason, you go through a sequence of steps, and when you solve a math problem, you go through a sequence of steps of first finding out what's missing and then adding that.

当你推理时，你会经历一系列步骤，当你解决数学问题时，你会经历一系列步骤，首先找出缺少的内容，然后添加它。

And it went from 20% correct to 80%.

正确率从 20% 上升到 80%。

Right on those problems.

就这些问题。

Andrew Huberman:

安德鲁·休伯曼：

And as people hear that, they probably think, well, that means 20% wrong still.

当人们听到这个消息时，他们可能会想，好吧，这意味着仍然有 20% 的错误。

But could you imagine any human or panel of humans behind a wall where if you asked it a question and then another question and another question, that it would give you back better than 80% accurate information in a matter of seconds?

但你能想象墙后的任何一个人或一群人，如果你问它一个问题，然后再问一个问题，它会在几秒钟内给你返回超过 80% 准确的信息吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So I think we are being perhaps a little bit unfair to compare these large language models to the best humans rather than the average human.

因此，我认为我们将这些大型语言模型与最优秀的人类而不是普通人进行比较可能有点不公平。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right?

对吗？

As you said, most people couldn't pass the LSAT, the law test to get into law school, or MCAT, the test to get into medical school, and ChatGPT has.

正如你所说，大多数人无法通过 LSAT（进入法学院的法律考试）或 MCAT（进入医学院的考试），而 ChatGPT 做到了。

Andrew Huberman:

安德鲁·休伯曼：

Is there a world now where we take the existing AI, LLMs, these computers basically that can learn like a collection of human brains and send that somehow into the future, right?

现在是否有一个世界，我们利用现有的人工智能、法学硕士，这些计算机基本上可以像人类大脑的集合一样学习，并以某种方式将其发送到未来，对吗？

Give them an imagined future.

给他们一个想象中的未来。

Okay.

好的。

Could we give them outcome A and outcome B and let them forage into future states that we are not yet able to get to, and then harness that knowledge and explore the two different outcomes?

我们能否给他们结果 A 和结果 B，让他们探索我们尚未达到的未来状态，然后利用这些知识并探索两种不同的结果？

I think that's perhaps the better question in some sense, because we can't travel back in time, but we can perhaps travel into the future with AI if you provide it different scenarios and you say, unlike a panel of people, panel of experts, medical experts or space travel experts or sea travel experts, you can't say, "Hey, you know what?

我认为这在某种意义上可能是更好的问题，因为我们无法回到过去，但如果你提供不同的场景，我们也许可以通过人工智能进入未来，并且你说，与一群人、专家小组、医学专家或太空旅行专家或海上旅行专家不同，你不能说，“嘿，你知道吗？

Don't sleep tonight.

今晚别睡了。

You're just going to work for the next 48 hours.

接下来的 48 小时你将继续工作。

In fact, you're going to work for the next three weeks or three months.

事实上，你将在接下来的三周或三个月内工作。

And you know what?

你知道吗？

You're not going to do anything else.

你不会做任何其他事情。

You're not going to pay attention to your health.

你不会关注你的健康。

You're not going to do anything else." But you can take a large language model and you can say, "Just forage for knowledge under the following different scenarios," and then have that fleet of large language models come back and give us the information like, I don't know, tomorrow.

你不会做任何其他事情。”但是你可以采用一个大型语言模型，你可以说，“只是在以下不同的场景下寻找知识”，然后让大型语言模型的舰队回来并给我们提供信息，比如，我不知道，明天。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay, so I've lived through this myself.

好吧，我自己就经历过这个。

Back in the 1980s, I was just starting my career, and I was one of the pioneers in developing learning algorithms for neural network models.

早在 20 世纪 80 年代，我刚刚开始我的职业生涯，我是开发神经网络模型学习算法的先驱之一。

Jeff Hinton and I collaborated together on something called the Boltzmann machine, and he actually won a Nobel Prize for this recently.

杰夫·辛顿（Jeff Hinton）和我合作开发了一种叫做玻尔兹曼机的东西，他最近因此获得了诺贝尔奖。

Andrew Huberman:

安德鲁·休伯曼：

Yeah, just this year.

是的，就在今年。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Wonderful.

太棒了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

He's one of my best friends.

他是我最好的朋友之一。

Brilliant, and he well deserved it for not just the Boltzmann machine, but all the work he's done since then on machine learning and then back propagation and so forth.

太棒了，他当之无愧，不仅因为玻尔兹曼机，还因为他从那时起在机器学习和反向传播等方面所做的所有工作。

But back then, Jeff and I had this view of the future.

但当时，杰夫和我对未来有这样的看法。

AI was dominated by symbol processing, rules, logic, right?

人工智能主要是符号处理、规则、逻辑，对吗？

Writing computer programs.

编写计算机程序。

For every problem, you need a different computer program, and it was very human resource intensive to write programs so that it was very slow going, and they never actually got there.

对于每个问题，你都需要不同的计算机程序，而编写程序需要大量人力资源，因此进展非常缓慢，而且他们从未真正实现这一目标。

They never wrote a program for vision, for example, even though the computer vision computer community really worked hard for a long time.

例如，他们从未编写过视觉程序，尽管计算机视觉计算机社区确实努力了很长时间。

But we had this view of the future.

但我们对未来有这样的看法。

We had this view that nature has solved these problems and it is existence proof that you can solve the vision problem.

我们认为大自然已经解决了这些问题，并且它是可以解决视力问题的存在证明。

Look, every animal can see, even insects, right?

你看，所有动物都能看见，甚至昆虫，对吧？

Come on.

快点。

Well, let's figure out how they did it.

好吧，让我们弄清楚他们是如何做到的。

Maybe we can help by following up on nature, we can actually, again, going back to algorithms, I was telling you.

也许我们可以通过追踪自然来提供帮助，我们实际上可以再次回到算法，我告诉过你。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And so in the case of the brain, what makes it different from a digital computer, digital computers basically can run any program, but a fly brain, for example, only runs the program that its special purpose hardware allows it to run.

因此，就大脑而言，它与数字计算机的不同之处在于，数字计算机基本上可以运行任何程序，但例如，苍蝇大脑只能运行其专用硬件允许其运行的程序。

Andrew Huberman:

安德鲁·休伯曼：

Not much neuroplasticity.

没有太多的神经可塑性。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

There's enough there, just enough in habituation and so forth, so that it can survive.

那里已经足够了，只要有足够的习惯等等，它就能生存下来。

And this is-

这是——

Andrew Huberman:

安德鲁·休伯曼：

Survive 24 hours.

存活24小时。

I'm not trying to be disparaging to the fly biologist.

我并不是想贬低果蝇生物学家。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, okay.

好吧，好吧。

No.

不。

Andrew Huberman:

安德鲁·休伯曼：

But when I think of neuroplasticity, I think of the magnificent neuroplasticity-

但当我想到神经可塑性时，我想到了伟大的神经可塑性——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I agree

我同意

Andrew Huberman:

安德鲁·休伯曼：

...

of the human brain to customize to a world of experience.

人类大脑定制一个体验世界。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I agree, but-

我同意，但是-

Andrew Huberman:

安德鲁·休伯曼：

When I think about a fly, I think about a really cool set of neural circuits that work really well to avoid getting swatted, to eating, and to reproducing, and not a whole lot else.

当我想到一只苍蝇时，我想到的是一组非常酷的神经回路，它们在避免被拍打、进食和繁殖方面表现得非常好，而不是其他很多。

They don't really build technology.

他们并不真正构建技术。

They might have interesting relationships, but-

他们可能有有趣的关系，但是——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

who knows?

谁知道？

Who cares?

谁在乎？

It's not that it doesn't matter, it's just a question of the lack of plasticity makes them kind of a meh species.

这并不是说这不重要，只是缺乏可塑性的问题使它们成为一种无聊的物种。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

I can see I've pressed your button here.

我可以看到我已经按下了你的按钮。

Andrew Huberman:

安德鲁·休伯曼：

No, I love fly biology.

不，我喜欢苍蝇生物学。

They taught us about algorithms for direction selectivity in the visual system.

他们教给我们视觉系统中方向选择性的算法。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Oh, okay.

哦好的。

Andrew Huberman:

安德鲁·休伯曼：

Oh, no. I love the Drosophila biology.

哦，不。我喜欢果蝇生物学。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's gone well.

一切顺利。

Andrew Huberman:

安德鲁·休伯曼：

I just think that the lack of neuroplasticity-

我只是认为缺乏神经可塑性-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay

好的

Andrew Huberman:

安德鲁·休伯曼：

...

it reveals a certain key limitation, and the reason we're the curators of the Earth is because we have so much plasticity.

它揭示了某个关键的局限性，而我们之所以成为地球的管理者，是因为我们有如此多的可塑性。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Of course.

当然。

But you have to take it one step at a time.

但你必须一步一步地采取。

Nature first has to be able to create creatures that can survive, and then their brains get bigger as the environment gets more complex and here we are.

大自然首先必须能够创造出能够生存的生物，然后随着环境变得更加复杂，它们的大脑也会变得更大，而我们就在这里。

But the key is that it turns out that certain algorithms in the fly brain are present in our brain.

但关键是事实证明，果蝇大脑中的某些算法也存在于我们的大脑中。

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Like conditioning.

就像调理一样。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Classical conditioning.

经典调理。

You can classical condition a fly in terms of training it to when you give it a reward, it will produce the same action, right?

你可以用经典的条件来训练一只苍蝇，当你给予它奖励时，它会产生相同的动作，对吧？

This is like conditioned behavior.

这就像条件行为。

And that algorithm that I told you about that is in your value function, right, temporal difference learning, that algorithm is in the fly brain, it's in your brain.

我告诉你的那个算法是在你的价值函数中，对，时间差异学习，这个算法在苍蝇的大脑中，它在你的大脑中。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So we can learn about learning from-

所以我们可以从中学习——

Andrew Huberman:

安德鲁·休伯曼：

Sure

当然可以

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

many species.

许多物种。

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

I was just having a little fun poking at the fly biologist.

我只是想用戳苍蝇生物学家的方式来获得一点乐趣。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No.

不。

Andrew Huberman:

安德鲁·休伯曼：

I actually think Drosophila has done a great deal, as has honeybee biology.

事实上，我认为果蝇做了很多工作，蜜蜂生物学也是如此。

For instance, if you give caffeine to bees on particular flowers, they'll actually try and pollinate those flowers more-

例如，如果你在特定的花朵上给蜜蜂咖啡因，它们实际上会尝试更多地为这些花朵授粉-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, yeah

哦，是的

Andrew Huberman:

安德鲁·休伯曼：

...

because they actually like the feeling of being caffeinated.

因为他们实际上喜欢喝咖啡的感觉。

There's a bad pun about a buzz here, but I'm not going to make that pun because everyone's done it before.

这里有一个关于嗡嗡声的双关语，但我不会使用这个双关语，因为每个人都曾经这样做过。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

No, I fully absorb and agree with the value of studying simpler organisms to find the algorithms.

不，我完全理解并同意研究更简单的生物体以找到算法的价值。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

That's where we are right now.

这就是我们现在所处的情况。

But now to just go into the future now.

但现在就进入未来吧。

I'm telling the story about where we were.

我正在讲述我们在哪里的故事。

We were predicting the future.

我们正在预测未来。

We were saying this is an alternative to traditional AI.

我们说这是传统人工智能的替代方案。

We were not taken seriously.

我们没有被认真对待。

The experts said, "No, no. Write programs." They were getting all the resources, the grants, the jobs, and we were just like the little furry mammals under the feet of these dinosaurs, right?

专家们说：“不，不，写程序。”他们获得了所有的资源、补助金、工作机会，而我们就像这些恐龙脚下的毛茸茸的小哺乳动物，对吧？

In retrospect.

回想起来。

Andrew Huberman:

安德鲁·休伯曼：

I love the analogy.

我喜欢这个比喻。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But here's the point.

但这就是重点。

Andrew Huberman:

安德鲁·休伯曼：

But the dinosaurs died off.

但恐龙灭绝了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But the point I'm making is that it's possible for our brain to make these extrapolations into the future.

但我想说的是，我们的大脑有可能对未来做出这些推断。

Why not AI versions of brains?

为什么不是人工智能版本的大脑呢？

Why not?

为什么不呢？

I think your idea is a great one.

我认为你的想法很棒。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

The reason I'm excited about AI, and increasingly so across the course of this conversation, is because there are very few opportunities to forage information at such large scale and around the circadian clock.

我对人工智能感到兴奋的原因是，在这次谈话的过程中，我越来越兴奋，因为很少有机会在如此大规模和昼夜节律的情况下收集信息。

If there's one thing that we are truly a slave to as humans, it's the circadian biology.

如果有一样东西是我们作为人类真正的奴隶的话，那就是昼夜节律生物学。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

You got to sleep sooner or later, and even if you don't, your cognition really waxes and wanes across the circadian cycle.

你迟早要睡觉，即使你不睡觉，你的认知能力也会随着昼夜节律周期而变化。

And if you don't, you're going to die early.

如果你不这样做，你就会早死。

We know this.

我们知道这一点。

Computers can work, work, work.

计算机可以工作、工作、工作。

Sure, you got to power them.

当然，你必须给它们供电。

There's the cooling thing.

那里有冷却的东西。

There are a bunch of things related to that, but that's tractable.

有很多与此相关的事情，但这是很容易处理的。

So computers can work, work, work.

所以计算机可以工作、工作、工作。

And the idea that they can provide a portal into the future, and that they can just bring it back so we can take a look-see.

他们的想法是，他们可以提供通向未来的门户，并且他们可以将其带回来，以便我们可以看看。

I'm not saying we have to implement their advice, but to be able to send a panel of diverse, computationally diverse, experientially diverse AI experts into the future and bring us back a panel of potential routes to take, to me is so exciting.

我并不是说我们必须实施他们的建议，而是能够向未来派出一组由多样化、计算多样化、经验多样化的人工智能专家组成的小组，并为我们带回一组潜在的路线，对我来说是如此令人兴奋。

Maybe a good example would be treatments for schizophrenia.

