运用基于神经科学的方案提升学习速度与健康水平 | 波比·克拉姆博士

欢迎来到Huberman实验室播客，在这里我们讨论科学及基于科学的日常生活工具。我是Andrew Huberman，斯坦福医学院的神经生物学和眼科学教授。今天的嘉宾是Poppy Crum博士。

Welcome to the Huberman Lab Podcast where we discuss science and science based tools for everyday life. I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine. My guest today is Doctor. Poppy Crum. Doctor.

Poppy Crum是神经科学家、斯坦福大学教授，曾任杜比实验室首席科学家。她的研究聚焦于技术如何加速神经可塑性与学习，并全面提升我们的生活体验。你肯定听说过甚至使用过可穿戴设备和睡眠科技——它们能监测睡眠、告诉你获得了多少慢波睡眠和快速眼动睡眠，还能调控睡眠环境及房间温度。很快，可穿戴与可听戴技术将成为你生活的一部分。顾名思义，可听戴技术能聆听你和他人的声音，推断出最适合你即时健康与心理状态的方案。

Poppy Crum is a neuroscientist, a professor at Stanford and the former chief scientist at Dolby Laboratories. Her work focuses on how technology can accelerate neuroplasticity and learning and generally enrich our life experience. You've no doubt heard about and perhaps use wearables and sleep technologies that can monitor your sleep, tell you how much slow wave sleep you're getting, how much REM sleep and technologies that can control the temperature of your sleep environment and your room environment. Well, you can soon expect wearables and hearable technologies to be part of your life. Hearable technologies are as the name suggests, technologies that can hear your voice and the voice of other people and deduce what is going to be best for your immediate health and your states of mind.

信不信由你，这些技术将理解你的大脑状态和目标，并相应调整你的家庭、工作等环境，让你更专注、更彻底放松，并与人建立更深层次连接。正如Poppy所言，这一切现在听起来或许像科幻，甚至有些令人抗拒或恐惧，但她将解释这如何大幅改善儿童与成人的生活，并真正增强人类共情能力。在本期节目中，你会发现Poppy是位真正的跨界思想家和科学家。她有着独特经历——幼年时就发现自己拥有绝对音感。

Believe it or not, these technologies will understand your brain states, your goals, and it will make changes to your home and working and other environments so that you can focus better, relax more thoroughly and connect with other people on a deeper level. As Poppy explains, all of this might seem kind of space age and maybe even a little aversive or scary now, but she explains how it will vastly improve life for both kids and adults and indeed increase human human empathy. During today's episode, you'll realize that Poppy is a true out of the box thinker and scientist. She has a really unique story. She discovered she has perfect pitch at a young age.

她解释了这种能力的含义及其如何塑造她的世界观与工作。Poppy还慷慨地为所有听众创建了一个零成本的分步指南，让你能构建定制化AI工具来提升任意技能，并建立更佳的健康方案与日常习惯。需要强调的是，使用这个工具完全不需要编程知识，任何人都能上手。

She explains what that is and how that shaped her worldview and her work. Poppy also graciously built a zero cost step by step protocol for all of you. It allows you to build a custom AI tool to improve at any skill you want and to build better health protocols and routines. I should point out that you don't need to know how to program in order to use this tool that she's built. Anyone can use it.

如你将看到的，它极其实用。我们在节目说明中提供了链接。今天的对话不同于以往任何一期，它是对未来的真实窥探，也为你指明了当下就能改善生活的新工具。在开始前，我想强调本播客独立于我在斯坦福的教学与研究职责。

And as you'll see, it's extremely useful. We provide a link to it in the show note captions. Today's conversation is unlike any that we previously had on the podcast. It's a true glimpse into the future, and it also points you to new tools that you can use now to improve your life. Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford.

但这确实体现了我向公众免费提供科学及科学相关工具信息的愿望与努力。秉承这一理念，本期节目包含赞助商内容。现在，有请我与Poppy Crum博士的对话。

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. In keeping with that theme, today's episode does include sponsors. And now for my conversation with Doctor. Poppy Crum. Doctor.

Poppy Crum，欢迎你。

Poppy Crum, welcome.

谢谢，桑迪。能来到这里真是太好了。

Thanks, Sandy. It's great to be here.

很高兴再次见到你。我们应该现在告诉大家，我们曾是研究生同学，但这不是你此行的原因。你之所以在这里，是因为你从事着极具原创性的工作。你涉足过许多不同的技术领域，神经科学等等。今天我想聊很多话题，但我想先从神经可塑性谈起，这是我们神经系统根据经验做出改变的惊人能力。

Great to see you again. We should let people know now, we were graduate students together, but that's not why you're here. You're here because you do incredibly original work. You've worked in so many different domains of technology, neuroscience, etcetera. Today, I wanna talk about a lot of things, but I wanna start off by talking about neuroplasticity, this incredible ability of our nervous systems to change in response to experience.

我知道我对神经可塑性的理解，但我想了解你是如何看待神经可塑性的。特别是，我想知道，你是否认为我们的大脑比大多数人认为的更具可塑性？比如，我们能否改变的程度远超想象？只是我们尚未找到实现的方法？或者你认为我们的大脑相当固定？

I know how I think about neuroplasticity, but I wanna know how you think about neuroplasticity. In particular, I wanna know, do you think our brains are much more plastic than most of us believe? Like, can we change much more than we think? And we just haven't access the ways to do that? Or do you think that our brains are pretty fixed?

而为了推动人类物种进步，我们可能不得不，我不知道，创造机器人或其他东西来完成我们因大脑固定而无法胜任的工作。让我们先听听你对神经可塑性的定义以及你认为其限制是什么的看法。

And in order to make progress as a species, we're gonna have to, I don't know, create robots or something to do the work that we're not able to do because our brains are fixed. Let's start off by just getting your take on what neuroplasticity is and what you think the limits on it are.

我确实认为我们的可塑性远超日常讨论或意识到的程度。关于创造机器人这一点，我们创造的机器人越多，随之而来的是人类在使用机器人作为合作伙伴或工具增强能力时产生的神经可塑性。因此，我对神经可塑性的理解很大程度上在于尝试理解——这也是我职业生涯中大量实践的——在开发和构建技术时，要考虑到它们如何塑造我们的大脑。我们日常生活中接触的一切，无论是环境与背景的统计数据，还是日常使用的技术，都在通过神经可塑性以各种方式重塑我们的大脑，有些影响更为显著。

I do think we're much more plastic than and and than we talk about or we realize in our daily lives. And and just to your point about creating robots, the more we create robots, there's neuroplasticity that comes with using comes robots as humans when we use them in partnerships or as tools to accelerate our capabilities. So neuroplasticity, the way where I resonate with it a lot is trying to understand, and this is what I've done a lot of in my career, is thinking about building and developing technologies, but with an understanding of how they shape our brain. Everything we engage with in our daily lives, whether it's the statistics of our environments and our context, or the technologies we use on a daily basis, are shaping our brains ways through neuroplasticity. Some more than others.

随着年龄增长，我们知道某些改变高度依赖于我们的专注与参与程度，而非被动消费与变化。但我认为，当前每个人都应该更多地思考他们使用的技术——尤其是在人工智能和沉浸式技术时代——如何塑造或构建我们未来的大脑。随便翻开任何一本神经科学基础医学院教材，你都会看到几页关于“小人图”的内容。什么是小人图？它是一种数据表征，但当你看到时，会觉得这个图形有点滑稽。

Some we know as we age are very dependent on how attentive and engaged we are as opposed to passively just consuming and changing. But we are in a place where everyone, I believe, needs to be thinking more about how the technologies they're using, especially in the age of AI and immersive technologies, how they are shaping or architecting our brains as we move forward. You go to any Neuroscience 101 medical school textbook, and there's something you'll see a few pages on something called the homunculus. Now, what is the homunculus? It's a data representation, but it'll be this sort of funny looking creature when you see it.

你看到的那个扭曲人形图像，实际上只是大脑中负责编码和表征触觉信息的细胞数量的数据可视化。有趣的是，这个图像源自20世纪40年代怀尔德·潘菲尔德的研究。他在癫痫患者手术前记录了他们的体感细胞活动。由于大脑皮层没有痛觉受体，他可以在患者清醒状态下触碰其大脑不同区域，让他们报告身体感受到的触觉。通过这种皮层映射，我们最终得到了小人图。

But that picture of this sort of distorted human that you're looking at is really just data representation of how many cells in your brain are helping, are coding and representing information for your sense of touch. And image though, and this is where things get kind of funny, that image comes from Wilder Penfield back in the '40s. He recorded somatosensory cells of patients just before they were to have surgery for epilepsy and such. Since we don't have pain receptors in our cortex, he could have this awake human and be able to touch different parts of their brain and ask them, you know, to report what sensation they felt on their bodies. And so he mapped that part of their their cortex, and then that that's how we ended up with the homunculus.

你会发现，它的嘴唇会更大。背部某些区域的敏感度会降低，那些你本就感觉不那么敏锐的部位。快进到今天，当你观察这个小人图时，我总会让人们思考一个问题：这张图有什么问题？要知道，这是1940年的图像，至今仍出现在每本教科书中。

And you'll see, you know, it'll have bigger lips. It'll have, smaller parts of your back, and the areas where you just don't have the same sensitivities. Well, fast forward to today. When you look at that homunculus, one of the things I always will ask people to think about is, you know, what's wrong with this image? You know, this is an image from 1940 that is still in every textbook.

斯坦福的学生一看就会立刻指出：拇指应该更大，因为我们整天都在刷手机。由于总在移动设备上打字，我的手指确实更敏感了。或许他们还会说：脚踝尺寸没变，但我们现在开车远比40年代频繁。若生活在不同地区，驾驶习惯也不同。再过几年，可能我们都不需要开车了，这些神经资源会被优化到其他部位。

And, you know, any Stanford student will look at it and they'll immediately say, Well, the thumb should be bigger, because we do this all day long. And I've got more sensitivity in my fingers because I'm always typing on my mobile device, which is absolutely true. Or maybe they'll say something like, Well, the ankles are the same size, and we drive cars now a lot more than we did in the 40s. Or maybe if I live different part of the world, I drive on one side versus the other. And in a few years, we probably won't be driving and those resources get optimized elsewhere.

小人图本质上是大脑为帮助我们成功而分配资源的示意图。这些资源就是我们有限的脑细胞，支撑着我们在世界中蓬勃发展所需的能力。其美妙之处在于：当你培养专长时，会获得更多支持——更多资源助力你精进这项技能，但这些资源也会变得更专精。比如作为小提琴手，我的左手指尖会获得更多脑细胞支持，右脑体感皮层会发育出更敏锐的触觉，让我演奏时更流畅精湛。

So what the homunculus is, is it's a representation of how our brain has allocated resources to help us be successful. And those resources are the limited cells we have that support whatever we need to flourish in our world. And the beauty of that is when you develop expertise, you develop more support, more resources go to helping you do that thing, but they also get more specific. They develop more specificity so that, you know, I might have suddenly a lot more cells in my brain devoted to helping me. I'm a violinist and my left hand, my right hemisphere, my somatosensory cortex, I'm going have a lot more cells that are helping me feel my fingers and the tips of everything so that I can be fluid and more virtuosic.

这意味着我拥有更多脑细胞，但它们分工更专门化。它们赋予我更敏锐的感知力，提供更精细的差异化数据——这正是我的大脑所需所应的。因此无论是音乐训练还是电子游戏，所有这些都在重塑我们的大脑，影响着神经可塑性。

But that means I have more cells, but they're more specified. They're giving me more sensitivity. They're giving me more data that's differentiated. And that's what my brain needs, and that's what my brain's responding to. And so when we think about that, my practice as a musician versus my practice playing video games, all of these things influence our brain and influence our plasticity.

最让我着迷的是：每次接触科技产品时，它都在重塑我们的大脑。我们的环境不仅塑造着我们，环境本身也在剧变。通过人们的听觉阈值，我甚至能推测出他们居住的城市。

Now, where things get kind of interesting to me and sort of my obsession on that side is every time we engage with a technology, it's going to shape our brain. Right? It's both, you know, our environments, but our environments are changing. Those are shaping who we are. You know, I think you can look at people's hearing thresholds and predict what city they live in.

完全正确。确实如此。

Then absolutely. You'll Yes.

能简单解释下这个现象吗？比如我几年前去芝加哥时——很美的城市，美食也令人惊艳。

Can you just briefly explain explain that would be? I mean, I was visiting the city of Chicago a couple years ago. Beautiful city. Yeah. Amazing food.

喜欢这里的人们。城市非常喧嚣。

Love the people. Very loud city.

嗯。

Mhmm.

市中心街道宽阔。与我习惯的环境相比树木不算多。我当时就想，哇，这里真的吵得厉害。我在郊区长大，后来一有机会就赶紧搬走了。

Wide downtown streets. Not a ton of trees compared to what I'm used to. And I was like, wow, it's really loud here. And I grew up in the suburbs. Got out as quickly as I could.

是啊。我不喜欢郊区。抱歉了，郊区居民们，那不适合我。我热爱荒野，也喜欢城市。

Yeah. Don't like the suburbs. Sorry. Suburb dwellers, not for me. I like the wilderness, and I like cities.

但你是说真的能仅凭人们的成长地或现居地，就预测出他们对响度的听觉阈值？

But you're telling me that you can actually predict people's hearing thresholds for loudness simply based on where they were raised or where they currently live?

某种程度上，两者皆有影响。对吧？因为城市有特定的声学印记——各类噪音。那些喧嚣城市中的声响，还包括制造这些噪音的源头，对吧？这些往往是独特的，比如交通工具类型、人口密度甚至建筑结构都会影响。

In part, it can be both. Right? Because cities have sonic imprints types of noise. Things that are very loud cities, but also what's creating that noise, right? That's often unique, the inputs, the types of vehicles, the types of density of people even the construction in those environments.

这正在改变现有的噪音环境，进而塑造人们的听觉阈值。在最基础的层面，它也在塑造人们的敏感度。如果你习惯了环境中某些动物的叫声，当它们出现时，你会对其产生特定的警觉反应，从而发展出更高的敏感度。反之若异常罕见，比如我突然听到鸡叫声...

It is changing what noise exists. That's shaping people's hearing thresholds. At the lowest level, it's also shaping their sensitivities. If you're used to hearing certain animals in your environment and they come with, you know, you should be heightened to a certain response in that, you're going to develop increased sensitivity to that. Whereas if it's really abnormal, you know, I hear chickens.

我有个邻居在城里养鸡。

I have a neighbor who has chickens in the city.

还养公鸡吗？

Roosters too?

对，对，没错。

Yes. Yes. K.

我小时候住的地方附近有只公鸡。我听过公鸡打鸣。那些声音深深烙印在我脑海里。

I grew up near a rooster. I hear that rooster. Yeah. Those those sounds are embedded deeply in my mind.

这涉及语义语境，还有某种频谱对吧？我说的频谱强度及其含义——所谓频谱是指不同频率的振幅及其波形特征。

There's the semantic context and then just the sort of spectrum. Right? And the intensity of that spectrum and meaning when I say spectrum, mean the different frequency amplitudes and and what that shaping's like.

高音调，低音调。嗯。

High pitch, low pitch. Yeah.

是的。这会直接影响你的神经系统变化，哪怕是最基础的听觉层面——耳朵、大脑、耳蜗接收到的信息。但更深层来说，这关乎潜在的噪音伤害和暴露程度。更高层的大脑区域还会对特定频率进行放大处理，让你意识到所处环境中哪些频率更重要。说起来挺有意思的...

Yeah. And that affects how your neural system is changing, even at the lowest level of what your ears, your brain, your cochlea is getting exposed to. But then also where So that would be the lower level, what sort of noise damage might exist, what exposures. But then also, then there's the amplification of coming from your higher level areas that are helping you know that these frequencies that are more important in your context, in your environment. There's a a funny like, this is kinda funny.

我记得有部电影叫《寂静之声》，开篇我就很喜欢彼得·萨斯加德。他是其中的演员之一。这部电影本意是想带点奇幻色彩。'奇幻'这个词对吗？用这个词准确吗？

There was a film called, I think, it's The Sound of Silence, and it start I I love Peter Sarsgaard. He was one of the the actors in it. And it was sort of meant to be a bit fantastical. Is that a word? Is that the right word?

但实际上，制片人跟我聊了很多，试图通过我来塑造主角的行为方式。因为我拥有绝对音感，他们想在电影中模仿某些特质。最终这个角色成了为人们调音生活的人——他会走进别人的生活空间，然后说'哦，你工作不顺或感情出问题，是因为你生活中存在这个三全音程'，或者'你家的热水器发出这个音高，而烧水壶又是那个音调'。

But in fact, to me so the filmmakers had talked to me a lot, as had to and inform this sort of main character in the way he behaved. Because I have absolute pitch, and there were certain things that they were trying to emulate in this film. He ends up being this person who tunes people's lives. He'll walk into their environments and be like, Oh, things are going badly at work or your relationship's because you're you're you know, you've got this tritone. You're or, you know, your your water heater is making this pitch, and your teapot is at this point.

哦，明白了

Oh, got this

在洛杉矶肯定很吃香。洛杉矶人会愿意花大价钱买这种服务。

to go over so well in LA. People would pay millions of dollars in Los Angeles.

简直太滑稽了。

It's totally funny.

你真的会给人做这种调音吗？

Do you do this for people?

不。好吧好吧。不过我告诉你，我住酒店时只要听到异响就会立刻换房间。这就是我——

No. Okay. Okay. But I will tell you, I will walk into hotel rooms, immediately if I hear something, I've moved. So that is I-

因为你拥有完美音高。你能定义一下完美音高吗？这是否意味着你总能精准地用嗓音唱出某个音符？

Because you have perfect pitch. Could you define perfect pitch? Does that mean that you can always hit a note perfectly with your voice?

其实不存在完美音高这回事，只有绝对音高。我认为这只是因为，比如说，啊，那个A音等于440赫兹对吧？但这是我们现代使用的标准。

There is no such thing as perfect pitch. There's absolute pitch. And so, I think only because the idea of so, like, ah, that would be a equal four forty hertz. Right? But that's a standard that we use in modern time.

而且你知道，A音的定义实际上随着我们的审美变迁、人们的喜好变化、以及音乐制作工具的发展而改变。巴洛克时期A音是415赫兹。现在...

And the, you know, different what a is has actually changed throughout our lives with aesthetic, with what people liked, with the tools we used to create music. And in the Baroque era, A was four fifteen hertz. Now Can

你能唱出来吗？太棒了。还有

you hit that? Awesome. And

无论如何，这就是为什么称之为绝对音高——因为随着基底膜随着年龄变硬，或者我的时间处理能力下降，我的大脑仍会认为我唱的是440赫兹，但实际可能并非如此。

in any case, so that's why it's absolute because, you know, guess what? As my basilar membrane gets more rigid as I might age or my temporal processing slows down, my brain's going to still think I'm in, you know, I'm singing 440 hertz, but it might not be.

基底膜是内耳中将声波转化为电信号的部分对吧？是的。好吧，有道理。

It's Basilar membrane is a portion of the internal ear that converts sound waves into electrical signals. Right? Yeah. Okay. Fair enough.

我正在和一位听觉机械生理学专家交谈。没错，我教授听觉生理学，但我想确认下，毕竟对面坐着专家。我们稍事休息，感谢赞助商大卫的支持。

Well I'm talking to an auditory Mechanically. Physiology. Rehearsals that Yeah. I teach auditory physiology, but I want to just make sure because I'm sitting across from an expert. I'd like to take a quick break and acknowledge one of our sponsors, David.

大卫制作的蛋白棒与众不同。它含有28克蛋白质，仅150卡路里且零糖分。没错，28克蛋白质中有75卡路里来自蛋白质，这比市面上其他蛋白棒高出50%。大卫蛋白棒的口感也令人惊艳。

David makes a protein bar unlike any other. It has 28 grams of protein, only 150 calories and zero grams of sugar. That's right, 28 grams of protein and 75 of its calories come from protein. This is 50% higher than the next closest protein bar. David protein bars also tastes amazing.

甚至连质地都无可挑剔。我最爱的是巧克力曲奇面团口味，不过新出的巧克力花生酱和巧克力布朗尼风味我也很喜欢。基本上所有口味我都非常中意，它们都美味得难以置信。实际上最大的挑战是决定每天吃哪种口味、吃多少次。

Even the texture is amazing. My favorite bar is the chocolate chip cookie dough, but then again, I also like the new chocolate peanut butter flavor and the chocolate brownie flavor. Basically, I like all the flavors a lot. They're all incredibly delicious. In fact, the toughest challenge is knowing which ones to eat on which days and how many times per day.

我限制自己每天只吃两根，但对它们的热爱无可救药。大卫让我能在零食级的热量中获取28克蛋白质，轻松达成每日每磅体重1克蛋白质的目标，且无需摄入过多卡路里。我常在下午把它当点心，出门旅行也必随身携带——仅150卡路里就能带来28克蛋白质的极致满足感。

I limit myself to two per day, but I absolutely love them. With David, I'm able to get 28 grams of protein in the calories of a snack, which makes it easy to hit my protein goals of one gram of protein per pound of body weight per day. And it allows me to do so without ingesting too many calories. I'll eat a David protein bar most afternoons as a snack, and I always keep one with me when I'm out of the house or traveling. They're incredibly delicious, and given that they have 28 grams of protein, they're really satisfying for having just 150 calories.

若想尝试大卫蛋白棒，请访问davidprotein.com/huberman（再次强调：davidprotein.com/huberman）。本期节目也由Helix Sleep赞助。Helix Sleep提供根据个人睡眠需求定制的床垫和枕头。我曾在多个播客中强调：优质睡眠是身心健康与高效表现的基础。

If you'd like to try David, you can go to davidprotein.com/huberman. Again, that's davidprotein.com/huberman. Today's episode is also brought to us by Helix Sleep. Helix Sleep makes mattresses and pillows that are customized to your unique sleep needs. 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.

床垫的软硬程度直接影响每夜睡眠质量，必须与个人睡眠特点相匹配。在Helix官网完成两分钟测试，回答诸如'你习惯仰卧、侧卧还是俯卧？''夜间容易发热或发冷？'等问题——无论你是否清楚这些答案，Helix都能为你匹配理想床垫。

Now the mattress you sleep on makes a huge difference in the quality of sleep that you get each night, how soft it is or how firm it is, all play into your comfort and need to be tailored to your unique sleep needs. If you go to the Helix website, you can take a brief two minute quiz and it will ask you questions such as do you sleep on your back, your side, or your stomach? Do you tend to run hot or cold during the night? Things of that sort. Maybe you know the answers to those questions, maybe you don't.