也许一个很好的例子是精神分裂症的治疗。

This is an area that I want to make certain that we talk about.

这是我想确保我们讨论的一个领域。

I grew up learning as a neuroscience student that schizophrenia was somehow a disruption of the dopamine system because if you give neuroleptic drugs that block dopamine receptors, that you get some improvement in the motor symptoms and some of the hallucinations, et cetera.

作为一名神经科学专业的学生，我从小就知道精神分裂症在某种程度上是多巴胺系统的破坏，因为如果你服用阻断多巴胺受体的抗精神病药物，你的运动症状和一些幻觉等都会得到一些改善。

You now also have people who say, "No, that's not really the basis of schizophrenia.

现在也有人说：“不，这并不是精神分裂症的真正基础。

I'd love your thoughts." And you have incredible work from people like Chris Palmer at Harvard, and we even have people at Stanford now focusing on what Chris really founded as a field, which is metabolic psychiatry.

我很想听听你的想法。”哈佛大学的克里斯·帕尔默（Chris Palmer）等人做出了令人难以置信的工作，甚至斯坦福大学的人现在也专注于克里斯真正创立的一个领域，即代谢精神病学。

The idea that, who could imagine, I'm being sarcastic here, what you eat impacts your mitochondria, how you exercise impacts your mitochondria, mitochondria impacts brain function, and lo and behold, metabolic health of the brain and body impacts schizophrenia symptoms.

谁能想象，我在这里是在讽刺，你吃的东西会影响你的线粒体，你的锻炼方式会影响你的线粒体，线粒体会影响大脑功能，你瞧，大脑和身体的代谢健康会影响精神分裂症的症状。

And he's looked at ways that people can use ketogenic diet, maybe not to cure, but to treat, and in some cases, maybe even cure schizophrenia.

他研究了人们可以使用生酮饮食的方法，也许不是为了治愈，而是为了治疗，在某些情况下，甚至可能治愈精神分裂症。

So here we are at this place where we still don't have a, quote-unquote, "cure for schizophrenia," but you could send LLMs into the future and start to forage all of the data in those fields, probably could do that in an hour.

因此，我们现在仍然没有“治疗精神分裂症”的方法，但你可以将法学硕士送到未来，并开始寻找这些领域的所有数据，可能在一小时内就能做到。

Plus, come up with a bunch of hypothesized different positive and negative result clinical trials that don't even exist yet.

另外，提出一堆假设的不同阳性和阴性结果的临床试验，这些临床试验甚至还不存在。

10,000 subjects in Scandinavia who go on ketogenic diet, who have a certain level of susceptibility to schizophrenia based on what we know from twin studies, things that never ever, ever would be possible to do in an afternoon, maybe even in a year.

斯堪的纳维亚半岛有 10,000 名接受生酮饮食的受试者，根据我们从双胞胎研究中了解到的情况，他们对精神分裂症有一定程度的易感性，这是永远不可能在一个下午甚至一年内完成的事情。

There isn't funding.

没有资金。

And boom, get the answers back and let them present us those answers.

然后，把答案拿回来，让他们向我们展示这些答案。

And then you say, "Well, it's artificial." But so are human brains coming up with these experiments.

然后你说：“嗯，这是人为的。”但人类大脑也在进行这些实验。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So to me, I'm starting to realize that it's not that we have to implement everything that AI tells us or offers us.

所以对我来说，我开始意识到，我们并不是必须实现人工智能告诉我们或为我们提供的一切。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It just gives us-

它只是给我们——

Andrew Huberman:

安德鲁·休伯曼：

But it sure as hell gives us a great window into-

但它确实为我们提供了一个很好的窗口——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

what might be happening or is likely to happen.

可能发生或可能发生的事情。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Specifically for schizophrenia, I'm pretty sure that if we had these large language models 20 years ago, we would've known back then that ketamine would've been a really good drug to try to help these people.

特别是对于精神分裂症，我非常确定，如果我们在 20 年前拥有这些大型语言模型，我们当时就会知道氯胺酮将是一种非常好的药物来帮助这些人。

Andrew Huberman:

安德鲁·休伯曼：

Tell us about the relationship between ketamine and schizophrenia.

告诉我们氯胺酮和精神分裂症之间的关系。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Because I think a lot of people, and maybe you could define schizophrenia, even though most people think about people hearing voices and psychosis, there's a bit more to it that maybe we just bring out the contour.

因为我认为很多人，也许你可以定义精神分裂症，尽管大多数人认为人们听到声音和精神病，但还有更多的内容，也许我们只是勾勒出轮廓。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

So one of the things now that we know, see, the problem is that if you look at the endpoint, that doesn't tell you what started the problem.

所以现在我们知道的一件事是，问题是，如果你查看端点，它不会告诉你是什么引发了问题。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It started early in development.

它在开发初期就开始了。

Schizophrenia is something that appears late adolescence, early adulthood, but it actually is already a genetic problem from the get-go.

精神分裂症是在青春期晚期、成年早期出现的疾病，但实际上它从一开始就已经是一个遗传问题。

Andrew Huberman:

安德鲁·休伯曼：

So what is the concordance in identical twins?

那么同卵双胞胎的一致性是什么呢？

Meaning if you have identical twins in the womb-

意思是如果你子宫里有同卵双胞胎-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

and one is destined to be-

而一个人注定会成为——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

full-blown schizophrenic-

彻底的精神分裂症——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay

好的

Andrew Huberman:

安德鲁·休伯曼：

...

what's the probability the other will be?

另一个的概率是多少？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So here's the experiment.

这是实验。

Okay, this has been replicated many, many times in mice, I should say.

好吧，我应该说，这已经在老鼠身上复制了很多很多次。

Or no. Okay, let me start with a human.

或者没有。好吧，让我从人类开始。

Okay.

好的。

So ketamine was for a long time, and it still is, a party drug, special K.

所以氯胺酮很长一段时间以来都是一种派对毒品，一种特殊的 K。

Andrew Huberman:

安德鲁·休伯曼：

I've never taken it, but this is what I hear.

我从未接受过，但这就是我所听到的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I haven't either.

我也没有。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I don't know.

我不知道。

Andrew Huberman:

安德鲁·休伯曼：

It's a dissociative anesthetic, right?

这是一种解离麻醉剂，对吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But I'll tell you what happens because I've talked to these people who have done this.

但我会告诉你发生了什么，因为我已经和那些做过这件事的人交谈过。

You take ketamine, sub-anesthetic.

你服用氯胺酮，亚麻醉剂。

By the way, it's an anesthetic.

顺便说一下，这是一种麻醉剂。

It's given to children.

它是给孩子们的。

It's a pretty good anesthetic, and it's also used in veterinary medicine.

这是一种很好的麻醉剂，也用于兽医学。

But in any case, you take young adults.

但无论如何，你都会带着年轻人。

Here's what they experience.

这是他们的经历。

They experience out-of-body experience.

他们体验到灵魂出窍的体验。

They have this wonderful feeling of energy, and it's a high, but it's a very unusual high.

他们有一种美妙的能量感，这是一种兴奋，但这是一种非常不寻常的兴奋。

Now if they just go and have one experience, but if they have two, like they party two days in a row, a lot of them come into the emergency room.

现在，如果他们只是去体验一次，但如果他们有两次，就像他们连续两天聚会一样，很多人都会进入急诊室。

And here's what the symptoms are.

这是症状。

Full-blown psychosis.

彻底的精神病。

Full-blown.

全面爆发。

We're talking about indistinguishable from a schizophrenic break.

我们所说的精神分裂与精神分裂症没有什么区别。

Andrew Huberman:

安德鲁·休伯曼：

So auditory hallucinations?

那么幻听？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Auditory hallucinations, paranoia.

幻听、偏执。

Very advanced.

非常先进。

You'd say that, "My God, this person here is really has become a schizophrenic." And this is really, like you say, the symptoms are the same.

你可能会说，“天哪，这个人真的成了精神分裂症患者了。”正如你所说，这确实是相同的症状。

However, if you isolate them for a couple of days, they'll come back.

但是，如果你将它们隔离几天，它们就会回来。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So it means that ketamine can induce a form of schizophrenia, psychosis temporarily.

所以这意味着氯胺酮可以暂时诱发一种精神分裂症、精神病。

Not permanently, fortunately.

幸运的是，不是永久的。

Okay, so what does it attack?

好吧，那么它会攻击什么呢？

Okay, and there's another literature on this.

好的，还有另一篇关于此的文献。

It turns out that it binds to a form of receptor, a glutamate receptor called NMDA receptors, which are very important, by the way, for learning and memory.

事实证明，它与一种受体结合，一种称为 NMDA 受体的谷氨酸受体，顺便说一下，它对于学习和记忆非常重要。

But we know the target, and we also know what the acute outcome is, that it reduces the strength of the inhibitory circuit, the interneurons that use inhibitory transmitters.

但我们知道目标，也知道急性结果是什么，它会降低抑制回路（使用抑制性递质的中间神经元）的强度。

The enzyme that creates the inhibitory transmitter is downregulated.

产生抑制性递质的酶被下调。

And what does that do?

那有什么作用呢？

It means that there's more excitation.

这意味着有更多的兴奋。

And what does that mean when there's more excitation?

当有更多的兴奋时，这意味着什么？

It means that there's more activity in the cortex, and there's actually much more vigor, and you start becoming crazy, right, if it's too much activity.

这意味着大脑皮层有更多的活动，实际上有更多的活力，如果活动太多，你就会开始变得疯狂，对吧。

So this is interesting.

所以这很有趣。

So this is telling us, I think, that we should be thinking about-- And now there's a whole field now in psychiatry that has to do with the glutamate hypothesis for where the actual imbalance first occurs.

因此，我认为，这告诉我们，我们应该思考——现在精神病学中有一个完整的领域与谷氨酸假说有关，即实际不平衡首先发生的地方。

It's an imbalance between the excitatory inhibitory systems that are in the cortex, keep you in balance.

这是皮质中兴奋性抑制系统之间的不平衡，使您保持平衡。

Andrew Huberman:

安德鲁·休伯曼：

And NMDA, N-methyl-D-aspartate receptors are glutamate receptors.

而NMDA、N-甲基-D-天冬氨酸受体都是谷氨酸受体。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes, they are glutamate.

是的，它们是谷氨酸。

Andrew Huberman:

安德鲁·休伯曼：

They're one class.

他们是一个班的

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's one class.

那是一堂课。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Okay, so now here is a hypothesis for why ketamine might be good for depression.

好吧，现在这是一个关于为什么氯胺酮可能对抑郁症有好处的假设。

People are taking it now who are depressed, right?

现在抑郁症患者都在服用它，对吗？

So here we have a drug that causes overexcitation, and here you have a person who's underexcited.

所以这里有一种药物会导致过度兴奋，而这里有一个人会兴奋不足。

Andrew Huberman:

安德鲁·休伯曼：

Mm.

嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Depression is associated with lower excitatory activity in some parts of the cortex.

抑郁症与大脑皮层某些部分的兴奋性活动降低有关。

Well, if you titrate it, you can come back into balance, right?

好吧，如果你滴定它，你就能恢复平衡，对吗？

So what you do is you fight depression with schizophrenia.

所以你要做的就是对抗抑郁症和精神分裂症。

A touch of schizophrenia.

有点精神分裂的感觉。

Now, you have to keep giving, I think, once every three weeks.

现在，我认为你必须继续每三周捐赠一次。

They have to have a new dose of ketamine.

他们必须服用新剂量的氯胺酮。

But it's helped an enormous number of people with very severe clinical depression.

但它帮助了大量患有非常严重的临床抑郁症的人。

So as we learn more about the mechanisms underlying some of these disorders, the better we are going to be at extrapolating and coming up with some solutions, at least, to prevent it from getting worse.

因此，当我们对其中一些疾病的机制了解得更多时，我们就能更好地推断并提出一些解决方案，至少可以防止情况变得更糟。

By the way, I'm pretty sure that the large language models could have figured this out long ago.

顺便说一句，我很确定大型语言模型很久以前就可以解决这个问题。

Andrew Huberman:

安德鲁·休伯曼：

So in an attempt to understand how we might be able to leverage these large language models now, how would we have used these large language models long ago?

因此，为了尝试了解我们现在如何利用这些大型语言模型，那么很久以前我们会如何使用这些大型语言模型呢？

Let's say you had 2024 AI technology in 19-- Let's have fun here.

假设你在 19 年就拥有了 2024 年的人工智能技术——让我们在这里玩得开心。

1998, the year that I started graduate school.

1998年，我开始读研究生的那一年。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

At that time, it was like the dopamine hypothesis of schizophrenia was in every textbook.

那时，就像精神分裂症的多巴胺假说出现在每本教科书中一样。

There was a little bit about glutamate, perhaps, but it was all about dopamine.

也许有一点与谷氨酸有关，但全都与多巴胺有关。

So how would the large language models have discovered this?

那么大型语言模型是如何发现这一点的呢？

Ketamine was known as a drug.

氯胺酮被认为是一种药物。

Ketamine, by the way, is very similar to PCP.

顺便说一句，氯胺酮与五氯苯酚非常相似。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Phencyclidine, which also binds the NMDA receptor.

苯环利定，也结合 NMDA 受体。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

So how would-

那么如何-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Which is also a party drug.

这也是一种派对毒品。

Andrew Huberman:

安德鲁·休伯曼：

Which is also, yeah.

这也是，是的。

Not one I recommend, nor ketamine.

我不推荐，也不是氯胺酮。

Frankly, I don't recommend any recreational drugs, but I'm not a recreational drug guy.

坦白说，我不推荐任何消遣性毒品，但我不是一个消遣性毒品迷。

But what would those large language models do if they-- So you've got 2024 technology placed into 1998.

但是那些大型语言模型会做什么，如果它们 - 所以你已经把 2024 年的技术放到了 1998 年。

They're foraging for existing knowledge, but then are they able to make predictions?