对我来说，最终匹配的是DUSK床垫。使用三年半以来，这是我体验过最优质的睡眠。访问helixsleep.com/huberman参与测试，Helix将为你定制专属床垫。现在订购可享最高27%优惠。

Either way, Helix will match you to the ideal mattress for you. For me, that turned out to be the DUSK mattress. 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. If you'd like to try Helix Sleep, you can go to helixsleep.com/huberman, take that two minute sleep quiz, and Helix will match you to a mattress that's customized to you. Right now Helix is giving up to 27% off all mattress orders.

重申优惠链接：helixsleep.com/huberman，最高27%折扣。好的。所以说我们的大脑是根据个人经历定制的——尤其是童年经历，但成年经历同样重要。

Again, that's helixsleep.com/huberman to get up to 27% off. Okay. So our brains are customized to our experience. Yep. Especially our childhood experience, but also our adult experience.

是的。你提到了小人模型，这个身体表面的表征。你还说了一些让我必须追问的事情，就是这位假设中的斯坦福学生——其实可以是任何地方的学生——说，如今我们花很多时间用拇指打字，一边用拇指打字一边思考和表达情感。对吧？我是说，当我们用拇指发短信时，有时是在进行情感交流。

Yes. You mentioned the homunculus, this representation of the body surface. And you said something that I just have to pick up on and ask some questions about, which is that this hypothetical Stanford student, could be any student anywhere, says, Nowadays, we spend a lot of time writing with our thumbs and thinking as we write with our thumbs and emoting. Right? I mean, when we text with our thumbs, we're sometimes involved in an emotional exchange.

对。我的问题是这样的。过去十五年左右代表了新技术融合的空前时期。对吧？我指的是智能手机。

Yeah. My question is this. The last fifteen years or so have represented an unprecedented time of new technology integration. Right? I mean, the smartphone.

嗯。

Mhmm.

发短信。当我发短信时，我意识到自己脑海里会听到一个声音，那是我自己的声音，因为如果我在往外发短信，就是在发送信息。但如果我认识给我发短信的人，我也会在内心听到他们的声音。

Texting. And when I text, I realized that I'm hearing a voice in my head as I text, which is my voice, because if I'm texting outward, I'm sending a text. But then I'm also internalizing the voice of the person writing to me if I know them.

嗯。

Mhmm.

但这是经过我大脑过滤后的声音。对吧？所以我不是为了微观分析而微观分析，但我们通过短信进行的对话，其实都发生在自己脑海里。不过参与者有两个或更多——群发短信现在考虑起来太复杂了。但这种转变的本质是什么？

But it's coming through filtered by my brain. Right? So it's like I'm not trying to microdissect something here for the sake of microdissection, but the conversation that we have by text, it's all happening in our own head. But there are two or more players, group text was too complicated to even consider right now. But what is that transformation really about?

以前，我会给你写封信。我会寄信给你。我会写封电子邮件发给你。所以整个过程其实被放慢了。

Previously, I would write you a letter. I would send you a letter. I'd write you an email. I'd send you an email. And so the process was really slowed.

现在你可以与某人进行非常快速的对话，一来一往，对吧？有些人打字快，发邮件快，但都比不上发短信的速度，对吗？我甚至能知道你在思考，因为会出现‘正在输入’的提示，对吧？那么，有没有可能我们现在已经将整个‘小矮人’区域或大脑皮层的其他区域分配给了对话功能，而在2010年之前，大脑根本不曾参与任何形式的对话？

Now you can be in a conversation with somebody that's really fast, back and forth. Right? Some people can type fast, can email fast, but nothing like what you can do with text, right? I can even know when you're thinking because it's dot, dot, dot, or you're writing, right? And so is it possible that we've now allocated an entire region of the homunculus or of some other region of cortex brain to conversation that prior to 2010 or so, the brain just was not involved in conversations of any sort.

换句话说，我们现在实现了拇指书写与听觉的整合——这是全新的。我们能听到自己的声音，想象对方的声音，并以极快的速度完成这一切。我们是在讨论一个新的大脑区域，还是在利用旧有脑区，试图在维恩图中寻找并推动重叠部分？因为我记得这一切发生得非常迅速且无缝。我记得短信刚出现时，感觉有点慢，有点笨拙。

In other words, we now have the integration of writing with thumbs, that's new. Hearing our own voice, hearing the hypothetical voice of the other person at the other end, and doing that all at rapid speed. Are we talking about like a new brain area, or are we talking about using old brain areas and just trying to find and push the overlap in the Venn diagram? Because I remember all of this happening very quickly and very seamlessly. I remember like texting showed up, and it was like, alright, well, it's a little slow, a little clunky.

很快它就有了自动填充功能。很快它就开始学习我们的习惯。现在我们还能语音识别。而且人们掌握这些技能非常快。所以问题是：我们是在用旧有脑区以新方式组合它们吗？

Pretty soon it was autofill. Pretty soon it was learning us. Now we can do voice recognition. And it's, know, people pick this up very fast. So the question is, are we taking old brain areas and combining them in new ways?

还是说，我们实际上正在从根本上改变大脑的工作方式，以实现如今看似微不足道，却如同发短信般基础的生活行为？我们的大脑中究竟发生了什么？

Or is it possible that we're actually changing the way that our brain works fundamentally in order to be able to carry out something as what seems to be nowadays trivial, but as basic to everyday life as texting? What's going on in our brain?

我们并非在开发新资源。我们拥有的是相同的细胞——当然，神经发生确实存在。但关键在于这些细胞如何分配。关于之前提到的小矮人，我快速补充一点：小矮人是大脑中映射图的范例，一种皮层映射。

Aren't developing new resources. We've got the same cells that are Or, I mean, there's neurogenesis, of course. But it's how those are getting allocated. Just One quick comment from what we said before when we talk about the homunculus. The homunculus is an example of a map in the brain, a cortical map.

映射在大脑中至关重要，因为它们让需要互动的细胞能提供特异性，使我们反应迅速、精准，因为相关细胞距离更近。同时，这些细胞的响应具有高度可塑性，可能取决于我们的输入。所以小矮人可能是一种映射，但我们大脑中遍布各种映射图，且这些映射图之间存在大量交叉输入。你讨论的是：是否存在某些区域，过去我们未将其分配用于区分处理特定细胞功能，而现在这些区域与我大脑解读短信的不同方式密切相关？

Maps are important in the brain because they allow cells that need to interact to give us specificity, to make us fast, to have tight reaction times and things because you've shorter distance and things that belong together. Also, there's a lot of motility in terms of what those cells respond to, potentially dependent on our input. So the homunculus might be one map, but there are maps all over our brain. And those maps still have a lot of cross input. So, what you're talking about is, are you having areas where we didn't use to allocate and differentiate in, you know, the specificity of what those cells were doing that are now quite related to the different ways my brain is having to interpret a text message.

这种微妙差异与细节处理，如今我确实变得更熟练了。我的反应速度更快，解读速度也更快。那么，我是否正在重新分配原本执行其他功能的细胞来实现这一点？很可能。

And the subtlety and the nuance of that, that actually now I'm I get faster at. I have faster reaction times. I also have faster interpretations. So am I allocating cells that used to do something else to allow me to have it? Probably.

但我也在构建这样一种认知——把我看作一个多感官综合体，需要整合视觉、听觉、嗅觉信息来形成完整的对象体验。这种整合与模式匹配现在也发生在我们的新型沟通方式中，这是前所未有的。这意味着什么？意味着更高的可重复性、更快的模式匹配、更强的整合能力，这些都让我们能以更快的速度前进。

But I'm also building, you know, where think about me as a multisensory object that has I have to integrate information across sight, sound, smell to form a holistic object experience. That same sort of integration and pattern is happening now when we communicate in ways that it didn't used to. So what does that mean? It means there's a lot more repeatability, a lot faster pattern matching, a lot more integration that is allowing us to go faster.

我完全同意。我觉得有整整一代人是伴随着智能手机长大的，对他们来说这已是生活的一部分。在这个领域里，我听过最具冲击力的一句话是：有天晚上我在圣克拉拉大学给学生做讲座，谈到收起手机能让注意力更集中，远离智能手机会让生活更美好之类的内容。结束后有个二十出头的年轻人走过来对我说：'你根本不明白。'

I completely agree. I feel like there's an entire generation of people who grew up with smartphones for which it's just part of life. I think one of the most impactful statements I ever heard in this kind of general domain was, I gave a talk down at Santa Clara University one evening to some students. And I made a comment about putting the phone away and how much easier it is to focus when you put the phone away and how much better life is when you take space from your smartphone and all of this kind of thing. And afterwards, this young guy came up to me, he's probably in his early 20s, and he said, listen, you don't get it at all.

我问什么意思，他说：'你们是在大脑发育成熟后才接触这项技术的。'他代表自己发声说：'当手机没电时，我感觉生命力从身体里流失，这种痛苦几乎难以忍受，直到手机重新开机。'

I said, what do you mean? He said, you adopted this technology into your life and after your brain had developed. He said when he's speaking for himself. He said, when my phone runs out of charge, I feel the life drain out of my body. And it is unbearable or nearly unbearable until that phone pops back on.

'然后我才感觉生命力回归身体，因为又能和朋友联系了。我不再感到孤独，不再觉得与世隔绝。'这番话让我震撼至今，因为我意识到正如他所言，他的大脑在社交情境、沟通方式、安全感等方面确实与我有本质不同。

And then I feel life return to my body, and it's because I can communicate with my friends again. I don't feel alone. I don't feel cut off from the rest of the world. And I was thinking to myself, wow. Like, his statements really stuck with me because I realized that his brain, as he was pointing out, is indeed fundamentally different than mine in terms of social context, communication, feelings of safety, and on and on.

而且他绝非个例。对某些人来说可能没那么极端，但对多数人而言，在迫切等待回复的重要对话中看到'正在输入...'的提示，确实是种非常强烈的情感体验。

And I don't think he's alone. I think for some people, it might not be quite as extreme. But for many of us, to see that dot dot dot in the midst of a conversation where we really want the answer to something, or it's an emotionally charged conversation can be a very intense human experience.

这很有趣。

That's interesting.

所以我们加速了彼此间的信息传递，但即使是琐事——不必是争吵或'是癌症晚期还是良性肿瘤'这种极端情况，对吧？'他们还活着吗？找到了吗？'这类信息也同样如此。

So, we've sped up the that we transfer information between one another. But even about trivial things, it doesn't have to be an argument or a like, is it stage four cancer or is it benign, right? Those are extreme conditions, right? Are they alive or are they dead? Did they find him or her or did they not?

这些都是极端案例，但日常生活中也存在类似情况。我注意到，比如有时我会去海岸边或大苏尔地区，刻意远离手机。通常需要一两个小时甚至半天时间，才能真正融入当地环境，不再期待通过智能手机获取外界刺激。而且我认为在这方面我并不特殊。所以问题在于，你认为科技对大脑的影响是积极、消极、中性，还是持不可知论态度？

Those are extreme cases, but there's just the everyday life of, and I noticed this, like if I go up the coast sometimes or I'll go to Big Sur and I will intentionally have time away from my phone. It takes about an hour or two or maybe even a half day to really drop into the local environment where you're not looking for stimulation coming in through the smartphone. And I don't think I'm unusual in that regard either. So I guess the question is, do you think that the technology is good, bad, neutral, or are you agnostic as to how the technologies are shaping our brain?

这个问题涉及多个维度。关于智能手机和音频领域，我想特别指出：过去二三十年间（或许更久些），压缩算法的巨大进步让我们能够随身携带毕生的音乐和内容资源——比如MP3这类高效感知压缩算法（有损感知算法），以及我在杜比等公司的工作经历。但内容压缩算法的本质目标，是通过智能方式去除大量信息的同时，完整传递体验和信号的精髓。观察年轻一代用缩写和简写交流时，即便只是发个'LOL'，其实也承载着丰富的沟通内涵。

It goes in lots of different directions. One thing I did wanna say, though, with smartphones specifically and sort of everything, in audio, our ability to carry our lifetime of music and content with us has been because of, you know, huge advances in the last twenty five, thirty years, and maybe maybe slightly more, around compression algorithms that have enabled us to have really effective what we call perceptual compression, lossy perceptual algorithms, and things like MP3 and my past work with companies like Dolby. But whenever you're talking about what's the goal of content compression algorithms, it's to translate the entirety of the experience, the entirety of a signal with a lot of the information removed, right? But in intelligent ways. When you look at the way someone is communicating with acronyms and the shorthand that the next generations use to communicate, it is such a rich communication, even though they might just say LOL.

这本质上是一种能触发强烈认知体验的有损压缩，对吧？

It's actually a lossy compression that's triggering a huge cognitive experience. Right?

能否为不熟悉术语的听众解释下什么是有损压缩？

Can you explain lossy for people who might not be familiar with it?

有损意味着信息在编解码过程中会丢失部分内容，但理想状态下这些丢失不会影响感知体验。比如处理歌曲文件时，若每隔500毫秒删除片段（虽然会严重失真），或者采用更智能的方式——早期MP3模型其实就是对人脑的数学模拟。

Lossy means that in your encoding and decoding of that information, there is actually information that's lost when you decode it. But hopefully, that information is not impacting the perceptual experience. Imagine I have a song and I want to represent that song. I could take out to make my file smaller, I could take out every other, every five hundred milliseconds of that, and it would sound really horrible, right? Or I could be a lot more intelligent, and instead, basically, if you look at early models like MP3, they're kind of like computational models of the brain.

这些模型可能止步于听觉神经层面，但本质上在模拟人脑处理声音的机制：哪些能被听见，哪些会被遮蔽。当两个声音同时出现时，算法会判断只需编码主导声音即可，次要声音无需占用比特位。

They stop you know, they might stop at, the auditory nerve, but they're trying to put a model of how our brain would deal with sound. What we would hear, what we wouldn't. This sounds present and and it's present at the same time as this sound, then this sound wouldn't be heard, but this sound would be. So we don't need to spend any of our bits coding this sound. Instead, we just need to code this one.

因此这种算法能智能决定哪些信息需要保留，从而用最少数据量还原最佳感知体验——即我们最终接收到的效果。这也解释了为什么我在教授'如何用最小信息量呈现丰富体验'时总会强调：关键在于理解感知的本质。

And so it becomes an intelligent way for the model and the algorithm of deciding what information needs to be represented and what doesn't to create the same, you know, the best perceptual experience, which perceptual meaning what we get to take home. I think one of the things that's important then, why I think whenever I used to have to teach some of what it means to represent a rich experience with minimal data, you think with minimal information,

仅仅因为你有一个10岁的女儿？是不是用缩写交流对你来说像密码一样难懂？

Just because you have a 10 year old daughter? Does have communication by acronym that to you is cryptic?

有时候是。但我得自己琢磨明白。不过没错。但重点是，这就是一个有损压缩算法的例子，实际上它承载着更丰富的感知体验，对吧？虽然常需要上下文，但本质上是用少量信息位来试图表达更复杂的情感和状态，对吗？

Sometimes. But I have to figure it out then. But yes. But the point is, that is an example of a lossy compression algorithm that actually has a much richer perceptual experience, right? And it often needs context, but it's still, you know, you're using few bits of information to try to represent a much richer feeling in a much richer state, right?

而且观察不同人群会发现，他们的生理体验差异很大，这取决于他们成长过程中接触这类语境的经历。

And if you look at different people, they're going to have, you know, bigger physiological experience dependent on, you know, how how they've grown up with that kind of context.

听起来确实如此。我不想过度解读，但你似乎看到了数据压缩的巨大潜力。就拿短信缩写来说，相比三十年前人们直接对话的方式，这是种极致的数据压缩。虽然传输的数据量减少了，但体验的丰富程度却丝毫不减，甚至更胜一筹，你是这个意思吧？

It sounds to me Yeah. I I don't want to project here, but it sounds to me like you see the great opportunity of data compression. Like, let's just stay with the use of acronyms in texting. That's a vast data compression compared to the kind of speech and direct exchange that people engaged in thirty years ago. So there's less data being exchanged, but the experience is just as rich, if not more rich, is what you're saying.

这让我觉得你认为这种现象总体上是中立偏积极的。

Which implies to me that you look at it as generally neutral to benevolent.

对，这是好事。只是方式不同而已。

Like, it's good. Yeah, it's just different.

我再过两个月就50岁了。不像有些人总说'我们年轻时会给恋人写信'，比如亲手写生日贺卡，或者面对面交谈。而现在的年轻一代只会敷衍地说'随便啦'。

I'm coming up on 50 in a couple months. And as opposed to somebody saying, Well, you know, when I was younger, we'd write our boyfriend or girlfriend a letter. You know, I would actually write out a birthday card. I would go, you'd have a face to face conversation. And you've got this younger generation that are saying, yeah, whatever.

这就像我们曾听说过的，我过去常在雪地里跋涉上学那种事。如今我们有带暖气的校车，还有无人驾驶汽车。所以我认为，让所有年龄段的人了解到，即使某些数据或交流元素被完全剔除，体验的丰富性仍能得以保留，这是重要且有益的。

This is like what we heard about, I used to trudge to school in the snow kind of thing. Like, well, we have heated school buses now, and we've got driverless cars. So I think this is important and useful for people of all ages to hear that the richness of an experience can be maintained, even though that there are data, or some elements of the exchange are being completely removed.

完全正确，但这种保留是基于那些个体建立的神经连接，对吧？是那一代人的。

Absolutely, but it's maintained because of the neural connections that are built in those individuals, right? And that generation.

我常思考，神经系统喜欢沿着连续体编码，就像'喜欢'、'讨厌'或'一般'。你觉得技术是中性的吗？比如，你会失去一些东西，也会获得一些。还是你认为这很糟糕？如今我们听到很多对AI的恐惧。

I always think of, okay, and the nervous system likes to code along a continuum, but like, yum, yuck, or meh. Like, do you think that a technology is kind of neutral? Like, yeah, you lose some things, you gain some things. Or you think like, this is bad. These days we hear a lot of AI fear.

我们会讨论这个。也有人对AI和智能手机能做的事超级兴奋。比如我姐姐和她女儿就爱用智能手机，因为能远程沟通，带来安全感，快速交流更方便。

We'll talk about that. Or you hear also people who are super excited about what AI can do, what smartphones can do. I mean, some people, like my sister and her daughter, love smartphones because they can communicate. It gives a feeling of safety at a distance. Like quick communications are easier.

静下心来写信很难。她马上要上大学了。问题是，你们会保持多频繁的联系？这提高了对联系频率的期待，但降低了接触深度。因为你可以发条'嘿，今早想起你了'。

It's hard to sit down and write a letter. She's going off to college soon. So the question is like, how often will you be in touch? It raises expectations about frequency, but it reduces of contact, but it reduces expectations of depth. Because you can do like a, Hey, I was thinking about you this morning.

这样可能感觉挺够分量。但若我大学时寄封信回家，写'嘿，今早想起你了。爱你的安德鲁'，收信人大概会懵——不知道这算什么。

And that can feel like a lot. But a letter, if I sent a letter home, you know, during college, my own like, hey, I was thinking about you this morning. Love, Andrew. I'd be like, okay. Like, I don't know how that would be.

他们可能会想：'这就写完了？'对吧？所以我觉得这是个跷跷板效应。

They'd be like, well, that didn't take long. Right? So I think that there's a it's a seesaw.

你获得了更多通信频率，随之而来的是对它们不同层次的期待。我女儿现在在夏令营，我们被允许在两周内只能写信。

You get more frequency, and then it comes with different levels of expectation on those. My daughter's at camp right now, and we were only allowed to write letters for two weeks.

手写信件。

Handwritten letters.

手写信件。

Handwritten letters.

那是怎么

How did that

进行的？事情是这样的。多年前我的家在一场洪水中被毁，我从洪水中抢救出的少数物品之一，就是这个——我给我兄弟的这些信件，还有我祖先在内战期间的一段通信记录，你知道，就是那种求爱时期的往来信件，都被保存下来了。这些信件可以追溯到1865年。

go It's happening. I mean, I'd lost their home in a flood years ago. And one of the only things I saved out of the flood, which is this and and I just brought these back because I I got them for my brother, is the the there this communication between one of my ancestors, you know, during the civil war, like, were courting, and that was all saved, these letters back and forth between the woman. And, you know, and it's you know, with these it's like 1865.

你还保留着那些信件？

And You have those letters?

是的，我有。来这儿之前它们一直存在我的电脑里。虽然经历了洪水，但这些写在羊皮纸上的信件，墨水并没有晕染开。

I do. I do. I had them in my in my computer back until I flew up here. And but, you know, they were on parchment. And even though they went through a flood, they they, you know, they didn't run.

他们坐着，那是一个截然不同的交流时代。能保存下这些非常美好，因为如果没有那段历史，安妮就无法传达这些。无论如何，我极力主张技术融合。但对我来说，世界就是数据。我确实是这么认为的。

They sit and it's this very different era of communication. And it's wonderful to have that preserved because that doesn't translate, right, through Anne without that history. In any case, I'm a huge advocate for integration of technology. But for me, the world is data. I do think that way.

我观察我女儿的举止时就会想，好吧，我的数据正在输入。她为什么会有那样的反应？我可以举个例子。我们当时在讨论神经可塑性。就像我们是由三类事物构成的生物。

And I look at the way my daughter behaves, I'm like, Okay, well, my data's coming in. And why did she respond that way? There's an example I can give. We were talking about neuroplasticity. It's like we are the creatures of sort of three things.

其一是我们的感官系统及其进化方式，无论是内在噪音损害了我们的感官受体，还是外部压力——在嘈杂环境中，我的大脑能获取的信息量将与听力受损者相当。于是你突然就限制了我能接触到的数据。再者就是我们既有的先验认知。对吧？如果把大脑看作某种贝叶斯模型，对我们来说事物并不像某些生物那样总是确定性的。

One is our sensory systems, how they've evolved, and be it by the intrinsic noise that is degrading our sensory receptors or the external strain My brain is going to have access to about the same amount of information as someone with hearing loss if I'm in a very noisy environment. So suddenly you've compromised the data I have access to. And then also our established priors. Right? Our priors being if you think about the brain as sort of a Bayesian model, things aren't always deterministic for us like they are for some creatures.