他们正在寻找现有的知识，但他们能够做出预测吗？

Like, "Hey, this stuff is going to turn out to be wrong," or, "Hey, this stuff is-"

就像，“嘿，这个东西会被证明是错误的”，或者，“嘿，这个东西是——”

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

This is all very speculative, and really, we can begin actually to see this happening now.

这一切都非常具有推测性，实际上，我们现在就可以开始真正看到这种情况的发生。

So I have a colleague at the Salk Institute, Rusty Gage.

我在索尔克研究所有一位同事，Rusty Gage。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Very distinguished neuroscientist, and he discovered that there are new neurons being born in the hippocampus, right?

非常杰出的神经科学家，他发现海马体中正在诞生新的神经元，对吧？

In adults, which is something that in a textbook says that doesn't happen, right?

对于成年人来说，这是教科书上说的不会发生的事情，对吗？

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

That was around 1998 that Rusty did that.

大约在 1998 年，Rusty 就这么做了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

That's right.

这是正确的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And I actually have a paper with him where we tested LTP, long-term potentiation, for actually the effects of exercise on neurogenesis.

事实上，我和他有一篇论文，我们测试了 LTP（长时程增强），以了解运动对神经发生的实际影响。

Andrew Huberman:

安德鲁·休伯曼：

Exercise increases neurogenesis.

运动可以增加神经发生。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

It increases the cells.

它增加了细胞。

Yeah, it increases neurogenesis and also the cells that are active become part of the circuit.

是的，它会增加神经发生，并且活跃的细胞也会成为回路的一部分。

More cells become integrated.

更多的细胞变得整合。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

And this is true in humans as well, right?

这对于人类来说也是如此，对吧？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

And there was some cancer drug that was given that they showed that there were new cells that they were able to later in postmortem to actually see that they were born in the adult.

他们使用了一些抗癌药物，结果表明，在死后尸检中，他们能够真正看到它们是在成人体内诞生的新细胞。

Okay.

好的。

So here we are, okay, in 1998, and the question is, can you jump into the future?

那么，我们现在已经是 1998 年了，问题是，你能跳到未来吗？

Okay.

好的。

So Rusty We happened to talk about this issue, about he's using these large language models now for his research.

Rusty 我们碰巧谈论了这个问题，关于他现在正在使用这些大型语言模型进行研究。

I said, "Oh, wow.

我说：“哦，哇。

How do you use it?" And he said, "We use it as an idea pump." "What do you mean idea pump?" "Well, we give it all of the experiments that we've done, and we have the literature, it's access to the literature and so forth, and we ask it for ideas for new experiments."

你怎么用它？”他说：“我们用它作为创意泵。” “你说的想法泵是什么意思？” “嗯，我们把我们做过的所有实验都交给它，我们有文献，它可以访问文献等等，我们向它询问新实验的想法。”

Andrew Huberman:

安德鲁·休伯曼：

Oh, I love it.

哦，我喜欢它。

I was on a plane where I sat next to a guy that works at Google, and he's one of the main people there in terms of voice-to-text, and text-to-voice software.

我在飞机上坐在一个在谷歌工作的人旁边，他是语音转文本和文本转语音软件方面的主要人物之一。

And he showed me something.

他给我看了一些东西。

I'll provide a link to it because it's another one of these open resource things.

我将提供一个链接，因为它是这些开放资源中的另一个。

And I'm not super techy.

而且我技术并不高。

I don't get an F in technology.

我在技术方面没有得F。

I don't get an A-plus.

我没有得到A+。

I'm kind of in the middle, so I think I'm pretty representative of the average listener for this podcast, presumably.

我处于中间位置，所以我想我很能代表这个播客的普通听众。

What he showed me is that you open up this website, and you can take PDFs or you take URLs, so website addresses, and you just place them in the margin.

他向我展示的是，你打开这个网站，你可以获取 PDF 或 URL，即网站地址，然后将它们放在页边空白处。

You literally just drag and drop them there.

您只需将它们拖放到那里即可。

And then you can ask questions, and the AI will generate answers that are based on the content of whatever you put into this margin, those PDFs, those websites.

然后你可以提出问题，人工智能将根据你在空白处输入的任何内容、那些 PDF、那些网站生成答案。

And the cool thing is it references them, so you know which article it came from.

最酷的是它引用了它们，所以你知道它来自哪一篇文章。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And then you can start asking it more sophisticated questions.

然后你可以开始问它更复杂的问题。

Like in the two examples of the effects of a drug, one being very strong and one being very weak, which of these papers do you think is more rigorous based on subject number, but also kind of the strength of the findings?

就像药物作用的两个例子一样，一个非常强，一个非常弱，根据主题数量，您认为哪一篇论文更严格，而且从研究结果的强度来看？

A pretty vague thing.

一个相当模糊的事情。

Strength of findings is pretty vague, right?

研究结果的强度相当模糊，对吗？

Anyone that argues, "Those are weak findings, those aren't enough subjects," well, we know a hell of a lot about human memory from one patient, HM.

任何认为“这些都是薄弱的发现，这些还不够充分”的人，好吧，我们从一位患者 HM 那里了解了很多关于人类记忆的知识。

So strength of findings when people-

因此，当人们——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah

是啊

Andrew Huberman:

安德鲁·休伯曼：

...

is a subjective thing.

是一个主观的事情。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

You really have to be an expert in a field to understand strength of findings, and even then.

你确实必须成为某个领域的专家才能了解研究结果的强度，即便如此。

And what's amazing is it starts giving back answers like, "Well, if you're concerned about number of subjects, this paper," but that's a pretty obvious one, which one had more subjects.

令人惊奇的是它开始给出这样的答案：“好吧，如果你关心主题的数量，这篇论文，”但这是一个非常明显的问题，哪一篇有更多的主题。

But it can start critiquing the statistics that they used in these papers-

但它可以开始批评他们在这些论文中使用的统计数据——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, wow

哦，哇

Andrew Huberman:

安德鲁·休伯曼：

...

in very sophisticated ways-

以非常复杂的方式——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Huh

呵呵

Andrew Huberman:

安德鲁·休伯曼：

...

and explain back to you why certain papers may not be interesting and others are more interesting, and it starts to weight the evidence.

并向你解释为什么某些论文可能不有趣而其他论文更有趣，并且它开始权衡证据。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh my gosh.

天哪。

Andrew Huberman:

安德鲁·休伯曼：

And then you say, "Well, with that weighted evidence, can you hypothesize what would happen if?" And so I've done a little bit of this where it starts trying to predict the future-

然后你说，“好吧，有了这些加权证据，你能假设如果会发生什么吗？”所以我做了一些这样的事情，开始尝试预测未来 -

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Wow

哇

Andrew Huberman:

安德鲁·休伯曼：

...

based on 10 papers that you gave it five minutes ago.

基于您五分钟前提交的 10 篇论文。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Amazing.

太棒了。

Andrew Huberman:

安德鲁·休伯曼：

I don't think any professor could do that, except in their very specific area of interest, and if they were already familiar with the papers, and it would take them many hours if not days to read all those papers in detail.

我认为任何教授都无法做到这一点，除非在他们非常具体的兴趣领域，并且如果他们已经熟悉这些论文，那么他们将花费数小时甚至数天的时间来详细阅读所有这些论文。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And they might not actually come up with the same answers, right?

他们实际上可能不会得出相同的答案，对吧？

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

So actually, this is something that is happening in medicine, by the way, for doctors who are using AI as an assistant.

事实上，顺便说一下，对于使用人工智能作为助手的医生来说，这就是医学领域正在发生的事情。

This is really interesting.

这真的很有趣。

And this is dermatology.

这是皮肤科。

It was a paper in "Nature," skin lesions.

这是《自然》杂志上的一篇关于皮肤损伤的论文。

There's 2,000 skin lesions.

有2000处皮肤损伤。

And some of them are cancerous, and others are benign.

其中一些是癌性的，另一些是良性的。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And so, in any case, they tested the expert doctors, and then they tested an AI, and they were both doing about 90%.

因此，无论如何，他们测试了专家医生，然后测试了人工智能，结果都达到了 90% 左右。

Right?

正确的？

However, if you let the doctor use the AI, it boosts the doctor to 98%.

然而，如果你让医生使用人工智能，它会将医生的效率提升到98%。

Andrew Huberman:

安德鲁·休伯曼：

98% accuracy.

98% 的准确率。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

And what's going on there?

那里发生了什么事？

It's very interesting.

这很有趣。

So it turns out that although they got the same 90%, they had different expertise, that the AI had access to more data, and so it could look at the lesions that were rare that the doctor may never have seen, okay?

所以事实证明，虽然他们得到了相同的 90%，但他们拥有不同的专业知识，人工智能可以访问更多数据，因此它可以查看医生可能从未见过的罕见病变，好吗？

But the doctor has more in-depth knowledge of the most common ones that he's seen over and over again, and knows the subtleties and so forth.

但医生对他一遍又一遍地看到的最常见的疾病有更深入的了解，并且知道其中的微妙之处等等。

But so putting them together, it makes so much sense that they're going to improve if they work together.

但把他们放在一起，就很有意义了，如果他们一起工作，他们就会进步。

And I think that now what you're saying is that using AI as a tool for discovery, with the expert who's interpreting and looking at the arguments, the statistical arguments, and also looking at the paper maybe in a new way, maybe that's the future of science.

我认为现在你所说的是，使用人工智能作为发现工具，由专家解释和研究论点、统计论点，并以一种新的方式看待论文，也许这就是科学的未来。

Maybe that's what's going to happen.

也许这就是即将发生的事情。

Everybody's worried about, "Oh, AI's going to replace us.

每个人都担心，“哦，人工智能将取代我们。

It's going to be much better than we are at everything, and humans are obsolete." Nothing could be further from the case.

它在所有方面都会比我们好得多，而人类已经过时了。”事实并非如此。

Our strengths and weaknesses are different, and by working together, it's going to strengthen both what we do and what AI does, and it's going to be a partnership.

我们的优势和劣势各不相同，通过共同努力，我们的工作和人工智能的工作都将得到加强，而且这将成为一种伙伴关系。

It's not going to be adversarial.

这不会是敌对的。

It's going to be a partnership.

这将是一种伙伴关系。

Andrew Huberman:

安德鲁·休伯曼：

Would you say that's the case for things like understanding or discovering treatments for neurologic illness, for avoiding large-scale catastrophes?

您认为理解或发现神经系统疾病的治疗方法、避免大规模灾难等事情也是如此吗？

Like can it predict macro movements?

比如它可以预测宏观走势吗？

Let me give an example.

让我举个例子。

Here in Los Angeles, there's occasionally an accident on the freeway.

在洛杉矶，高速公路上偶尔会发生事故。

You have a lot of cameras over freeways nowadays.

如今，高速公路上有很多摄像头。

You have cameras in cars.

你的车里有摄像头。

You can imagine all of the data being sent in in real time, and you could probably predict accidents pretty easily.

您可以想象所有数据都是实时发送的，并且您可以很容易地预测事故。

I mean, these are just moving objects, right, at a specific rate.

我的意思是，这些只是以特定速率移动的物体，对吧。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

Who's driving haphazardly.

谁开车乱了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

But you could also potentially signal takeover of the brakes or the steering wheel of a car and prevent accidents.

但您也可以发出信号接管汽车的刹车或方向盘，并防止事故发生。

I mean, certain cars already do that, but could you essentially eliminate Well, let's do something even more important.

我的意思是，某些汽车已经做到了这一点，但是你能基本上消除吗？好吧，让我们做一些更重要的事情。

Let's eliminate traffic.

让我们消除交通。

I don't know if you can do that, because that's a fun old problem.

我不知道你是否能做到这一点，因为这是一个有趣的老问题。

But could you predict physical events in the world into the future?

但是你能预测未来世界上发生的物理事件吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay, this has already been done, not for traffic, but for hurricanes.

好吧，这已经完成了，不是为了交通，而是为了飓风。

So as you know, the weather is extremely difficult to predict, except here in California, where it's always going to be sunny.

如您所知，天气极难预测，除了加利福尼亚州，那里总是晴朗。

But now what they've done is to feed a lot of previous data from previous hurricanes and also simulations of hurricanes.

但现在他们所做的是提供以前飓风的大量数据以及飓风模拟。

You can simulate them in a supercomputer.

您可以在超级计算机中模拟它们。

It takes days and weeks.

这需要几天甚至几周的时间。

So it's not very useful for actually accurately predicting where it's going to hit Florida.

因此，它对于实际准确预测飓风将袭击佛罗里达州的位置并不是很有用。

But what they did was, after training up the AI on all of this data, it was able to predict with much better accuracy exactly where in Florida it is going to make landfall.

但他们所做的是，在对所有这些数据进行人工智能训练后，它能够更准确地预测它将在佛罗里达州的哪个地方登陆。

And it does that on your laptop in 10 minutes.

10 分钟内即可在您的笔记本电脑上完成此操作。

Andrew Huberman:

安德鲁·休伯曼：

Incredible.

难以置信。

So something just clicked for me, and it's probably obvious to you and to most people, but I think this is true.

所以我突然想到了一些事情，这对你和大多数人来说可能是显而易见的，但我认为这是真的。

I think what I'm about to say is true.

我想我要说的是真的。

At the beginning of our conversation, we were talking about the acquisition of knowledge versus the implementation of knowledge.

在我们谈话的开始，我们讨论的是知识的获取与知识的实施。

Just learning facts versus learning how to implement those facts in the form of physical action or cognitive action, right?

仅仅学习事实与学习如何以身体行动或认知行动的形式实现这些事实，对吗？

Math problem is cognitive action, physical action.

数学问题是认知行动、身体行动。

Okay.

好的。

AI can do both knowledge acquisition, it can learn facts, long lists of facts, and combinations of facts, but presumably, it can also run a lot of problem sets and solve a lot of problem sets.

人工智能既可以获取知识，也可以学习事实、一长串事实以及事实组合，但据推测，它还可以运行大量问题集并解决大量问题集。

I don't think, except with some crude, still to me, examples of robotics, that it's very good at action yet, but it will probably get there at some point.

我不认为，除了一些对我来说仍然粗糙的机器人技术例子之外，它还没有非常擅长行动，但它可能会在某个时候实现这一点。

Robots are getting better, but they're not doing what we're doing yet.

机器人正在变得越来越好，但它们还没有做我们正在做的事情。

But it seems to me that as long as they can acquire knowledge and then solve different problem sets, different iterations of combinations of knowledge, that basically they are in a position to take any data about prior events or current events and make pretty darn good predictions about the future and run those back to us quickly enough-

但在我看来，只要他们能够获取知识，然后解决不同的问题集，知识组合的不同迭代，基本上他们就能够获取有关先前事件或当前事件的任何数据，并对未来做出非常好的预测，并足够快地将这些预测返回给我们——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Mm-hmm

嗯嗯

Andrew Huberman:

安德鲁·休伯曼：

...

and to themselves quickly enough that they could play out the different iterations.

并且足够快地让他们自己能够完成不同的迭代。

And so I'm thinking one of the problems that seems to have really vexed neuroscientists and the field of medicine and the general public has been the increase in the at least diagnosis of autism.

因此，我认为真正困扰神经科学家、医学领域和公众的问题之一是自闭症诊断率的增加。

I've heard so many different hypotheses over the years.

多年来我听到过很多不同的假设。

I think we're still pretty much in the fog on this one.

我认为我们在这一点上仍然一头雾水。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It is a tough problem.

这是一个棘手的问题。

Andrew Huberman:

安德鲁·休伯曼：

Could AI start to come up with new and potential solutions and treatments if they're necessary, but maybe get to the heart of this problem?

如果有必要的话，人工智能是否可以开始提出新的、潜在的解决方案和治疗方法，但也许能触及这个问题的核心？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It might, and it depends on the data you have.

可能会，这取决于您拥有的数据。

It depends on the complexity of the disease.

这取决于疾病的复杂性。

But it will happen.

但这将会发生。

In other words, we will use those tools the best we can, because obviously, if you can make any progress at all and jump into the future, wow, that would save lives.

换句话说，我们将尽最大努力使用这些工具，因为显然，如果你能取得任何进展并进入未来，哇，这将拯救生命。

That would help so many people out there.

这会帮助很多人。

I really think the promise here is so great-

我真的认为这里的承诺是如此伟大-

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm

嗯嗯

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

that even though there are flaws and there are regulatory problems, we really have to really push.

尽管存在缺陷和监管问题，但我们确实必须真正推动。

And we have to do that in a way that is going to help people in terms of making their jobs better and helping them solve problems that otherwise they would have had difficulty with and so forth.

我们必须以一种能够帮助人们改善工作并帮助他们解决否则他们会遇到困难的问题的方式来做到这一点。

And it's beginning to happen, but these are early days.

这一切已经开始发生，但现在还处于早期阶段。

So we're at a stage right now with AI that is similar to what happened after the first flight of the Wright brothers.

因此，我们现在所处的人工智能阶段与莱特兄弟首次飞行后发生的情况类似。

In other words-

换句话说——

Andrew Huberman:

安德鲁·休伯曼：

It's that significant

原来如此意义重大

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

the achievement that the Wright brothers made was to get off the ground 10 feet and to power forward with a human being 100 feet, right?

莱特兄弟取得的成就是离开地面10英尺并与人一起前进100英尺，对吗？

That was it.

就是这样。

That was the first flight.

那是第一次飞行。

And it took an enormous amount of improvements.

这需要大量的改进。

The most difficult thing that had to be solved was control.

最难解决的问题就是控制。

How do you control it?

你如何控制它？

How do you make it go in the direction you want it to go?

如何让它朝着你想要的方向发展？

And shades of what's happening now in AI is that we are off the ground, we're not going very far yet, but who knows where it will take us into the future.

人工智能现在正在发生的事情的阴影是我们还处于起步阶段，我们还没有走得太远，但谁知道它将把我们带向未来。

Andrew Huberman:

安德鲁·休伯曼：

Let's talk about Parkinson's disease, a depletion of dopamine neurons that leads to difficulty in smooth movement generation, and also some cognitive and mood-based dysfunction.

让我们来谈谈帕金森病，这是一种多巴胺神经元的耗竭，导致平滑运动产生困难，以及一些认知和情绪功能障碍。

Tell us about your work on Parkinson's and what did you learn?

告诉我们您在帕金森病方面的工作以及您学到了什么？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So as you point out, Parkinson's is, first, a degenerative disease.

正如您所指出的，帕金森病首先是一种退行性疾病。

It's very interesting because the dopamine cells are in a particular part of the brain, the brain stem, and they are the ones that are responsible for procedural learning.

这非常有趣，因为多巴胺细胞位于大脑的特定部分，即脑干，它们负责程序性学习。

I told you before about temporal difference.

我之前告诉过你时间差异。

It's dopamine cells.

这是多巴胺细胞。

And it's a very powerful way for the-- It's a global signal.

这是一个非常有力的方式——这是一个全球信号。

It's called a neuromodulator because it modulates all of the other signals taking place throughout the cortex.

它被称为神经调节器，因为它调节整个皮层发生的所有其他信号。

And also, it's very important for learning sequences of actions that produce survival, for survival.

而且，对于学习产生生存的一系列行动非常重要，为了生存。

But the problem is that with certain Environmental insults, especially toxins like pesticides, those neurons are very vulnerable, and when they die, you get all of the symptoms that you just described.

但问题是，在某些环境侵害下，尤其是杀虫剂等毒素，这些神经元非常脆弱，当它们死亡时，你就会出现刚才描述的所有症状。

The people who have lost those cells, actually before the treatment, L-DOPA, which is a dopamine precursor, they actually became comatose.

失去这些细胞的人实际上在接受左旋多巴（多巴胺前体）治疗之前，他们实际上陷入了昏迷。

They didn't move.

他们没有动。

They were still alive, but they just didn't move at all.

他们还活着，只是一动不动。

They-

他们——

Andrew Huberman:

安德鲁·休伯曼：

It's tragic.

真是悲剧。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Locked in, it's called.

被锁住了，这就是所谓的。

Yeah, it's tragic.

是的，很悲剧。

So when the first trials of L-DOPA were given to them, it was magical because suddenly they started talking again.

因此，当他们第一次试用左旋多巴时，这很神奇，因为他们突然又开始说话了。

So, this is amazing.

所以，这太棒了。

Andrew Huberman:

安德鲁·休伯曼：

I'm curious, when they started talking again, did they report that their brain state during the locked-in phase-

我很好奇，当他们再次开始说话时，他们有没有报告说他们在锁定阶段的大脑状态——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

was slow velocity?

速度慢吗？

Was it sort of like a dream-like state, or they felt like they were in a nap, or were they in there screaming to get out?

这是一种类似梦境的状态，还是他们感觉自己在小睡，或者他们在那里尖叫着要出去？

Because their physical velocity obviously was zero, they're locked in, after all.

因为他们的物理速度显然为零，所以他们毕竟被锁定了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And I've long wondered when coming back from a run or from waking up from a great night's sleep, when I shift into my waking state, whether or not physical velocity and cognitive velocity are linked.

我一直想知道，当我跑步回来或从一夜好眠中醒来时，当我进入清醒状态时，身体速度和认知速度是否相关。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

That's a wonderful observation or a question.

这是一个很棒的观察或问题。

I'll bet you know the answer.

我敢打赌你知道答案。

Okay.

好的。

Here's something that is really amazing.

这是真正令人惊奇的事情。

It was discovered interestingly when they tend to move slowly, as you said, but to them cognitively, they think they're moving fast.

有趣的是，正如你所说，当他们倾向于缓慢移动时，但对他们来说，他们认为自己移动得很快。

Now, it's not because they can't move fast, because you can say, "Well, can you move faster?" "Sure." And they move normal.

现在，这并不是因为他们不能快速移动，而是因为你可以说：“好吧，你能移动得更快吗？” “当然。”他们的动作也很正常。

But to them, they think they're moving at super velocity.

但对他们来说，他们认为自己正在以超快的速度移动。

Andrew Huberman:

安德鲁·休伯曼：

So it's a set point issue.

所以这是一个设定点问题。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So it's a set point issue, yes.

所以这是一个设定点问题，是的。

It's all about set points.

这都是关于设定点的。

That's what's really going on.

这就是真正发生的事情。

And as the set point gets further and further down, now without moving at all, they think they're moving, right?

随着设定值越来越低，现在根本没有移动，他们认为自己正在移动，对吗？

This is what's going on.

这就是正在发生的事情。

By the way, you can ask them, "What was it like?

顺便说一句，你可以问他们：“那是什么样的？

We were talking to you, and you didn't respond." "Oh, I didn't feel like it."

我们正在跟你说话，你却没有回应。” “哦，我没感觉。”

Andrew Huberman:

安德鲁·休伯曼：

The brain confabulates an answer.

大脑拼凑出一个答案。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, they confabulated it because they didn't have enough energy or they couldn't initiate actions.

好吧，他们胡编乱造是因为他们没有足够的精力或者无法采取行动。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's one of the things that they have trouble with, with movements, starting a movement.

这是他们在运动、发起运动时遇到的麻烦之一。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

As you can tell, I'm fascinated by this notion of cognitive velocity.

正如你所知，我对认知速度的概念很着迷。

And again, there may be a better or more accurate or official language for it, but I feel like it encompasses so much of what we try to do when we learn, and the fact that during sleep, you have these very vivid dreams during rapid eye movement sleep, so cognitive velocity is very fast, time perception is different-

再说一次，可能有更好或更准确的官方语言，但我觉得它包含了我们学习时尝试做的很多事情，而且事实上，在睡眠期间，你在快速眼动睡眠期间会做这些非常生动的梦，所以认知速度非常快，时间感知是不同的-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

than in slow-wave sleep dreams.

比慢波睡眠中的梦更重要。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And I really think there's something to it as at least one metric that relates to brain state.

我真的认为它至少有一个与大脑状态相关的指标。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

I've long thought that we know so much more about brain states during sleep than we do about wakeful brain states.

我一直认为我们对睡眠期间大脑状态的了解比对清醒时大脑状态的了解要多得多。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

We talk about focus, motivated, flow.

我们谈论专注、动力、心流。

These are not scientific terms.

这些不是科学术语。

I'm not being disparaging of them.

我并不是在贬低他们。

They're pretty much all we've got until we come up with something better.

在我们想出更好的东西之前，它们几乎是我们所拥有的一切。

But we're biologists and neuroscientists and computational neuroscientists, in your case, and we're trying to figure out what brain state are we in right now.

但就你而言，我们是生物学家、神经科学家和计算神经科学家，我们正在试图弄清楚我们现在处于什么大脑状态。

Our cognitive velocity is a certain value.

我们的认知速度是一个确定的值。

But I think the more that people think about this, I'll venture to say that the more that they think a little bit about their cognitive velocity at different times of day-

但我认为人们越多地思考这个问题，我敢说，他们越多地思考自己在一天中不同时间的认知速度——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

you start to notice that there tends to be a few times of day, for me, it tends to be early to late mid-morning, and then again in the evening after a little bit of trough in energy, that, boy, that hour and a half each, that's the time to get real work done.

你开始注意到，一天中往往有几个时间，对我来说，往往是上午早到晚，然后是在晚上，在能量低谷之后，每个时间都有一个半小时，这就是完成真正工作的时间。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I have the same experience.

我也有同样的经历。

Andrew Huberman:

安德鲁·休伯曼：

Because I can mentally sprint far at those times.

因为那时我的精神可以冲刺很远。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

But there are other times of day when-

但一天中还有其他时候——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Molasses

糖蜜

Andrew Huberman:

安德鲁·休伯曼：

...

I don't care how much caffeine I drink- ...

我不在乎我喝了多少咖啡因-...

I don't care, unless it's a stressful event that I need to-

我不在乎，除非这是一件有压力的事情，我需要——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

meet the demands of that stress, I can't get to that faster pace while I'm also engaging.

为了满足这种压力的要求，我无法在参与的同时达到更快的节奏。

You can read faster, you can listen, but you're not using the information, you're not storing the information.

你可以读得更快，你可以听，但你没有使用这些信息，你没有存储这些信息。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Andrew Huberman:

安德鲁·休伯曼：

What times of day for you are-

您一天中的什么时间是-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, I get most done in the morning, and then you're right, later after dinner-

不，我在早上完成大部分工作，然后你是对的，晚饭后-

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm

嗯嗯

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

is different, though.

但情况有所不同。

I think in the morning, I'm better at creative stuff, and then I think that in the evening, I'm better at actually just cranking it out.

我认为在早上，我更擅长创造性的东西，然后我认为在晚上，我更擅长实际地把它搞出来。

Andrew Huberman:

安德鲁·休伯曼：

Interesting.

有趣。

Given the relationship between body temperature and circadian rhythm-

鉴于体温和昼夜节律之间的关系 -

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

I would like to run an experiment that relates core body temperature to cognitive velocity.

我想做一个将核心体温与认知速度联系起来的实验。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I've actually noticed, this is something that is just purely subjective, but the temperature at the Salk inside the building is kept 35.

我实际上注意到，这纯粹是主观的，但建筑物内索尔克的温度保持在 35。

It's rock solid.

它坚如磐石。

But in the afternoon, I feel a little chilly.

但到了下午，我感觉有点冷。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's probably my internal-

这可能是我的内心——

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Sure

当然可以

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

temperature.

温度。

Andrew Huberman:

安德鲁·休伯曼：

Yeah, body temperature starts to come down.

是的，体温开始下降。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Body temperature, yeah, is probably going down, and that may correspond to the loss of energy, the amount of the ability for the brain and everything else.

是的，体温可能会下降，这可能与能量、大脑和其他一切能力的损失相对应。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

By the way, this is Q10.

顺便说一下，这是Q10。

This is jargon.

这是行话。

Every single enzyme in your every cell can go at different rates, depending on the temperature, right?

每个细胞中的每种酶都可以以不同的速率运行，具体取决于温度，对吗？

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And so, yeah, so the body temperature is doing this, and all the cells are doing this, too.