我们的大脑必须接收数据并据此做出决策

Our brains having to take data and make decisions about it and

也就是对vaishin（注：疑为

Which is respond to vaishin. We should just explain for Deterministic would be input A leads to output B. Yep. Evasion is, it depends on the statistics of what's happening externally and internally. Yep.

这些都是概率模型。就像A有可能变成B，或A可能驱动B，但也有概率A会驱动C、D或F。

These are probabilistic models. Like there's a likelihood of A becoming B, or there's a likelihood of A driving B, but there's also a probability that A will drive C, D, or F.

完全正确。我们应该深入探讨——让我们在环境中最高效、在世间互动中最出色的能力，正是处理这些概率情境时的速度和效率。那些需要大脑进行概率推断的情况，往往是环境适应能力的绝佳指标。无论是工作环境还是走在街上。我们如何处理这些不单纯指示左右、而是包含海量不同输入的数据。

Absolutely. We should get into, I mean, some of the things that make us the most effective in our environments and just in interacting in the world is how fast and effective we are with dealing with those probabilistic situations. Those things where your brain It's like probabilistic inference is a great indicator of success in an environment. Be it a work environment, be it just walking down the street. And that's how do we deal with this data that doesn't just tell us we have to go right or left, but there's a lot of different inputs.

这是我们在世界中的情境智能。我们可以从多种角度来解析这一点。无论如何，我们都是感官系统、先验知识（即大脑在那一刻之前积累的统计数据和信息，用于权衡行为和决策）以及期望和所处环境的产物，这些因素共同塑造了我们当下的状态。有个有趣的故事：我女儿两岁半时，我们在史密森尼学会的天文馆观看一部典型的穹幕电影。

And it's our sort of situational intelligence in the world. And we can break that down into a lot of different ways. In any case, we are the products of our sensory systems, our priors, which are the statistics and data we've had up until that moment that our brain's using to weigh how it's gonna behave and the decisions it makes, but also then our expectations, the context of that, you know, that have shaped where we are. And so there's this funny story. Like, my daughter, when she was two and a half, were in the planetarium at the Smithsonian, and we're watching, I think, one typical film you might watch in a planetarium.

影片从洛杉矶开始，镜头拉远飞向太阳，途中经过那个经典的NASA地球图像——漆黑寂静的太空中悬浮着蓝星。我女儿突然用尽全力大喊'小黄人！'。我顿时恍然：当然，她对这个图像的认知完全来源于环球影业的片头标志。

We started in LA, zoom out on our way to the sun, and we passed that sort of, quintessential NASA image of the Earth. And it's totally dark and silent. And my daughter, as loud as she possibly could, yells, Minions. And I'm like, Oh, yes, of course. Her experiencefully established prior of that image is coming from the Universal logo.

她根本不知道那写着'Universal'字样。这反应既可爱又合理，却真实展现了人性的本质——面对相同的物理信息，每个人都基于独特经历形成截然不同的认知，我们需要承认这种差异。

And she never you know, that says Universal. I love it. It was totally valid. But it was this very honest and true part of what it is to be human. Like, each of us is experiencing very different having very different experiences of the same physical information, and we need to recognize that.

这种认知差异源于我们的接触经历、先验知识和感官系统，再加上当下的预期，三者共同作用。理解这点后，你才能真正领会技术的影响力。我虽极力推崇技术对人类进步的推动——无论是提升人类能力，还是优化决策数据与洞察力——但有时我们在技术应用上却因小失大。那些提高效率的工具也可能削弱我们的认知能力。比如依赖AI写论文的人，最终可能丧失独立写作能力，甚至影响其知识吸收方式。

But it is driven by our exposures and our priors and our sensory systems. It's sort that trifecta and our expectations of the moment. And once you unpack that, you really start to understand and and appreciate the influence of technology. Now, I am a huge advocate for technology, improving us as humans, but also improving the data we have to make better decisions and the sort of insights that drive us. At the same time, I think sometimes we're penny wise pound foolish with how we use technology, and the quick things that make us faster can also make us dumber and take away our cognitive capabilities And where you'll end up with those that are using the technologies might be to write papers all the time or maybe well, and we can talk about that more, are putting themselves in a place where they are going to be compromised trying to do anything without that technology and also in terms of their learning of that data, that information.

因此，工具的使用方式会造成认知能力的巨大分化——它究竟使你更优秀高效，还是相反？我长期在斯坦福任教，这是我们另一个共同点。

And so you start even ending up with bigger differentiations and cognitive capabilities by whether how you use a tool, a technology tool to make you better or faster or not. One of my sort of things I've always done is teach at Stanford. Thus, we also have that in common.

真该去听听你的课。

I need to sit in on one of your lectures.

我开的课程叫'神经可塑性与电子游戏'。虽然是神经生理学家，但我本质上是技术主义者，痴迷建筑与跨领域创新。虽然课程名称涉及游戏，实则更关注闭环训练环境的强大效力——游戏只是这种环境的典型载体。

Yeah, but my class there is called neuroplasticity and video gaming. And I'm a neurophysiologist, but I'm really a technologist. I like buildings. I like innovation across many domains. And while that class says video gaming, it's really more well, games are powerful in the sense that there's this sort of closed loop environment.

你提供反馈，就能获得关于自己表现的数据，但你可以控制这个过程，知道如何随机化、如何构建。我们这门课的目标是，在理解你所影响的神经回路及训练目标的基础上，开发技术和游戏。我的学生中有音乐家，有计算机科学家，还有斯坦福顶尖运动员。

You give feedback, you get data on your performance, but you get to control that and know what you randomize, how you build. And what our aim is in that class is to build technology and games with an understanding of the neural circuits you're impacting and what you want to train. I'll have students that are musicians. I'll have students that are computer scientists. I'll have students that are some of Sanford's top athletes.

已有不少顶尖运动员修过我的课程。课程始终聚焦于：我想剖析人类表现的某个方面，并以闭环方式真正增强对这类学习的敏感度或可及性。对于不熟悉游戏在神经科学领域作用或历史的人——过去有些很棒的研究，比如比较玩家与非玩家，从自我认同开始。典型玩家实际上具有我们所说的更高敏感度——这是你的专业领域，随时可以反驳我。

I've had a number of their top athletes go through my course. And it's always focused on, Okay, there's some aspect of human performance I want to dissect, and I want to really amplify the sensitivity or the access to that type of learning in a closed loop way. Just for anyone that isn't familiar with the role or the history of gaming in the neuroscience space, You know, there's been some great papers in the past. Take a gamer versus a non gamer, just to start with, someone self identified. A typical gamer actually has what we would call more sensitive and this is your domain, you can counter me on this anytime.

但对比敏感度函数不同。这种函数反映你在视觉场景中识别边缘和差异的能力。懂吗？他们看得更快，对这类差异更敏感。比自称'非游戏玩家'的人强得多。

But contrast sensitivity functions. And like a contrast sensitivity function is your ability to see edges and differentiation in a visual landscape. Okay? They can see faster and, you know, more they're more sensitive to that sort of differentiation. So than someone who says I'm not a video game player or or self identifies that way.

因为他们训练过。比如第一人称射击游戏——我偶尔在街机厅玩过这类。我成长过程中没怎么玩电子游戏。

Because they've trained it. They've it. Like a first person shooter game Yeah. Which I've played occasionally in an arcade or something like that. I didn't play a lot of video games growing up.

现在也不玩。但很多确实基于对比敏感度——绝对要分清是敌是友？该不该开枪？没错。

I don't these days either. But, yeah, a lot of it is based on contrast sensitivity knowing Absolutely. Is that a friend or foe? Are you supposed to shoot them or not? Yeah.

必须极速决策。快到接近反射级别。对，无需思考，但需要快速迭代和决断。

You have to make these decisions very fast. Yeah. Like right on the threshold of what you would call like reflexive. Yes. Like no thinking involved, but it's rapid iteration and decision making.

然后规则会突变。对吧？比如突然需要把其他东西变成目标，把某些元素转化为——

Then the rules will switch. Yeah. Right? Like suddenly, you're you're supposed to turn other other things into targets and other things into into

你说得对，因为当你让一个自称非玩家的人玩上四十小时的《使命召唤》后，他们的对比敏感度就会变得像游戏玩家一样，而且这种改变会持续。一年后再测量，依然如此。四十小时的《使命召唤》不仅改变了我在游戏中的视角，更从根本上转变了我感知世界的方式，让我对情境意识和情境智能有了更高的敏感度。

You're spot on because then you take someone who that self identified non gamer, make them play forty hours of Call of Duty, and now their contrast sensitivity looks like a video game player, and it persists. Go back, measure them a year later. But forty hours of playing Call of Duty, and I see the world differently, not just in my video game. I actually have foundational shifts in how I experience the world that give me greater sensitivity to my situational awareness, my situational intelligence.

在现实生活中。

In real life.

没错。没错。因为这属于底层信息处理能力。我最喜欢研究这类能力的交叉影响。

Yeah. Yeah. Yeah. Because that's a low level processing capability. I love intersecting those when you can.

但更有趣的是——这是Alex Pouget和Daphne Bavelier的杰出研究——不仅是对比敏感度。让我们深入探讨贝叶斯概率决策层面，在非确定性情境中，经过训练的游戏玩家会与非玩家做出相同判断，但速度更快。这种获取信息的优势能力，我认为非常惊人。若能善加利用，将成为强大的工具。

But what's even, I think, more interesting is you also and these were some this was a great study by Alex Pouje and Daphne DeBelleve, where it's not just the contrast sensitivity. Let's go to that next level where we were talking about Bayesian probabilistic decisions where things aren't deterministic. For a video game player, and I can train this, they're going to make the same decisions as a non video game player in those probabilistic inferential situations, but they're going to do it a lot faster. And so that edge, that ability to get access to that information is phenomenal, I think. And and when you can tap into that, that becomes a very powerful thing.

就像玩四十小时《使命召唤》能提升概率推理能力。今年我课程里有几位斯坦福顶尖足球运动员，我们专注于：你缺失哪些数据？如何构建闭环训练环境？通过实时加速度、速度等数据（而非两小时训练后的数据）配合听觉反馈，让他们获得更优的神经通路来提升表现。我们在他们小腿安装传感器实时监测运动数据，进行某种游戏化训练。

So, like, probabilistic inference goes up when I've, you know, played forty hours of Call of Duty. But then what I like to do is take it and say, okay. Here's, you know, a training environment. I had a couple of Stanford's top soccer players in my course this year, and our focus was, Okay, what data do you not have, and how can we build a closed loop environment and make it something so that you're gaining better neurological access to your performance based on data like my acceleration, my velocity, not at the end of my two hour practice, but in real time and getting auditory feedback so that I am actually tapping into more neural training. So we had, sensors, you know, like on on their calves that were measuring acceleration velocity and give able to give us feedback in real time as they were doing, you know, a sort of somewhat gamified training.

我不想用'游戏化'这个词——太泛滥了。但可以说，这是个充满乐趣的环境。嗯。

I I don't wanna use the word gamified. It's so overused. But let's say, it felt like fun. Mhmm. Environment.