所以，是的，体温在这样做，所有的细胞也在这样做。

So it's an explanation.

所以这是一个解释。

I'm not sure if it's the right one, but...

我不确定这是否正确，但是...

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Craig Heller, my colleague at Stanford in the biology department, has beautifully described how the enzymatic control over pyruvate, I believe it is, controls muscular failure.

我在斯坦福大学生物系的同事克雷格·海勒（Craig Heller）精彩地描述了酶对丙酮酸的控制，我相信它是如何控制肌肉衰竭的。

That local muscular failure, when people are trying to move some resistance, has everything to do with the local temperature- That shuts down certain enzymatic processes that don't allow the muscles to contract the same way.

当人们试图移动一些阻力时，局部肌肉衰竭与局部温度密切相关——局部温度会关闭某些不允许肌肉以同样方式收缩的酶促过程。

He knows the details, and he covered them on this podcast.

他知道细节，并在这个播客上报道了它们。

I'm forgetting the details.

我忘记了细节。

You start to go, wow, these enzymes are so beautifully controlled by temperature.

你开始感叹，哇，这些酶能很好地受温度控制。

And of course, his laboratory is focused on ways to bypass those temperature or to change temperature locally in order to bypass those limitations and have shown them again and again.

当然，他的实验室专注于绕过这些温度或局部改变温度的方法，以绕过这些限制，并一次又一次地展示它们。

It's just incredible.

这真是令人难以置信。

Yeah, here we're speculating about what it would mean for cognitive velocity, but I think it's such a different world to think about the underlying biology as opposed to just thinking about a drug.

是的，我们在这里猜测这对认知速度意味着什么，但我认为考虑潜在的生物学而不是仅仅考虑药物是一个不同的世界。

You increase dopamine and norepinephrine and epinephrine, the so-called catecholamines, and you're going to increase energy, focus, and alertness.

你会增加多巴胺、去甲肾上腺素和肾上腺素，即所谓的儿茶酚胺，你会增加能量、注意力和警觉性。

But you're going to pay the price.

但你将付出代价。

You're going to have a trough in energy, focus, and alertness that's proportional to how much greater it was when you took the drug.

你的精力、注意力和警觉性将会出现一个低谷，这与你服药时的谷值水平成正比。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Boy, amphetamines are a good example.

男孩，安非他明就是一个很好的例子。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Boy, you're going a mile a minute when you're taking the drug.

孩子，当你服用药物时，你会每分钟跑一英里。

Of course, from where I stand, that's your impression.

当然，从我的立场来看，这是你的印象。

And the reality is you don't actually accomplish that much more.

而现实是你实际上并没有完成更多的事情。

Andrew Huberman:

安德鲁·休伯曼：

Have any LLMs, so AI, been used to answer this really pressing question of what is going to be the consequence on cognition for these young brains that have been weaned while taking Ritalin-

有没有法学硕士，比如人工智能，被用来回答这个真正紧迫的问题，即这些在服用利他林时断奶的年轻大脑的认知会产生什么后果？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

哦

Andrew Huberman:

安德鲁·休伯曼：

...

Adderall, Vyvanse, and other stimulants?

Adderall、Vyvanse 和其他兴奋剂？

Because we have millions of kids that have been raised this way.

因为我们有数以百万计的孩子就是这样长大的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

We've done this experiment on our whole cadre, a whole generation, and I really would like to know the answer.

我们对我们整个干部、整整一代人做过这个实验，我很想知道答案。

I wonder if anybody's studying that.

我想知道有没有人在研究这个

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's really a great question, because we gave them speed, effectively.

这确实是一个很好的问题，因为我们有效地为他们提供了速度。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

The drug that causes the brain to be activated.

使大脑被激活的药物。

But by the way, the consequence is that when it wears off, you have no energy.

但顺便说一句，后果是当它消失时，你就没有能量了。

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right?

对吗？

You're just completely spent.

你已经彻底精疲力竭了。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's it.

就是这样。

Andrew Huberman:

安德鲁·休伯曼：

That's the pit.

这就是坑啊

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's the pit.

这就是坑啊

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But that's why you take more of it, you see?

但这就是为什么你需要更多，你明白吗？

That's the problem is it's a spiral.

问题是它是一个螺旋。

Andrew Huberman:

安德鲁·休伯曼：

I love how today you're making it so very clear how computation, how math and computers and AI now are really shaping the way that we think about these biological problems, which are also psychological problems, which are also daily challenges.

我喜欢你今天非常清楚地阐述了计算、数学、计算机和人工智能如何真正塑造我们思考这些生物问题的方式，这些问题也是心理问题，也是日常挑战。

I also love that we touched on mitochondria and how to replenish mitochondria.

我也喜欢我们触及线粒体以及如何补充线粒体。

I want to make sure that we talk about a couple of things that I know are in the back of people's minds, no pun intended here, which are consciousness and free will.

我想确保我们谈论一些我知道人们内心深处的事情，这里没有双关语，那就是意识和自由意志。

Normally, I don't like to talk about these things, not because they're sensitive, but because I find the discussions around them typically to be more philosophical than neurobiological, and they tend to be pretty circular.

通常，我不喜欢谈论这些事情，不是因为它们很敏感，而是因为我发现围绕它们的讨论通常更具哲学性，而不是神经生物学，而且它们往往相当循环。

And so you get people like Kevin Mitchell, I think he has a book about free will.

所以你会遇到像凯文·米切尔这样的人，我认为他有一本关于自由意志的书。

He believes in free will.

他相信自由意志。

You've got people like Robert Sapolsky who wrote the book "Determined." He doesn't believe in free will.

像罗伯特·萨波尔斯基这样的人写了《决心》一书。他不相信自由意志。

How do you feel about free will, and is it even a discussion that we should be having?

您对自由意志有何看法？我们是否应该对此进行讨论？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, if you go back 500 years to the Middle Ages, the concept didn't exist, or at least not in the way we use it.

好吧，如果你回到 500 年前的中世纪，这个概念并不存在，或者至少在我们使用它的方式上不存在。

Because it was the way that humans felt about the world and how it worked and its impact on them was that it's all fate.

因为这是人类对世界的感受、世界的运作方式以及它对他们的影响，这都是命运。

They had this concept of fate, which is that there's nothing you can do, that something is going to happen to you because of what's going on and the gods up above or whatever it is, right?

他们有这样的命运概念，那就是你无能为力，因为正在发生的事情和天上的神或者其他什么，你会发生一些事情，对吗？

You attribute it to the physical forces around you that caused it, not to your own free will, not that there's something that you did that caused this to happen to you, right?

你把它归因于你周围的物理力量导致了它，而不是你自己的自由意志，而不是你做了什么导致了这件事发生在你身上，对吗？

So I think that these words, by the way, that we use, free will, consciousness, intelligence, understanding, they're weasel words because you can't pin them down.

所以我认为，顺便说一句，我们使用的这些词，自由意志、意识、智力、理解，它们都是狡猾的词，因为你无法确定它们。

There is no definition of consciousness that everybody agrees on.

对于意识，没有一个大家都同意的定义。

And it's tough to solve a problem, a scientific problem, if you don't have a definition that you can agree on.

如果你没有一个可以达成共识的定义，那么解决一个问题，一个科学问题就很困难。

And there's this big controversy about whether these large language models understand language or not, right?

关于这些大型语言模型是否理解语言存在很大争议，对吗？

The way we do.

我们就是这么做的。

And what it really is revealing is we don't understand what understanding is.

它真正揭示的是我们不明白什么是理解。

Literally, we don't have a really good argument or a measure that you can measure someone's understanding and then apply it to ChatGPT and see whether it's the same.

从字面上看，我们没有一个真正好的论据或衡量标准来衡量某人的理解，然后将其应用到 ChatGPT 上，看看是否相同。

It probably isn't exactly the same, but maybe there's some continuum here we're talking about.

它可能不完全相同，但也许我们正在谈论一些连续体。

The way I look at it, it's as if an alien suddenly landed on Earth and started talking to us in English, right?

在我看来，就好像一个外星人突然降落在地球上并开始用英语与我们交谈，对吗？

And the only thing we could be sure of it was that it's not human.

我们唯一能确定的是它不是人类。

Andrew Huberman:

安德鲁·休伯曼：

I met some people that I wondered about their terrestrial origins.

我遇到了一些人，我想知道他们的地球起源。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Well, okay, now there's a big diversity amongst humans, too.

好吧，现在人类之间也存在很大的多样性。

You're right about that.

你是对的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Certain colleagues of ours at UCSD years ago, one in particular in the physics department who I absolutely adore as a human being, just had such an unusual pattern of speech, of behavior, totally appropriate behavior, but just unusual.

几年前，我们在加州大学圣地亚哥分校的某些同事，特别是物理系的一位同事，我作为一个人非常崇拜他，他们的言语、行为模式非常不寻常，完全合适，但就是不寻常。

In the middle of a faculty meeting, would just kind of turn to me and start talking while the other person was presenting.

在教员会议中间，当另一个人在演讲时，他会转向我并开始讲话。

And I was like, "Maybe not now." And he would say, "Oh, okay But in any other domain, you'd say he was very socially adept.

我当时想，“也许不是现在。”他会说，“哦，好吧，但在任何其他领域，你都会说他非常善于社交。

And so there's certain people that just kind of discard with convention, and you kind of wonder, is he an alien?

所以有些人就是抛弃了传统，你会想，他是外星人吗？

It's kind of cool, in a cool way.

这有点酷，以一种酷的方式。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

He's one of my, again, a friend and somebody I really delight in.

他又是我的朋友之一，也是我真正喜欢的人。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, no, it's true.

是的，不，这是真的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Not everybody has adopted the same social conventions.

并非每个人都采用相同的社会习俗。

It could be a touch of autism.

这可能是一种自闭症。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's a problem that-

这是一个问题——

Andrew Huberman:

安德鲁·休伯曼：

Could be.

可能是。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

In other words, there are very high-functioning autistic people out there.

换句话说，那里有非常高功能的自闭症患者。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

He's brilliant, this guy.

他很聪明，这个家伙。

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And often they are.

事实往往如此。

There are people who are brilliant with autism.

有些人患有自闭症，却很聪明。

But

但是

Andrew Huberman:

安德鲁·休伯曼：

Could you build an LLM that was more on one end of the spectrum versus the other to see what kind of information they forage for?

你能否建立一个更偏向于另一端的法学硕士，看看他们寻找什么样的信息？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Actually, I reviewed a paper.

事实上，我审阅了一篇论文。

Andrew Huberman:

安德鲁·休伯曼：

It seems like it would be a really important thing to do.

看来这将是一件非常重要的事情。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's been done.

已经完成了。

Okay, there was a paper that I reviewed where they took the LLM, and they fine-tuned it with different data from people with different disorders, the autism and so forth.

好的，我审阅了一篇论文，他们在哪里取得了法学硕士学位，他们根据患有不同疾病、自闭症等的人的不同数据对其进行了微调。

And sociopaths.

还有反社会者。

Andrew Huberman:

安德鲁·休伯曼：

That's scary.

太可怕了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And-

还有——

Andrew Huberman:

安德鲁·休伯曼：

But you'd want to know the answer.

但你想知道答案。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, no.

不，不。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And they got these LLMs to behave just like those people who have these disorders.

他们让这些法学硕士的行为就像那些患有这些疾病的人一样。

You can get them to behave that way, yes.

是的，你可以让他们这样做。

Andrew Huberman:

安德鲁·休伯曼：

Could you do political leaning and values?

你能做政治倾向和价值观吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I haven't seen that, but it's pretty clear that, to me at least, that if you can do sociopathy, you can probably do any political belief.

我还没有看到这一点，但很明显，至少对我来说，如果你能做到反社会，你就可能能做到任何政治信仰。

Andrew Huberman:

安德鲁·休伯曼：

But you could also view all this as, you could take benevolent tracks.

但你也可以将这一切视为，你可以采取仁慈的轨迹。

You could also say hyper-creative, sensitive to emotional tone of voices, and find out what kind of information that person brings, excuse me, that LLM-

你也可以说超级有创造力，对声音的情绪语气敏感，并找出那个人带来了什么样的信息，对不起，LLM-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay

好的

Andrew Huberman:

安德鲁·休伯曼：

...

brings back versus somebody who is very-

带回来对抗一个非常-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

oriented towards just the content of people's words as opposed to what-- Because among people, you find this.

只针对人们言语的内容，而不是“什么”——因为在人们中间，你会发现这一点。

If you've ever left a party with a significant other and sometimes someone will say, I've had this experience with like, "Did you see that interaction between so-and-so?" I'm like, "No, what are you talking about?" Like, "Did you hear that?" I'm like, "No, not at all.

如果你曾经和一个重要的人一起离开过聚会，有时有人会说，我有过这样的经历，“你看到某某之间的互动了吗？”我说：“不，你在说什么？”比如，“你听到了吗？”我想，“不，一点也不。

I heard the words, but I did not pick up on what you were picking up on."

我听到了这些话，但我没有听懂你在听什么。”

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

And it was clear that there was two very different experiences of the same content-

而且很明显，同样的内容有两种截然不同的体验——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right

右

Andrew Huberman:

安德鲁·休伯曼：

...

based purely on a difference in interpretation of the tonality.

纯粹基于音调解释的差异。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

There's a lot of information that, as you point out, which has to do with the tone, the spatial expressions.

正如你所指出的，有很多信息与语气、空间表达有关。

There's a tremendous amount of information that is passed, not just with words, but with all the other parts, the visual input and so forth.

有大量的信息在传递，不仅仅是通过文字，还通过所有其他部分、视觉输入等等。

And some people are good at picking that up, and others are not.

有些人擅长识别这一点，而另一些人则不然。

There's a tremendous variability between individuals.

个体之间存在着巨大的差异。

And that's biology is all about diversity.

这就是生物学的多样性。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And it's all about needing gene pool that's very diverse so that you can evolve and survive catastrophic changes that occur in a climate, for example.

例如，这一切都需要非常多样化的基因库，以便您能够进化并在气候发生的灾难性变化中生存。

But wouldn't it be wonderful if we could create an LLM that could understand what those differences are?