这个系统基于加速度数据计算和目标设定，通过不同声音提示帮助他们建立分辨能力。所谓分辨力，特别是对新手而言，往往无法判断加速是否成功。但通过分级反馈的闭环训练，神经表征会逐渐形成更精细的区分。实时听觉反馈构建的闭环环境，能在大脑中建立更高分辨率的表现形式和更强的差异敏感度。

But it's also based on computation of that acceleration data and what their targets were. It's feeding them different sonic cues so that they're building they're building that resolution. When I say resolution, what I mean is, especially as a novice, I can't tell the difference between whether I've accelerated successfully or not. But if you give me more gradation in the feedback that I get with that sort of that closed loop behavior, I start to my my neural representation of that is going to start differentiating more. So with that, that's where the auditory feedback so they're getting that in real time, and we you build that kind of closed loop environment that helps build that you know, create greater resolution in the brain and greater sensitivity to differentiation.

我很想听你分享关于你女儿改进游泳姿势的故事。对吧？因为她现在还不是一名顶尖运动员。也许有一天会是的，但她现在是个游泳选手。对吧？

I'd love for you to share the story about your daughter improving her swimming stroke. Right? Because she's not a d one athlete yet. Maybe she will be someday, but she's a swimmer. Right?

而且

And

在过去，如果你想提高游泳水平，你需要一位游泳教练。如果你想游得非常好，你就得找一位非常优秀的游泳教练，并且要反复与他们合作。你采取了一种略有不同的方法，这确实表明了这项技术潜在的益处和低成本，或者说相对低廉的成本。嗯，

in the past, if you wanted to get better at swimming, you needed a swimming coach. And if you wanted to get really good at swimming, you'd have to find a really good swimming coach, and you'd have to work with them repeatedly. You took a slightly different direction that really points to just how beneficial and inexpensive this technology can potentially be, or relatively inexpensive. Well,

首先，我要说的是。第一点是要有好的游泳教练。好吧。当然。我并不是

first, I'll say this. Number one is having good swimming coaches. Okay. Sure. I'm not

试图让家长们放弃游泳

trying to Parents do away with swimming

那些以数据为中心、真正喜欢构建技术的人有时可能会成为干扰因素，但希望不会。好吧。

who are data centric and really like building technologies are sometimes maybe can be red herring distractions, but hopefully not. Okay.

好的。嗯，是的。

All right. Well, yes.

这是其中之一。

That's one of them.

但让我们先让游泳教练们高兴起来。

But Let's keep the swimming coaches happy.

是的。举个例子，你可以去和精英运动员一起训练。如果你参加很多游泳训练营或培训项目，通常都会涉及到使用摄像头记录你的动作，评估你的泳姿。关键在于，你可以利用这些——我自己就这么做过——了解教练们其实也能上网学习那些对不同泳姿至关重要的技巧。

Yeah. So for example, you go and train with elite athletes. And and if you go to a lot of swimming camps where you're you know, or training programs, it's always about under you know, work with cameras and and, you know, what what they're they're recording you. They're, you know, assessing your strokes. But the point is what I you can use, and I did this, knowing the things that the coaches frankly, can go online and learn some of those things that matter to different strokes.

你可以使用Perplexity Labs、Repla这类工具

You can use Perplexity Labs, use Repla, use some of these

这些是在线资源吗？

These are online resources?

对，没错。而且你能快速搭建一个计算机视觉应用，实时提供关于你泳姿的数据分析。

Yeah. Yeah. And you can build, quickly build a computer vision app that is giving you data analytics on your strokes in real time.

那具体怎么操作？是把手机带下水分析泳姿吗？

So how does that work? You're taking the phone underwater, analyzing the stroke?

在这个案例中，我使用的是手机，所以我正在完成上述所有操作。

In this case, I'm using mobile phones, so I'm doing everything above.

好的，你正在拍摄。如果你能带我们过一遍这个流程。所以你拍摄你女儿自由泳的动作是为了

Okay, you're filming If you could walk us through this. So you film your daughter doing freestyle stroke for

对，或者蛙泳、蝶泳。有很多核心要点你可能需要关注。仰泳和自由泳。而我并不擅长。我们过去常跑步。

Right, or breaststroke, or butterfly. There's a lot of core things that maybe you want to care about. Backstroke and freestyle. And I am not. We used to run.

我知道你是个优秀的跑者。但我是跑步爱好者。我是攀岩者，游泳相对较少。比如身体的滚动幅度或手臂出水高度，你的入水速度是多少——一旦有了数据实际上可以分析得非常精细，对吧？还有你的入水速度是多少？

I know you're a good runner. But I'm a runner. I'm a rock climber, less a swimmer. Things like the roll or how high they're coming above the water, what's your velocity on a you can get actually very sophisticated once you have the data, right? And what's your velocity on entrance?

你的手臂入水时超前头部多少距离？你知道，可能还有些...也许有些你认为显而易见的事情，比如你想知道自己在整个泳池中划水动作和节奏的连贯性。这样你不仅能获取速度数据，还能获得我常说的——你会经常听我用这个词——更高分辨率的数据，以及更多能提供洞察的分析指标。这里重要的是，我10岁的孩子不会...我不会去告诉10岁的女儿需要改变头部入水速度或划水动作，但这些信息至少能让我理解并帮助她了解当前状态，以及她对教练要求的某些动作的完成度。我最欣赏这个创意的地方在于：看，这不仅是为了轻松获取过去需要...（虽然我在很多领域都编程）但现在你不再需要亲自编程就能开发这类应用了。

How far in front of your your head is your arm coming in? How you know, what is maybe there's again, maybe there are things that you you know, are obvious, which is you wanna know, you know, how consistent are your strokes and your cadence across, you know, the pool. So you don't just have your speed, you suddenly have access to what I would call, and and you'll hear me use this a lot, better resolution, but also a lot more analytics that can give you insight. Now, important thing here is, know, my 10 year old is not going to I'm not going to go tell my 10 year old that she needs to change her velocity on this head or stroke, but it gives me information that I can at least understand and help her know how something is going and how consistent she is on certain things that her coaches have told her to do. And what I love about the idea is, look, this isn't just for the ease of getting access to the type of data and information that would previously and I mean, I do code in a lot of areas, but you don't have to do that anymore to build these apps.

事实上，你不应该自己写代码。应该利用AI来开发这类工具。

In fact, you shouldn't. You should leverage AI for development of these types of tools.

你让AI编写代码来分析入水轨迹，如果目标是游得更快，该如何改进。

You tell AI to write a code so that it would analyze trajectory jumping into the pool, how that could be improved if the goal is to swim faster.

你可以利用AI构建一个应用程序来实现这一目标，从而随时获取你所需的任何数据。是的。在这种情况下，你试图进行更精准的划水动作分析，并在训练过程中深入理解相关原理。同样方法也适用于跑步、步态分析，甚至在职场环境中，你可以更全面地识别系统脆弱点和薄弱环节。我认为这类AI加速与工具开发将在两个主要领域产生重大影响。

You'd use AI to build an app that would allow you to do that so that you would have then access to that whatever the data is that you want to do. Yeah. So in that case, you're trying to do better stroke analytics and and understand things as you move forward. You could do the same thing for running, for gait, for you could do you know, in a work environment, you can understand a lot more about where vulnerabilities are, where weaknesses are. There are sort of two different places where I see this type of AI acceleration and tool building really having major impact.

首先是实现数据、分析与信息的民主化——将原本专属于精英阶层的资源开放给真正投入的人群。这对提升表现具有巨大价值，因为这类数据对理解学习过程至关重要。它同样适用于职场环境，帮助你更深入地理解特定流程或技能的成功要素。相比传统方法，你能获得更丰富的分析维度，不仅显著提升成功率，还为你提供了关于'数字孪生'的新思考素材。需要说明的是，我所说的数字孪生，其目的并非完全数字化复制物理系统。

It's on sort of democratizing data, analytics, and information that would normally be reserved for the elite to everyone that's really engaged. And that has a huge impact on improving performance because that kind of data is really useful in understanding learning. It also has applications for when you're in a work environment and you're trying to better understand success in that environment in some process or skill of what you're doing. Can gain different analytics than you otherwise would in ways that become much more successful but also give you new data to think about with regard to what I would call a digital twin. And when I use the word digital twin, the goal of the digital twin is not to digitize and represent a physical system in its entirety.

而是通过整合多源异构数据集（即来自不同系统的可互操作数据）来获取洞见。无论是医院、飞机、我的身体还是鱼缸，这种对物理系统/环境的数字化呈现，能提供持续实时的认知维度——这些认知在传统条件下是难以获得的。

It's to gain, use different interoperable, meaning data sets coming from different sources, to gain insights, you know, digitized data of a physical system or a physical environment or physical world, be it a hospital, be it airplanes, be it my body, be it my fish tank, to give me insights that are, you know, continuous and in real time that I otherwise wouldn't be able to gain access to.

我们早就知道有许多方法可以改善睡眠质量，包括服用特定成分：如苏糖酸镁、茶氨酸、洋甘菊提取物和甘氨酸，以及藏红花、缬草根等相对冷门的成分。这些经过临床验证的原料能帮助入睡、维持睡眠深度，并提升晨间清醒度。我很高兴宣布，我们的长期赞助商AG1最新推出了AGZ夜间饮品，专为优化睡眠与晨间焕活设计。过去几年我全程参与了这款新配方的研发工作。

We've known for a long time that there are things that we can do to improve our sleep. And that includes things that we can take, things like magnesium threonate, theanine, chamomile extract, and glycine, along with lesser known things like saffron and valerian root. These are all clinically supported ingredients that can help you fall asleep, stay asleep, and wake up feeling more refreshed. I'm excited to share that our longtime sponsor AG1 just created a new product called AGZ, a nightly drink designed to help you get better sleep and have you wake up feeling super refreshed. Over the past few years, I've worked with the team at AG1 to help create this new AGZ formula.

它将最佳助眠成分以精准配比融入即饮配方，省去了在庞杂的助眠补充剂市场中筛选合适品类与剂量的烦恼。据我所知，AGZ是目前市面上最全面的睡眠补充剂。我个人习惯在睡前30-60分钟饮用——顺带一提，它的口感非常出色。

It has the best sleep supporting compounds in exactly the right ratios in one easy to drink mix. This removes all the complexity of trying to forge the vast landscape of supplements focused on sleep and figuring out the right dosages and which ones to take for you. AGZ is to my knowledge, the most comprehensive sleep supplement on the market. I take it thirty to sixty minutes before sleep. It's delicious by the way.

它显著提升了我的睡眠质量与深度，这既来自我的主观感受，也得益于睡眠监测数据的佐证。期待大家都能体验这款AGZ新配方，享受优质睡眠带来的益处。AGZ现有巧克力、薄荷巧克力和混合莓果三种口味——正如前所述，每种都令人回味无穷。

And it dramatically increases both the quality and the depth of my sleep. I know that both from my subjective experience of my sleep and because I track my sleep. I'm excited for everyone to try this new AGZ formulation and to enjoy the benefits of better sleep. AGZ is available in chocolate, chocolate mint, and mixed berry flavors. And as I mentioned before, they're all extremely delicious.

三者中我个人偏爱薄荷巧克力，但每种都很出色。若想尝试AGZ，请访问drinkagz.com/huberman获取专属优惠。再次提醒：drinkagz.com/huberman。本期节目也得到Rora赞助，我认为他们生产着市面上最出色的净水设备。

My favorite of the three has to be, I think chocolate mint, but I really like them all. If you'd like to try AGZ, go to drinkagz.com/huberman to get a special offer. Again, that's drinkagz.com/huberman. Today's episode is also brought to us by Rora. Rora makes what I believe are the best water filters on the market.