但如果我们能够创建一个能够理解这些差异的法学硕士，那不是很棒吗？

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Now just think about it, right?

现在想想，对吗？

Andrew Huberman:

安德鲁·休伯曼：

Like a truly diverse LLM that integrated all those differences.

就像一个真正多元化的法学硕士整合了所有这些差异。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

But here's what you'd have to do.

但这是你必须做的。

What you'd have to do is to train it up on data from a bunch of individuals.

你所要做的就是根据来自一群人的数据来训练它。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Human individuals.

人类个体。

Now, one of the things about these LLMs is that they don't have a single persona.

现在，这些法学硕士的特点之一是他们没有单一的角色。

They can adopt any persona.

他们可以采用任何角色。

You have to tell it what you're expecting from-

你必须告诉它你的期望是什么-

Andrew Huberman:

安德鲁·休伯曼：

Or ask it in a way that works for you, and you'll get back a certain persona.

或者以适合你的方式提出问题，你就会得到某个角色。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

I once gave it an abstract from a paper, very technical, a computational paper, and I said, "You are a neuroscientist, and I want you to explain this abstract to a 10-year-old." It did it in a way that I could never have done it.

我曾经给过它一篇论文的摘要，非常技术性的计算论文，我说，“你是一位神经科学家，我希望你向一个 10 岁的孩子解释这个摘要。”它以一种我永远无法做到的方式做到了这一点。

Andrew Huberman:

安德鲁·休伯曼：

Was it accurate?

准确吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It really simplified it.

它确实简化了它。

Some of the subtleties were-

一些微妙之处是——

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm

嗯嗯

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

not in it, but it explained what plasticity was and explained what a synapse is.

不在其中，但它解释了可塑性是什么，并解释了突触是什么。

Andrew Huberman:

安德鲁·休伯曼：

Amazing.

太棒了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It did that.

它做到了。

Andrew Huberman:

安德鲁·休伯曼：

It's almost like a qualifying exam for a graduate student.

这几乎就像研究生的资格考试。

I saw something today on X, formerly known as Twitter, that blew my mind, that I wanted your thoughts on, that is very appropriate to what you're saying right now, which is someone was asking questions of an LLM on ChatGPT or maybe one of these other, Anthropic or Claude or something like that.

我今天在 X（以前称为 Twitter）上看到了一些东西，这让我大吃一惊，我想听听您的想法，这与您现在所说的非常合适，有人在 ChatGPT 上询问法学硕士问题，或者可能是其他问题之一，Anthropic 或 Claude 或类似的问题。

I probably misused those names.

我可能误用了这些名字。

One of the AI online sites.

AI 在线网站之一。

And somewhere in the middle of its answers, the LLM decided to just take a break and start looking at pictures of landscapes in Yosemite.

在回答中间的某个地方，法学硕士决定休息一下，开始看优胜美地的风景照片。

Like, the LLM was doing what a maybe cognitively fatigued person or what any kind of person online would do, which was to take a break and look at a couple pictures of something.

就像，法学硕士正在做一个可能认知疲劳的人或任何在线人都会做的事情，那就是休息一下，看几张某物的照片。

Maybe they're thinking about going camping there or something, and then get back to whatever task.

也许他们正在考虑去那里露营什么的，然后再回到任何任务。

We hear about hallucinations in AI.

我们听说过人工智能中的幻觉。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

That it can imagine things that aren't there, just like a human brain.

它可以像人脑一样想象不存在的事物。

But, that blew my mind.

但是，这让我大吃一惊。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I haven't encountered that, but isn't it fascinating?

我没遇到过，但这不是很有趣吗？

That's a sign of a real generative internal model.

这是真正的生成内部模型的标志。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

See, here's the thing that most distinguishes, I think, an LLM from a human is that if you go into a room, quiet room, and just sit there without any sensory stimulation, your brain keeps thinking Right.

看，我认为法学硕士与人类最有区别的一点是，如果你走进一个房间，安静的房间，只是坐在那里，没有任何感官刺激，你的大脑就会一直正确思考。

In other words, you think about what you want to do, planning ahead or something that happened to you during the day, right?

换句话说，你会考虑自己想要做什么、提前计划或者白天发生在你身上的事情，对吗？

Your brain is always generating internally.

你的大脑总是在内部产生。

After talking to you, one of these large language models just goes blank.

与你交谈后，这些大型语言模型之一就变成了空白。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

There is no continuous self-generated thoughts.

没有持续不断的自我产生的想法。

Andrew Huberman:

安德鲁·休伯曼：

And yet we know self-generated thought, and in particular, brain activity during sleep, as you illustrated earlier with the example of sleep spindles and rapid eye movement sleep are absolutely critical for shaping the knowledge that we experienced during the day.

然而，我们知道自我产生的思想，特别是睡眠期间的大脑活动，正如您之前以睡眠纺锤波和快速眼动睡眠为例所说明的那样，对于塑造我们白天所经历的知识绝对至关重要。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

So these LLMs are not quite where we are at yet.

所以这些法学硕士还没有达到我们现在的水平。

They can outperform us in certain things like Go, but how soon will we have LLMs, AI that is, with self-generated internal activity?

他们可以在围棋等某些事情上超越我们，但我们多久才能拥有法学硕士，即具有自我生成的内部活动的人工智能？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

We're getting closer.

我们越来越近了。

And so this is something I'm working on myself, actually, trying to understand how that's done in our own brains, with generating continual brain activity that leads to planning and things.

所以这实际上是我自己正在研究的事情，试图了解我们自己的大脑是如何完成这一过程的，并产生持续的大脑活动，从而导致计划和事情。

We don't know what the answer to that is yet in neuroscience.

我们还不知道神经科学的答案是什么。

And by the way, you go to a lecture, and you hear the words one after the next over an hour, and you see the slides one after the next.

顺便说一句，你去听讲座，一个多小时你会听到一个又一个的单词，你会看到一个又一个的幻灯片。

At the end, you ask a question, right?

最后你问一个问题，对吗？

Just let's think about what you just did.

让我们想想你刚刚做了什么。

Somehow, you're able to integrate all that information over the hour and then use your long-term memory then to come up with some insight or some issue that you want.

不知何故，你能够在一小时内整合所有这些信息，然后使用你的长期记忆来提出一些你想要的见解或一些问题。

How did your brain remember all that information?

你的大脑是如何记住所有这些信息的？

Working memory, traditional working memory that neuroscientists study is only for a few seconds, like maybe a telephone number or something.

工作记忆，神经科学家研究的传统工作记忆只有几秒钟，就像电话号码之类的。

But we're talking about long-term working memory.

但我们谈论的是长期工作记忆。

We don't understand how that is done.

我们不明白这是如何做到的。

And LLMs actually, large language models, can do something.

事实上，法学硕士，大型语言模型，可以做一些事情。

It's called in-context learning, and it was a great surprise because there is no plasticity.

这就是所谓的情境学习，这是一个很大的惊喜，因为它没有可塑性。

The thing learns at the beginning.

事物从一开始就学习。

You train it up on data, and then all it does after that is to inference, fast loop of activity, one word after the next, right?

你用数据训练它，然后它所做的就是推理，快速的活动循环，一个字接着一个字，对吗？

That's what happens with no learning.

这就是不学习就会发生的情况。

But it's been noticed that as you continue your dialogue, it seems to get better at things.

但人们注意到，当你继续对话时，事情似乎会变得更好。

How could that be?

怎么可能呢？

How could it be in context learning even though there's no plasticity?

即使没有可塑性，怎么可能在情境学习中呢？

That's a mystery.

这是一个谜。

We don't know the answer to that question yet, but we also don't know what the answer is for humans either.

我们还不知道这个问题的答案，但我们也不知道人类的答案是什么。

Andrew Huberman:

安德鲁·休伯曼：

Right.

对。

Could I ask you a few questions about you and as it relates to science and your trajectory?

我可以问你一些关于你的问题，以及与科学和你的轨迹有关的问题吗？

Building off of what you were just saying, do you have a practice of meditation or eyes closed, sensory input reduced or shut down, to drive your thinking in a particular way?

根据您刚才所说的，您是否有冥想或闭眼、减少或关闭感官输入的练习，以以特定的方式驱动您的思维？

Or are you at your computer talking to your students and postdocs and sprinting on the beach?

或者您正在电脑前与学生和博士后交谈并在海滩上冲刺？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's funny.

很有趣。

Andrew Huberman:

安德鲁·休伯曼：

Or asleep.

或者睡着了。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, it's funny you mention that because I get my best ideas not sprinting on the beach, but just either walking or jogging.

不，你提到这一点很有趣，因为我最好的想法不是在海滩上冲刺，而是步行或慢跑。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And it's wonderful.

这太棒了。

I don't know.

我不知道。

I think serotonin goes up.

我认为血清素会上升。

It's another neuromodulator I think that that stimulates ideas and thoughts.

我认为这是另一种神经调节剂，可以激发想法和思想。

And so inevitably, I come back to my office, and I can't remember any of those great ideas.

因此，不可避免地，我回到办公室，却记不起任何伟大的想法。

Andrew Huberman:

安德鲁·休伯曼：

What do you do about that?

你对此怎么办？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, now I take notes.

好吧，现在我记笔记。

Andrew Huberman:

安德鲁·休伯曼：

Okay.

好的。

Voice memos?

语音备忘录？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Uh-huh.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And some of them pan out.

其中一些成功了。

There's no doubt about it.

毫无疑问。

Andrew Huberman:

安德鲁·休伯曼：

Sure.

当然。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That you're put into a situation, it is a form of meditation.

你置身于一种情境中，这是一种冥想形式。

If you're running in a steady pace, nothing distracting about the beach.

如果您以稳定的速度跑步，海滩上就不会分散您的注意力。

Andrew Huberman:

安德鲁·休伯曼：

Or do you listen to music or podcasts or-

或者你听音乐或播客还是-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No, I never listen to anything except my own thoughts.

不，除了我自己的想法之外，我从不听任何东西。

Andrew Huberman:

安德鲁·休伯曼：

So there's a former guest on this podcast, she happens to be triple degreed from Harvard, but she's more in the personal coach space, but very, very high level, an impressive mind, impressive human all around.

这个播客中有一位前嘉宾，她恰好拥有哈佛大学的三学位，但她更多的是在私人教练领域，但水平非常非常高，有着令人印象深刻的头脑，令人印象深刻的人。

And she has this concept of wordlessness that can be used to accomplish a number of different things, but this idea that allowing oneself or creating conditions for oneself to enter states throughout the day or maybe once a day of very minimal sensory input.

她有这种无言的概念，可以用来完成许多不同的事情，但这个想法是允许自己或为自己创造条件，全天或一天一次以极少的感官输入进入状态。

No lecture, no podcast, no book, no music, nothing.

没有讲座，没有播客，没有书籍，没有音乐，什么都没有。

And allowing the brain to just idle and go a little bit non-linear, if you will.

如果你愿意的话，让大脑闲置并变得有点非线性。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

Where we're not constructing thoughts or paying attention to anyone else's thoughts through those media venues, in any kind of structured way as a source of great ideas and creativity.

我们不会通过这些媒体场所以任何结构化的方式构建思想或关注其他人的思想，作为伟大思想和创造力的来源。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's been studied.

已经研究过了。

Psychologists call it mind wandering.

心理学家称之为走神。

Andrew Huberman:

安德鲁·休伯曼：

Mind wandering.

心神游荡。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

It is a significant literature, and it's often when you have an aha moment, right?

这是一部重要的文学作品，而且常常是在你恍然大悟的时候，对吧？

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Your mind, and it's wandering, and it's-

你的思绪，它在徘徊，它——

Andrew Huberman:

安德鲁·休伯曼：

Beautiful

美丽

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

thinking non-linearly, in the sense of not following a sequence that is logical, hopping from thing to thing.

非线性思维，即不遵循逻辑顺序，从一件事跳到另一件事。

Often that's when you get a great idea, with just letting your mind wander.

通常，就是在这个时候，你只需让自己的思绪游离，就会产生一个好主意。

Yeah, and that happens to me.

是的，这发生在我身上。

Andrew Huberman:

安德鲁·休伯曼：

I wonder whether Social media and just texting and phones in general have eliminated a lot of the walks to the car after work where one would normally not be on a call or in communication with anyone or anything.

我想知道社交媒体以及短信和电话是否已经消除了人们下班后步行去汽车的情况，而人们通常不会打电话或与任何人或任何事物进行交流。

I used to do experiments where I was pipetting and running immunohistochemistry, and it was very relaxing, and I could think while I was doing-

我过去常常做实验，一边移液一边运行免疫组化，这非常放松，我一边做一边思考——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

it because I knew the procedures and then you had to pay attention to certain things-

因为我知道程序，然后你必须注意某些事情-

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay

好的

Andrew Huberman:

安德鲁·休伯曼：

...

and write them down.

并将它们写下来。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

But I would often feel like, wow, I'm both working and relaxing and thinking of things.

但我常常会觉得，哇，我既在工作，又在放松，并且在思考事情。

And then I would listen to music sometimes.

然后我有时会听音乐。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So we have a whole session, a clip in learning how to learn about exactly this phenomenon.

所以我们有一个完整的课程，一个片段来学习如何准确地了解这种现象。

Here's what we tell our students, is that if you're having trouble with some concept or you don't understand something, you're beating your head against the wall, stop.

我们告诉我们的学生，如果你在某些概念上遇到困难或者你不理解某些东西，你就是在用头撞墙，停下来。

Just go off and do something.

出去做点什么吧。

Go off and clean the dishes.

出去洗碗吧。

Go off and walk around the block.

出去绕着街区走走。

And inevitably, what happens is when you come back, your mind is clear and you figure out what to do.

不可避免的是，当你回来时，你的头脑很清晰，你知道该怎么做。

And that's one of the best pieces of advice that anybody could get because nobody has told us how the brain works.

这是任何人都能得到的最好建议之一，因为没有人告诉我们大脑是如何工作的。

Some people are really good at intuiting because they've experienced maybe-- Okay, the other thing is everybody I know who's really made important contributions, and I'll bet you're one of them, you're struggling with some problem at night and you go to bed and you wake up in the morning, ah, that's the solution.

有些人真的很擅长直觉，因为他们可能经历过——好吧，另一件事是我认识的每个人都真正做出了重要贡献，我敢打赌你就是其中之一，你在晚上与一些问题作斗争，你上床睡觉，早上醒来，啊，这就是解决方案。

That's what I should do, right?

这就是我应该做的，对吗？

Andrew Huberman:

安德鲁·休伯曼：

First thing in the morning when I wake up-

早上起床后第一件事——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes

是的

Andrew Huberman:

安德鲁·休伯曼：

...

is when I'm almost bombarded with, I wouldn't say insight, and not always meaningful insight, but certainly what was unclear becomes immediately clear on waking.

当我几乎被“洞察力”轰炸时，我不会说洞察力，并不总是有意义的洞察力，但肯定的是，那些不清楚的事情在醒来时会立即变得清晰。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

That's the thing that is so amazing about sleep.

这就是睡眠的奇妙之处。

And you can see people who know this can count on it.

您可以看到了解这一点的人可以信赖它。

In other words, the key is to think about it before you go to sleep .

也就是说，关键是睡觉前想一想。

Your brain works on it during the sleep period.

你的大脑在睡眠期间会进行工作。

And so, don't watch TV because then who knows what your brain's going to work on .

所以，不要看电视，因为谁知道你的大脑会做什么。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Use the time before you fall asleep to think about something that is bothering you or maybe something that you're trying to understand, maybe a paper that you read the paper and say, "Oh, I'm tired.

利用入睡前的时间思考一些困扰您的事情，或者您想要理解的事情，也许是您读到的一篇论文，然后说：“哦，我累了。

I'm going to go to sleep." You wake up in the morning and say, "Oh, I know what's going on in that paper." Yeah.

我要去睡觉了。”你早上醒来说，“哦，我知道那张报纸上写了什么。”是的。

That's what happens.

就是这样。

Once you know something about how the brain works, you can take advantage of that.

一旦你了解了大脑的工作原理，你就可以利用它。

Andrew Huberman:

安德鲁·休伯曼：

Do you pay attention to your dreams?

你关注你的梦想吗？

Do you record them?

你把它们记录下来吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No. Okay.

不，好吧。

So here's the problem.

所以问题就在这里。

Dreams seem so iconic and a lot of people somehow attribute things to them.

梦想看起来如此具有标志性，很多人都以某种方式将事物归因于梦想。

But there has never been any good theory or any good understanding, first of all, why we dream.

但从来没有任何好的理论或任何好的理解，首先，我们为什么做梦。

It's still not completely clear.

目前还不完全清楚。

There are some ideas, but or why this particular dream?

有一些想法，但是或者为什么会有这个特殊的梦想？

Does that have some significance for you?

这对你来说有什么意义吗？

And the only thing that I know that might explain a little bit is that the dreams are often very visual, rapid eye movement sleep, so that there's something happening that actually, it's interesting.

我所知道的唯一可以解释的一点是，梦通常是非常视觉化的、快速眼动的睡眠，所以实际上发生了一些有趣的事情。

All the neuromodulators are downregulated during sleep, and then during REM sleep, acetylcholine comes up.

所有神经调节剂在睡眠期间都会下调，然后在快速眼动睡眠期间，乙酰胆碱会出现。

So that's a very powerful neuromodulator.

所以这是一种非常强大的神经调节剂。

It's important for attention, for example, but it doesn't come up in the prefrontal cortex.

例如，它对于注意力很重要，但它不会出现在前额皮质中。

Which means that the circuits in the prefrontal cortex that are interpreting the sensory input coming in are not turned on.

这意味着前额皮质中负责解释传入的感觉输入的电路没有打开。

So whatever happens in your visual cortex is not being monitored anymore.

因此，无论你的视觉皮层发生什么，都不再受到监控。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

So you get bizarre things, that you start floating and things happen to you.

所以你会遇到一些奇怪的事情，你开始漂浮，事情发生在你身上。

And it's not anchored anymore.

而且它不再锚定了。

But that still doesn't explain why you have that period.

但这仍然无法解释为什么会有那个时期。

It's important because if you block it, and there are some sleeping pills that do block it, it really does cause problems with normal cognitive function.

这很重要，因为如果你阻止它，并且有些安眠药确实可以阻止它，它确实会导致正常认知功能出现问题。

Andrew Huberman:

安德鲁·休伯曼：

Cannabis as well.

大麻也是如此。

People who come off cannabis experience a tremendous REM rebound-

戒掉大麻的人会经历快速眼动睡眠的巨大反弹——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Ah, interesting

啊，有趣

Andrew Huberman:

安德鲁·休伯曼：

...

and lots of dreaming in the days and weeks and months after cannabis-

在吸食大麻后的几天、几周和几个月里，我做了很多梦——

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Wow.

哇。

Interesting

有趣

Andrew Huberman:

安德鲁·休伯曼：

...

I don't want to call it withdrawal because that has a different meaning.

我不想称之为撤回，因为那有不同的含义。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

No. It's the imbalance that was caused because the brain adjusted to the endocannabinoid levels.

不，这是由于大脑适应内源性大麻素水平而引起的不平衡。

And now, it's got to go back, and it takes time.

而现在，它必须回去，而且需要时间。

But it's interesting.

但这很有趣。

Isn't it interesting?

是不是很有趣？

It affects dreams.

它会影响梦想。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I think that may be a clue.

我想这可能是一个线索。

Maybe we should-

也许我们应该——

Andrew Huberman:

安德鲁·休伯曼：

Yeah, very common phenomenon, I'm told.

是的，据我所知，这是很常见的现象。

I'm not a cannabis user, but no judgment there.

我不是大麻使用者，但没有判断力。

I just am not.

我只是不是。

It's actually a book I read years ago when I was in college, so a long time ago, by Alan Hobson, who was out at Harvard.

这实际上是我多年前读过的一本书，当时我还在上大学，所以很久以前，作者是艾伦·霍布森（Alan Hobson），当时他在哈佛大学。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, yes.

哦，是的。

I know him.

我认识他。

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Oh, cool.

哦，酷。

So I never met him, but he had this interesting idea that dreams, in particular rapid eye movement dreams, were so very similar to the experience that one has on certain psychedelics, LSD, lysergic acid diethylamide, or psilocybin, and that perhaps dreams are revealing the unconscious mind.

所以我从未见过他，但他有一个有趣的想法，即梦，特别是快速眼动梦，与人们服用某些迷幻药、LSD、麦角酸二乙胺或裸盖菇素的经历非常相似，而且也许梦正在揭示无意识的心灵。

And not saying this in any psychological terms, that when we're asleep, our conscious mind can't control thought and action in the same way, obviously.

显然，这并不是用任何心理学术语来说的，当我们睡着时，我们的意识无法以同样的方式控制思想和行动。

It's sort of a recession of the waterline, so we're getting more of the unconscious processing revealed.

这有点像水线的衰退，所以我们正在揭示更多的无意识处理过程。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's an interesting hypothesis.

这是一个有趣的假设。

How would you test it?

你会如何测试它？

Andrew Huberman:

安德鲁·休伯曼：

I'd probably have to put someone in a scanner, have them go to sleep, put them in the scanner on a psilocybin journey.

我可能不得不将某人放入扫描仪中，让他们入睡，将他们放入扫描仪中进行裸盖菇素之旅。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I see.

我明白了。

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

This kind of thing.

这种事。

It's tough.

这很难。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Andrew Huberman:

安德鲁·休伯曼：

Any of these observational studies, of course, we both know are deficient in the sense that what you'd really like to do is control the neural activity.

当然，我们都知道，任何这些观察性研究都是有缺陷的，因为你真正想做的是控制神经活动。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's right.

没错。

Andrew Huberman:

安德鲁·休伯曼：

You'd like to get in there and tickle the neurons over here and see how the brain changes, and you'd love to get real-time subjective report.

你想进入那里，刺激这里的神经元，看看大脑是如何变化的，你也想得到实时的主观报告。

This is the problem with sleep and dreaming is you can wake people up and ask them what they were just dreaming about, but you can't really know what they're dreaming about in real time.

这就是睡眠和做梦的问题，你可以叫醒人们并询问他们刚刚做了什么梦，但你无法实时知道他们在做梦。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

It's true.

这是真的。

Yeah.

是的。

It's true.

这是真的。

By the way, there are two kinds of dreams.

顺便说一下，梦有两种。

Andrew Huberman:

安德鲁·休伯曼：

Hmm.

嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Very interesting.

非常有趣。

So if you wake someone up during REM sleep, you get very vivid changing.

因此，如果你在快速眼动睡眠期间叫醒某人，你会发生非常生动的变化。

Dreams, they're always different and changing.

梦想，总是不同的，总是在变化的。

But if you wake someone up during slow-wave sleep, you often get a dream report, but it's a kind of dream that keeps repeating over and over again every night.

但如果你在慢波睡眠期间叫醒某人，你经常会得到梦的报告，但这是一种每晚不断重复的梦。

And it's a very heavy emotional content.

而且是情感非常沉重的内容。

Andrew Huberman:

安德鲁·休伯曼：

Interesting.

有趣。

That's in slow-wave sleep.

那是在慢波睡眠中。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Because I've had a few dreams over and over and over throughout my life.

因为我一生中一遍又一遍地做过一些梦想。

So those would be in slow-wave sleep.

所以那些人将处于慢波睡眠状态。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, probably slow-wave sleep.

是的，可能是慢波睡眠。

Yeah.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Fascinating.

令人着迷。

As a neuroscientist who's computationally oriented, but really you incorporate the biology so well into your work, so that's one of the reasons you're you, you're this luminary of your field, and who's also now really excited about AI.

作为一名以计算为导向的神经科学家，但实际上你将生物学很好地融入到了你的工作中，这就是你成为你所在领域的杰出人物的原因之一，而且你现在也对人工智能感到非常兴奋。

What are you most excited about now?

你现在最兴奋的是什么？

Like if you had, and of course this isn't the case, but if you had 24 more months to just pour yourself into something, and then you had to hand the keys to your lab over to someone else, what would you go all in on?

就像如果你有，当然情况并非如此，但如果你还有 24 个月的时间来全身心投入某件事，然后你必须将实验室的钥匙交给其他人，你会全力以赴做什么？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, so the NIH has something called the Pioneer Award.

嗯，所以美国国立卫生研究院有一个叫做先锋奖的东西。

And what they're looking for are big ideas that could have a huge impact, right?

他们正在寻找的是能够产生巨大影响的伟大想法，对吗？

So I put one in recently, and the title is, Temporal Context in Brains and Transformers.

所以我最近放了一篇，标题是《大脑和变形金刚中的时间背景》。

Andrew Huberman:

安德鲁·休伯曼：

And in brains and transforms?

那么在大脑和转化中呢？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Transformers.

变形金刚。

Andrew Huberman:

安德鲁·休伯曼：

Formers.

前者。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

AI.

人工智能。

Right.

正确的。

The key to ChatGPT is the fact there's this new architecture, it's a deep learning architecture, feed forward network, but it's called a transformer.

ChatGPT 的关键在于有一个新的架构，它是一个深度学习架构，前馈网络，但它被称为变压器。

And it has certain parts in it that are unique.

它有某些独特的部分。

There's one called self-attention.

有一种叫做自我关注。

And it's a way of doing what is called temporal context.

这是一种所谓的时间上下文的方式。

What it does is it connects words that are far apart.

它的作用是将相距较远的单词连接起来。

You give it a sequence of words, and it can tell you the association.

你给它一个单词序列，它可以告诉你关联。

Like if I use the word this, and then you have to figure out in the last sentence, what did it refer to?

就像如果我使用这个词，然后你必须弄清楚最后一句中它指的是什么？

Well, there's three or four nouns it could've referred to, but from context, you can figure out which one it does, and you can learn that association.

嗯，它可能引用了三四个名词，但是从上下文中，你可以弄清楚它指的是哪一个，并且你可以了解这种关联。

Andrew Huberman:

安德鲁·休伯曼：

Could I just play with another example to make sure I understand this correctly?

我可以再举一个例子来确保我正确理解这一点吗？

I've seen these word bubble charts, like if we were to say piano, you'd say keys, you'd say music, you'd say seat.

我看过这些单词气泡图，就像如果我们说钢琴，你会说琴键，你会说音乐，你会说座位。

And then, it builds out a word cloud of association.

然后，它构建出一个关联词云。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, yeah.

哦，是的。

Right.

正确的。

Andrew Huberman:

安德鲁·休伯曼：

And then over here we'd say, I don't know, I'm thinking about the Salk Institute.

然后我们会说，我不知道，我正在考虑索尔克研究所。

I'd say sunset, Stonehenge, anyone that looks up, there's this phenomenal Salk hedge.

我会说日落，巨石阵，任何抬头的人，都会看到这个非凡的索尔克树篱。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's kind of a, yeah.

这有点像，是的。

Andrew Huberman:

安德鲁·休伯曼：

Then you start building out a word cloud over there.

然后你开始在那里构建一个词云。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Right.

对。

Andrew Huberman:

安德鲁·休伯曼：

These are disparate things, except I've been to a classical music concert at the Salk Institute.

这些是完全不同的事情，除了我去过索尔克学院的古典音乐会。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yeah, Symphony of Salt.

是的，《盐交响曲》。

Andrew Huberman:

安德鲁·休伯曼：

Twice.

两次。

So they're not completely non-overlapping.

所以它们并不是完全不重叠的。

And so you start getting associations at a distance, and eventually they bridge together.

所以你开始在远处建立联系，最终它们连接在一起。

Is this what you're referring to?

你指的是这个吗？

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Andrew Huberman:

安德鲁·休伯曼：

Okay.

好的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I think that that's an example, but it turns out that every word is ambiguous.

我认为这是一个例子，但事实证明每个词都是有歧义的。

It has like three, four meanings.

大概有三、四种意思。

And so you have to figure that out from context.