这是一个令人遗憾的现实，但自来水常常含有对我们的健康产生负面影响的污染物。事实上，环境工作组织2020年的一项研究估计，超过两亿美国人通过饮用自来水接触到PFAS化学物质，也就是所谓的永久化学物质。这些永久化学物质与严重的健康问题相关，如激素紊乱、肠道微生物群紊乱、生育问题以及许多其他健康问题。环境工作组织还显示，超过1.22亿美国人饮用的自来水中含有高水平的致癌化学物质。正是出于所有这些原因，我非常高兴Rora能成为本播客的赞助商。

It's an unfortunate reality, but tap water often contains contaminants that negatively impact our health. In fact, a 2020 study by the Environmental Working Group estimated that more than two hundred million Americans are exposed to PFAS chemicals, also known as forever chemicals through drinking of tap water. These forever chemicals are linked to serious health issues such as hormone disruption, gut microbiome disruption, fertility issues, and many other health problems. The environmental working group has also shown that over one hundred and twenty two million Americans drink tap water with high levels of chemicals known to cause cancer. It's for all these reasons that I'm thrilled to have Rora as a sponsor of this podcast.

Rora生产的我认为是市场上最好的水过滤器。我使用Rora的台面系统已经快一年了。Rora的过滤技术能去除有害物质，包括内分泌干扰物和消毒副产物，同时保留有益的矿物质，如镁和钙。它不需要安装或管道。它由医疗级不锈钢制成，其时尚的设计完美地适合您的台面。

Rora makes what I believe are the best water filters on the market. I've been using the Rora countertop system for almost a year now. Rora's filtration technology removes harmful substances, including endocrine disruptors and disinfection byproducts while preserving beneficial minerals like magnesium and calcium. It requires no installation or plumbing. It's built from medical grade stainless steel and its sleek design fits beautifully on your countertop.

事实上，我认为它是厨房的一个受欢迎的补充。它看起来很棒，水也很好喝。如果您想尝试Aurora，可以访问rora.com/huberman，获得独家折扣。再次强调，那是rora，r0rra.com/huberman。我们肯定会更多地讨论数字孪生，但我听到的是，它可能非常专业，用行话来说，就是领域特定的。

In fact, I consider it a welcome addition to my kitchen. It looks great and the water is delicious. If you'd like to try Aurora, you can go to rora.com/huberman and get an exclusive discount. Again, that's rora, r0rra.com/huberman. We will definitely talk more about digital twins, but what I'm hearing is that it can be very, as nerd speak, but domain specific.

我的意思是，我能想到的最基础的例子，实际上对我非常有用，就是我的冰箱的数字孪生，它会为我需要的东西下订单，而不是我不需要的东西，消除了购物清单的需求。它会跟踪，比如，嘿，你通常在这天和这天用完草莓，它会在后台跟踪，这些东西就会自动送达，就在那里。而且，消除了那种感觉，嗯，去商店不是很好吗？是的。今天早上我走到街角的商店，买了一些农产品。

I mean, like the lowest level example I can think of, which would actually be very useful to me, would be a digital twin of my refrigerator that would place an order for the things that I need, not for the things I don't need, eliminate the need for a shopping list. It would just keep track of like, hey, like, you usually run out of strawberries on this day and this day, and it would just keep track of it in the background, and this stuff would just arrive, and it would just be there. And like eliminate what seemed like, well, isn't going to the store nice? Yeah. This morning I walked to the corner store, bought some produce.

我有时间做那件事，花八分钟去做那件事。但真的，我希望冰箱里装满我喜欢和需要的东西，我可以雇人来做这件事，但那很贵。这可以轻松完成，可能很快就会轻松完成。我甚至不需要在我的手机上构建一个应用程序。是的。

I had the time to do that, the eight minutes to do that. But really, I would like the fridge to be stocked with the things that I like and need, and I could hire someone to do that, but that's expensive. This could be done trivially and probably will be done trivially soon. And I don't necessarily need to even build an app into my phone. Yeah.

所以我喜欢从最基础但高度有用且现在容易获得的技术角度来思考。有几个领域，比如当涉及到学生学习信息时，我们听说过AI，我们普遍认为AI是一个非常糟糕的东西。哦，他们只会用AI来写论文之类的东西。但AI在学习中有用途。我知道这一点，因为我还在学习。

So I like to think in terms of kind of lowest level, but highly useful and easily available now type technologies. There are a couple of areas, like when it comes to students learning information, we've heard AI, we've heard of AI generally as this really bad thing. Oh, they're just gonna use AI to write essays and things like that. But there's a use of AI for learning. I know this because I'm still learning.

我一直在为播客教学和学习，也就是我一直在使用AI从论文中提取大量文本。所以这不是AI幻觉。只是从论文中逐字提取大量文本。

I teach and learn all the time for the podcast, which is I've been using AI to take large volumes of text from papers. So this isn't AI hallucinating. Just take large volumes of text verbatim from papers.

是的。

Yes.

我读过那些论文，真的打印出来、做了笔记等等。然后我一直在用AI为我设计测试，考察论文内容。因为大约八个月前，在研究如何最好地学习和研究的播客时，我发现所有数据都指向一个事实：当我们自我测试时——尤其是远离材料时的自我测试，比如当我们思考‘嗯，皮质醇负反馈循环背后的激素级联是什么？’

I've read those papers, literally printed them out, taken notes, etcetera. And then I've been using AI to design tests for me of what's in those papers. Because I learned about eight months ago when researching a podcast on how to study and learn best, the data all point to the fact that when we self test Yes. Especially when we self test away from the material, like when we're being when we're thinking, oh, yeah. Like, what what is the cascade of hormones driving the cortisol negative feedback loop?

当我需要在散步时思考这个问题——而不是直接查资料，这种自我测试对记忆的影响最大，因为记忆主要是防止遗忘。可以这么理解。所以我一直在让AI为我构建测试，让它问我诸如‘垂体与肾上腺之间驱动皮质醇释放的信号是什么？皮质醇来自肾上腺的哪一层？’之类的问题。我太喜欢这种方式了。

When I have to think about that on a walk Yes. As opposed to just looking it up, it's the self testing that is really most impactful for memory, because most of memory is anti forgetting. This is kind of one way to think about it. So what I've been doing is having AI build tests for me and having asked me questions like, what is the signal between the pituitary and the adrenals that drives the release of cortisol and what layer of the adrenals does cortisol come from? I love that.

因此我确信它提取的信息是准确的，至少基于当前科学和医学的最佳认知。它不断测试我，同时也在学习。这正是AI令人难以置信之处——而我完全不认为自己对AI技术持极端态度。它能识别我记忆的薄弱和强项，因为我会问它：‘我的弱项和强项分别在哪里？’

So I'm sure that the information it's drawing from is accurate, at least to the best of science and medicines knowledge now. And it's just testing me, and it's learning. This is what's so incredible about AI, and I don't consider myself extreme on AI technology at all. It's learning where I'm weak and where I'm strong at remembering things. Because I'm asking it, where am I weak and where am I strong?

它会回答：‘比如命名和这里第三级概念联系需要加强。’我就说：‘那就测试我吧。’然后它就开始针对这些测试我。太神奇了——这项技术能做到这种程度让我震惊。

And they'll say, oh, like naming and this, like third order conceptual links here need a little bit of work. And I go, test me on it. And it starts testing me on it. It's amazing. Like, I'm blown away that the technology can do this.

我并没有用AI开发应用程序什么的，只是用它来帮助我更高效地学习。

And I'm not building apps with AI or anything. I'm just using it to try and learn better.

无论你是在开发应用还是构建工具，你都在将其作为优化认知、发现弱点，同时获得表现反馈并加速学习的工具，对吧？

Whether you're building apps or you're building a tool, you're using it as a tool that's helping you optimize your cognition and find your weaknesses, but also give you feedback on your performance and accelerate your learning in this, right?

嗯，这就是目标。

Well, that's the goal.

但你仍在努力学习。我认为即便在我使用的领域——移动设备与计算机视觉结合中，人工智能也是巨大的机遇与工具。利用摄像头和收集的数据实现更复杂的输入意义重大。但在这两种情况下，你都在塑造认知——用数据丰富你的知识储备。

But you're still putting in the effort to learn. And I think even the ways that I'm using it, computer vision with mobile devices, AI is a huge opportunity and tool. Using the cameras and the data that you've collected to have much more sophisticated input is huge. But in both of those cases, you're shaping cognition. You're using data to enrich what you can know.

人工智能在这些领域简直强大得不可思议，提供了绝佳机会。我个人将其划分为两个类别（或许过于简化）：是否将这个工具——不仅限于AI——用于提升自我？

And AI is just, you know, incredibly powerful and a great opportunity in those spaces. The the place where I think it is and I sort of separate it into literally just two categories. Maybe that's too simplistic. It's am I using and and this is true for any tool, not just AI. But am I using the tool?

我是否通过这项技术变得更睿智、获取更多信息、提高效率，同时增强认知能力并获得新见解？还是仅用它替代原有认知技能来提速？这并非否定后者价值。车载GPS就是完美例证——它通过替代认知工具让我们更高效。坦白说，若在陌生城市失去GPS导航，我们就会手足无措。

Am I using the technology in a way to make me smarter about and let me have more information and make me more effective, but also cognitively more effective, gain different insights? Or am I using it to replace a cognitive skill I've done before to be faster. And it doesn't mean you don't want to do those things. I mean, GPS in our car is a perfect example of a place where we're replacing a cognitive tool to make me faster and more effective. And frankly, you take away your GPS in a city you drive around, and we're not very good.

我记得纸质地图。早期关于海马体的研究正是基于伦敦出租车司机的脑内地图——

I remember paper maps. I remember the early studies of the hippocampus were based on London taxi drivers that had mental maps of the

完全正确。

city. Absolutely.

恕我直言，在GPS普及后，伦敦出租车司机那些脑内地图就不再是必需品了。

That, with all due respect to London taxi drivers up until GPS, those mental maps are not necessary anymore.

不。我是说，他们海马体中有更多的灰质，这一点我们很清楚。而今天再看他们，已经不需要这些了。因为坐在后座的人们拥有更多数据、更多信息，甚至拥有来自天空的视角。卫星数据对我们未来的成功至关重要。

No. And I mean, they had more gray matter in their hippocampus, and we know that. And you look at them today, and they don't have to have that. Because the people in their backseats have more data, have more information, have eyes from the sky. I mean, satellite data is so huge in our success in the future.

而且，你知道，它能预见到局部地区无法察觉的情况。所以这种能力已被取代。但这仍然意味着，当你失去那些数据时，就别指望自己能在没有它的情况下保持对环境的同等空间导航能力。对吧？

And, you know, it it can anticipate the things that locally you can't. And so it's been replaced. But it it still means when you lose that data, you don't don't expect yourself to have the same spatial navigation of that environment without it. Right?

我喜欢你的二分法。要么用它提升认知能力，要么用它加快速度。但你必须明确——我认为关键在于认知层面还是身体层面。

I love your two your two batches. Right? You're either using it to make you cognitively better or you're using it to speed you up. But you have to be, here's where I think Cognitively or physically.

认知层面意味着你仍在努力获取洞察力和数据信息，这些能让我成为更高效的人类。

Cognitively You're or still trying to gain insight and data and information that's making me a more effective human.