所以你必须从上下文中弄清楚这一点。

And, so in other words, there are words that live together.

换句话说，有些词是共存的。

Andrew Huberman:

安德鲁·休伯曼：

Mm-hmm.

嗯嗯。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

And that come up often.

这经常出现。

And you can learn that from just by predicting the next word in a sentence.

你可以通过预测句子中的下一个单词来了解这一点。

That's how a transformer is trained.

这就是变压器的训练方式。

You give it a bunch of words, and it keeps predicting the next word in a sentence.

你给它一堆单词，它就会不断预测句子中的下一个单词。

Andrew Huberman:

安德鲁·休伯曼：

Oh, like in my email now, it tries to predict the next word.

哦，就像我现在的电子邮件一样，它试图预测下一个单词。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Yes.

是的。

Exactly.

确切地。

Andrew Huberman:

安德鲁·休伯曼：

And it's mostly right part of the time.

而且大部分时间都是正确的。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Okay.

好的。

Well, that's because it's a very primitive version of this algorithm.

嗯，那是因为它是该算法的一个非常原始的版本。

What happened is if you train it up on enough, not only can it answer the next word, it internally builds up a semantic representation in the same way you describe the words that are related to each other, having associations.

发生的情况是，如果你对它进行足够的训练，它不仅可以回答下一个单词，它还会在内部构建语义表示，就像你描述彼此相关、具有关联的单词一样。

It can figure that out, and it has representations inside this very large network with trillions of parameters.

它可以弄清楚这一点，并且在这个拥有数万亿参数的庞大网络中拥有表示。

Unbelievable how big they have gotten.

令人难以置信的是他们已经变得有多大了。

And those associations now form an internal model of the meaning of the sentence.

这些关联现在形成了句子含义的内部模型。

Literally, this is something that now we've probed these transformers, and so we pretty much are pretty confident.

从字面上看，这是我们现在已经对这些变压器进行了探索，所以我们非常有信心。

And that means that it's forming an internal model of the outside world, in this case, a bunch of words.

这意味着它正在形成外部世界的内部模型，在本例中是一堆单词。

And that's how it's able to actually respond to you in a way that is sensible, that makes sense, and actually is interesting, and so forth.

这就是它能够以一种明智的、有意义的、实际上有趣的方式实际回应你的方式。

And it's all the self-attention I'm talking about.

我所说的都是自我关注。

So in any case, my pioneer proposal is to figure out how does the brain do self-attention?

所以无论如何，我的先驱建议是弄清楚大脑是如何进行自我注意力的？

Right?

正确的？

It's got to do it somehow.

它必须以某种方式做到这一点。

And I'll give you a little hint, basal ganglia.

我会给你一点提示，基底神经节。

Andrew Huberman:

安德鲁·休伯曼：

It's in the basal ganglia.

它位于基底神经节。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

That's my hypothesis.

这是我的假设。

Well, we'll see.

好吧，我们拭目以待。

I'll be working with experimental people.

我将与实验人员一起工作。

I've worked with John Reynolds, for example, who studies primate visual cortex, and we've looked at traveling waves there, and there are other people that have looked at in primates.

例如，我曾与约翰·雷诺兹（John Reynolds）合作，他研究灵长类动物的视觉皮层，我们研究了那里的行波，还有其他人研究了灵长类动物。

And so now these traveling waves I think are also a part of the pieces of the puzzle that are going to give us a much better view of how the cortex is organized and how it interacts with the basal ganglia.

所以现在，我认为这些行波也是拼图的一部分，它们将使我们更好地了解皮层的组织方式以及它如何与基底神经节相互作用。

We've already been there, but neuroscientists have studied each one of these parts of the brain independently, and now we have to start thinking about putting the pieces of the puzzle together, right?

我们已经做到了这一点，但神经科学家已经独立研究了大脑的每一部分，现在我们必须开始考虑将拼图的各个部分拼凑在一起，对吗？

Trying to get all the things that we know about these areas and see how they work together in a computational way, and that's really where I want to go.

尝试获取我们所了解的有关这些领域的所有信息，并了解它们如何以计算方式协同工作，这才是我真正想要去的地方。

Andrew Huberman:

安德鲁·休伯曼：

I love it, and I do hope they decide to fund your Pioneer Award.

我喜欢它，我确实希望他们决定资助你的先锋奖。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

I do too.

我也是。

Andrew Huberman:

安德鲁·休伯曼：

Yeah.

是的。

And should they make the bad decision not to, maybe we'll figure out another way to get the work done, and certainly you will.

如果他们做出不这样做的错误决定，也许我们会想出另一种方法来完成工作，当然你会的。

Terry, I want to thank you, first of all for coming here today, taking time out of your busy cognitive and running and teaching and research schedule to share your knowledge with us, and also for the incredible work that you're doing on public education and teaching the public, I should say, giving the public resources to learn how to learn better at zero cost.

特里，我首先要感谢你今天来到这里，从繁忙的认知、跑步、教学和研究日程中抽出时间与我们分享你的知识，还要感谢你在公共教育和教导公众方面所做的令人难以置信的工作，我应该说，为公共资源提供了学习如何以零成本更好地学习的方法。

So we will certainly provide links to Learning How to Learn and your book and to these other incredible resources that you've shared.

因此，我们肯定会提供“学习如何学习”和您的书以及您共享的其他令人难以置信的资源的链接。

And you've also given us a ton of practical tools today related to exercise mitochondria and some of the things that you do, which of course are just your versions of what you do, but that certainly, certainly are going to be of value to people, including me, in our cognitive and physical pursuits, and frankly, just longevity.

今天，您还为我们提供了大量与运动线粒体和您所做的一些事情相关的实用工具，这些当然只是您所做的事情的版本，但这肯定会对人们（包括我）在我们的认知和身体追求方面有价值，坦率地说，只是长寿。

This is not lost on me and those listening that your vigor is, as I mentioned earlier, undeniable, and it's been such a pleasure over the years to just see the amount of focus and energy and enthusiasm that you bring to your work, and to observe that it not only hasn't slowed, but you're picking up velocity.

我和那些听众并没有忽视这一点，正如我之前提到的，你的活力是不可否认的，多年来，我很高兴看到你为工作带来的专注、精力和热情，并观察到它不仅没有放缓，而且还在加快速度。

So thank you so much for educating us today.

非常感谢您今天对我们的教育。

I know I speak on behalf of myself and many, many people listening and watching.

我知道我代表我自己和很多很多聆听和观看的人发言。

This is a real gift, a real incredible experience to learn from you.

这是一份真正的礼物，是一次值得向您学习的真正令人难以置信的经历。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Wow.

哇。

Andrew Huberman:

安德鲁·休伯曼：

So thank you so much.

非常感谢。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Well, thank you, and I have to say that I've been blessed over the years with wonderful students and wonderful colleagues, and I count you among them-

嗯，谢谢你，我不得不说，多年来我很幸运拥有优秀的学生和优秀的同事，我把你算在其中 -

Andrew Huberman:

安德鲁·休伯曼：

Thank you

谢谢你

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

...

who really I've learned a lot from.

我确实从他身上学到了很多东西。

Andrew Huberman:

安德鲁·休伯曼：

Thank you.

谢谢你。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

But science is a social activity, and we learn from each other, and we all make mistakes.

但科学是一项社会活动，我们互相学习，我们都会犯错误。

But we learn from our mistakes, and that's the beauty of science is that we can make progress.

但我们从错误中吸取教训，这就是科学的美妙之处在于我们可以取得进步。

Now, your career has been remarkable, too, because you have affected and influenced more people than anybody else I know personally with the knowledge that you are broadcasting through your interviews, but also just in terms of your interests.

现在，你的职业生涯也非常出色，因为你影响和影响的人比我个人认识的任何人都多，据我所知，你通过采访进行传播，但也只是就你的兴趣而言。

I'm really impressed with what you've done, and I want you to keep at it because we need people like you.

你所做的事情给我留下了深刻的印象，我希望你继续下去，因为我们需要像你这样的人。

We need scientists who can actually express and reach the public.

我们需要能够真正表达并影响公众的科学家。

If we don't do that, everything we do is behind closed doors, right?

如果我们不这样做，我们所做的一切都是闭门造车，对吗？

Nothing gets out, and so you're one of the best of the breed in terms of being able to explain things in a clear way that gets through to more people than anybody else I know.

没有任何内容泄露出来，因此，就能够以清晰的方式解释事情而比我认识的任何人都了解的人而言，你是最优秀的人之一。

Andrew Huberman:

安德鲁·休伯曼：

Oh, well, thank you.

哦，好的，谢谢你。

I'm very honored to hear that.

我很荣幸听到这个消息。

It's a labor of love for me, and I'll take those words in, and I really appreciate it.

这对我来说是一种爱的劳动，我会接受这些话，我真的很感激。

It's an honor and a privilege to sit with you today, and please come back again.

今天很荣幸能和你们坐在一起，请再次回来。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

Oh, I would love to.

哦，我很乐意。

I would love to, yeah.

我很愿意，是的。

Andrew Huberman:

安德鲁·休伯曼：

All right.

好吧。

Thank you, Terry.

谢谢你，特里。

Dr. Terry Sejnowski:

特里·塞诺夫斯基博士：

You're welcome.

不客气。

Andrew Huberman:

安德鲁·休伯曼：

Thank you for joining me for today's discussion with Dr. Terry Sejnowski.

感谢您参加今天与 Terry Sejnowski 博士的讨论。

To find links to his work, the zero-cost online learning portal that he and his colleagues have developed, and to find links to his new book, please see the show note captions.

要查找他的作品（他和他的同事开发的零成本在线学习门户）的链接，以及查找他的新书的链接，请参阅节目注释标题。

If you're learning from and/or enjoying this podcast, please subscribe to our YouTube channel.

如果您正在学习和/或喜欢此播客，请订阅我们的 YouTube 频道。

That's a terrific zero-cost way to support us.

这是支持我们的绝佳零成本方式。

In addition, please follow the podcast on both Spotify and Apple, and on both Spotify and Apple, you can leave us up to a five-star review.

此外，请关注 Spotify 和 Apple 上的播客，在 Spotify 和 Apple 上，您都可以给我们留下五星级的评论。

Please check out the sponsors mentioned at the beginning and throughout today's episode.

请查看今天节目开头和整个节目中提到的赞助商。

That's the best way to support this podcast.

这是支持这个播客的最佳方式。

If you have questions or comments about the podcast or guests or topics that you'd like me to consider for the Huberman Lab Podcast, please put those in the comments section on YouTube.

如果您对播客、嘉宾或主题有任何疑问或意见，希望我为 Huberman 实验室播客考虑，请将这些问题或意见放入 YouTube 的评论部分。

I do read all the comments.

我确实阅读了所有评论。

For those of you that haven't heard, I have a new book coming out.

对于那些还没有听说过的人，我即将出版一本新书。

It's my very first book.

这是我的第一本书。

It's entitled "Protocols: An Operating Manual for the Human Body." This is a book that I've been working on for more than five years, and that's based on more than 30 years of research and experience, and it covers protocols for everything from sleep to exercise to stress control, protocols related to focus and motivation, and of course, I provide the scientific substantiation for the protocols that are included.

它的标题是“协议：人体操作手册”。这是我花了五年多时间编写的一本书，它基于 30 多年的研究和经验，涵盖了从睡眠到运动到压力控制的各个方面的方案，以及与注意力和动机相关的方案，当然，我还为所包含的方案提供了科学依据。

The book is now available by presale at protocolsbook.com.

该书现已在protocolbook.com 上预售。

There you can find links to various vendors.

在那里您可以找到各个供应商的链接。

You can pick the one that you like best.

您可以选择您最喜欢的一个。

Again, the book is called "Protocols: An Operating Manual for the Human Body." If you're not already following me on social media, I am Huberman Lab on all social media platforms.

同样，这本书的名字是“协议：人体操作手册”。如果您还没有在社交媒体上关注我，我是所有社交媒体平台上的 Huberman Lab。

So that's Instagram, X, formerly known as Twitter, Threads, Facebook, and LinkedIn.

这就是 Instagram、X，以前称为 Twitter、Threads、Facebook 和 LinkedIn。

And on all those platforms, I discuss science and science-related tools, some of which overlaps with the content of the Huberman Lab podcast, but much of which is distinct from the content on the Huberman Lab podcast.

在所有这些平台上，我讨论科学和与科学相关的工具，其中一些与胡伯曼实验室播客的内容重叠，但其中大部分与胡伯曼实验室播客的内容不同。

Again, that's Huberman Lab on all social media platforms.

再说一次，这就是所有社交媒体平台上的 Huberman Lab。

If you haven't already subscribed to our Neural Network Newsletter, our Neural Network Newsletter is a zero-cost monthly newsletter that includes podcast summaries, as well as protocols in the form of brief one to three-page PDFs.

如果您还没有订阅我们的神经网络新闻通讯，我们的神经网络新闻通讯是一份零成本的每月新闻通讯，其中包括播客摘要以及一到三页 PDF 形式的协议。

Those one to three-page PDFs cover things like deliberate heat exposure, deliberate cold exposure.

这些一到三页的 PDF 涵盖了诸如故意热暴露、故意冷暴露等内容。

We have a foundational fitness protocol.

我们有一个基本的健身协议。

We also have protocols for optimizing your sleep, dopamine, and much more.

我们还有优化您的睡眠、多巴胺等的方案。

Again, all available, completely zero cost.

再次强调，一切可用，完全零成本。

Simply go to hubermanlab.com, go to the Menu tab, scroll down to Newsletter, and provide your email.

只需访问 hubermanlab.com，转到“菜单”选项卡，向下滚动到“时事通讯”，然后提供您的电子邮件即可。

We do not share your email with anybody.

我们不会与任何人分享您的电子邮件。

Thank you once again for joining me for today's discussion with Dr. Terry Sejnowski, and last but certainly not least, thank you for your interest in science.

再次感谢您参加今天与 Terry Sejnowski 博士的讨论，最后但同样重要的是，感谢您对科学的兴趣。