没错。我认为包括我在内，人们担忧的是：当我们使用这些省去步骤、加速流程的技术后，却用中性甚至有害的事物填满额外获得的时间或心智空间。就像说'我能从八盎司的饮料中获取全部营养'。

Right. And I think that the place where people are concerned, including myself, is when we use these technologies that eliminate steps, make things faster. Yeah. But we fill in the additional time or mental space with things that are neutral to detrimental. It's sort of like saying, okay, I can get all the nutrients I need from a drink that's eight ounces.

这显然不成立。但问题在于：如何补充剩余热量？是用同样营养的食物保持健康平衡？还是为了摄入热量而吃进一堆虽不增重却有害的物质？

This is not true. But then the question is like, how do I make up the rest of my calories? Right? Am I making up with also nutritious food, right? Let's just say that it keeps me at a neutral health status, or am I eating stuff that, because I need calories that I'm not necessarily gaining weight, but I'm bringing in a bunch of bad stuff with those calories.

所以在这个心智版本中，虽然进程加速了，但人们却用某些让自己变得更蠢的东西填满了空出来的空间。

And so in the mental version of this, things are sped up, but people are filling the space with things that are making them dumber in some cases.

最近MIT有一篇论文，实际上它涉及了我大量时间在谈论和思考的内容，但

There was a recent paper from MIT that I actually It is very much what I spend a lot of my time talking about and thinking about, but

是的，你能描述一下那项研究吗？

Yeah, could you describe that study?

论文的首要结论是，当人们使用LLMs（大型语言模型）撰写论文时，他们的心理过程或认知过程大幅减少，没有相同的知识迁移效果，他们并未真正掌握信息。意料之中吧。所以，

The upshot of the paper first was that people, there's a lot less mental process or cognitive process that goes on for people when they use LLMs to write papers, and they don't have the same transfer, and they don't really learn the information. Surprise, surprise. So,

简单描述一下这项研究，尽管它获得了大量媒体报道，就是让MIT学生用AI写论文。对。对比传统方式，即自己思考并撰写。

just to briefly describe the study, even though it got a lot of popular press, it's, you know, MIT students writing papers using AI Yeah. Versus writing papers the old fashioned way where you think and write.

研究设置了三种不同情境。第一种是仅用大脑撰写论文；第二种是允许使用搜索引擎作为中间选项；再次说明，这些都是粗略分类。

So there were three different categories. People had to write the papers, you know, just with their using their brain only. And that that would be case one. Case two would be I get to use search engines, would be sort of a middle ground. Again, these are, you know, rough categories.

第三种则是使用LLMs完成论文。研究者观察知识迁移类型，通过脑电图（EEG）测量神经反应，分析写作过程中大脑神经活动模式，以及后续对这些信息的掌握程度。这篇论文非常出色，我不想因概括而贬低它。但我觉得论文的重要启示——也是我喜欢讨论的——是我常提及的认知负荷。你可以通过瞳孔直径、姿势等测量人们思考时的认知负荷。

And then a third would be I use LLMs to write my paper. And they're looking at, sort of what kind of transfer happened, kind of they were measuring neural response, so they were using EEG to look at neural patterns across the brain to understand how much neural engagement happened during the writing of the papers and during the whole process, then what they could do with that, what they knew about that information down the road. It's a really nice paper, so I don't want to diminish it in any way by summarizing it. But what I think is a really important upshot of that paper and also just how we talk about it that I liked was I talk a lot about cognitive load always. And you can measure cognitive load in the diameter of your pupil posture and how people are thinking.

这实质上反映了大脑当前解决问题或应对情境的运作强度。作为人类，我们会无意识地通过多种信号暴露自己处于何种认知负荷状态。认知负荷理论解析了大脑在负荷状态下的运作机制，这些负荷可能来自三个方面：内在信息（学习过程中的核心内容）、外在信息（外部干扰）以及关联信息（新旧知识连接）。

It's really how hard is my brain working right now to solve a problem or just in my context. And there are a lot of different cues we give up as humans that tell us when we're under states of different load cognitively and whether we are aware of it or not. And there's something called cognitive load theory that breaks down sort of what happens when our brains are under states of, you know, load. And that load can come from sort of three different places. It might be coming from intrinsic, what you would call intrinsic information, which is what and this is all during learning.

内在认知负荷源于学习材料本身的难度，你知道，有些内容容易掌握，有些则困难得多。这就是内在负荷。外在负荷则来自信息的呈现方式——是否教学不当？

The intrinsic load, cognitive load load would be from, you know, the difficulty of the material I'm trying to understand. How you know, really, some things are easy to learn, some things, you know, are a lot harder. And that's intrinsic load. Extraneous load would be the load that comes from how the information's presented. Is it poorly taught?

是否组织混乱？甚至包括环境因素。比如在嘈杂环境中试图通过听觉学习，就会产生外在认知负荷。明白吗？问题不在于信息本身，而是处理信息时的干扰因素。

Is it poorly organized? Or also even the environment. If I'm trying to learn something auditorily and it's noisy, that's introducing extraneous cognitive load. Right? It's not the information itself, but it's because of everything else happening with that data.

第三类是相关认知负荷。这是大脑用于构建心理图式、整合信息、真正形成对所接收信息的表征时所消耗的负荷。这种相关认知负荷才是真正的学习过程。没有它，就谈不上真正的学习。

And then the third is germane cognitive load. And that's the load that is used in my brain to build mental schemas, to build, to organize that information, to really develop a representation of what that information is that I'm taking in. And that germane cognitive load, that's the work. Right? And if you don't have germane cognitive load, you don't have learning, really.

研究发现，使用大语言模型主要影响的就是相关认知负荷，这其实非常明显。我的意思是...

And what they found is basically the germane cognitive load is what gets impacted most by using LLMs, which is I mean, it's a very obvious thing. Like, that's

意味着你无法充分调动高水平的相关认知

Meaning you don't engage quite as high levels of germane

使用大语言模型时，你并未投入构建认知图式的脑力劳动，无法建立神经图式和对信息的心理表征，导致后期无法有效调用这些信息。这非常关键，因为缺乏这种能力，你未来在该领域的智力发展必然受限。举两个例子：我认识一位医生和一位律师。

cognitive Using LLMs, you're not engaging the mental effort to build cognitive schema, to build neural schemas and sort of the mental representation of the information that you can interact with it later, and you have access to it later. And this is really important because without that, you won't be as intelligent on that topic, that's for sure, down the road. Let me give two examples. I have a doctor. I have a lawyer.

他们都大量使用大语言模型进行搜索或整合信息——医生用于汇总患者数据，律师用于整理案件历史档案。这些领域正在发生类似GPS导航的变革，因为这些工具正被快速采纳。

And both of them use LLMs extensively for searches, say, or for building information. In one case, it's for patient aggregation of patient data. In another case, it's for history of case files. That is the GPS that's happening in those spaces. And because those are the tools that are quickly adopted.

当一个人可能来自不同的世界，以不同的方式学习信息、处理数据、构建知识表征时，他们往往具备更强的外推能力、泛化能力，以及发现潜在规律的能力。纯粹通过大语言模型学习的大脑，虽然能运用现有工具解决相关任务，但在信息丰富度、深度理解、主题泛化和外推方面，无法与采用不同学习方式的人相提并论。这种认知差异是代际性的——并非源于信息不对称，而是即使最终达到相同目标，我们仍要承认其中存在差距。这种差距源自不同的学习路径。

Where you have someone that is maybe came from a different world, has learned that information, has gone and worked with data in a different way, worked their representation of that information, going to be better extrapolation, it's going to be better at generalization, it's going to be better at seeing patterns that would exist. The brain that has done everything through LLMs is going to be in a place where they will get the answer for that relevant task using the tools they have, but you're not the same level of richness and depth of information or generalization or extrapolation for those topics as someone that has learned in a different way. There's a generational difference in understanding, not because they don't have the same information, but there is an acknowledgment that there's a gap even though we're getting to the same place as fast. And that's because of the learning that's happened.

这就是相关认知负荷。

The germane cognitive load.

完全正确。认知负荷的问题。关键在于你必须亲力亲为，大脑必须经历这个过程。安迪，你描述中精彩之处在于——我很欣赏这点——你用它来测试自己、发现弱点。其实在MIT的论文里，这些观点虽然显而易见，但我们确实需要更深入地探讨。

Absolutely. The cognitive load. Like, you've got to do the work. Your brain has to and what was beautiful about your descriptions, Andy, is when you were talking about how you were using it, which I love, to test yourself, find your weaknesses. And actually in the paper in MIT, I again, these are things that are somewhat obvious, but I think we have to talk about them more.

领域能力更强的人使用工具时，仍会保持较高相关认知负荷，但这反而加速了学习进程。在需要快速掌握新领域或高压环境下，最大的风险在于：要么没有投入必要的认知努力，要么未能有效利用AI赋能工具。这些工具本应放大认知收益，却被用来快速交付成果后便弃之不用。

People with higher competency on the topic use the tools in ways that still engage more germane cognitive load but help to accelerate their learning. Where is the biggest vulnerability in a gap? Especially in areas and topics where you're trying to learn a new domain fast, or you're under pressure, and you're not putting in the germane effort, or you're not using the tools that you have access to that AI can enable. You're not using them to amplify your cognitive gain, but instead to deliver something faster, more rapid, and them walking away from it.

我想通过两个平行场景来深入探讨：如何最大化利用AI丰富而非削弱我们的大脑。第一个场景是慢食运动——就像我们从农贸市场精选真正有桃子味的桃子，亲手烹饪出美味佳肴。第二个场景则是网购现成的桃子派，切片即食。

I'm gonna try and present two parallel scenarios in order to go further into this question of how to use AI to our best advantage to enrich our brains as opposed to diminish our brains. So, I could imagine a world, because we already live in it, where there's this notion of slow food. Like you cook your food, you get great ingredients from the farmer's market, like a peach that quote unquote really tastes like a peach, this kind of thing. You make your own food, you cook it, and you taste it, and it's just delicious. I can also imagine a world where you order a peach pie online, it shows up and you take a slice and you eat it.

我们可以观察两代人：比如50岁以上和15岁以下的群体。老一辈会说：'自己做的桃子派不是更好吗？这些桃子多棒啊。'而15到30岁的年轻人可能会回答：'我觉得两者没什么差别，都一样喜欢。'

And you could take two different generations of people, maybe people that are currently now 50 or older and people that are 15 or younger. And the older generation would say, oh, isn't that the peach pie that you made so much better? Like these peaches are amazing. And I could imagine a real scenario where the younger person 15 to 30, let's say, would say like, I don't know, I actually really like the other pie. I like it just as well.

这时老一辈会困惑不解：'这算什么做法？'当然，经验差异确实存在。但从神经科学角度看，很可能两者的味觉体验其实等同，只是基于不同经历产生了主观判断差异。

And the older generation is like, what are you talking about? Like, this is how it's done. What's different? Well, sure, experience is different, etcetera. But from a neural standpoint, from a neuroscience standpoint, it very well could be that it tastes equally good to the two of them, just differs based on their experience.

这意味着这个人没有说谎。并不是说这个孩子对味觉不够敏感，而是他们的神经元已经适应了甜味的定义、甜咸之间的对比，以及桃子应有的味道。因为他们吃过桃子软糖，那味道就像桃子。你懂吗？

Meaning that the person isn't lying. It's not like this kid, you know, isn't as fine tuned to taste. It's that their neurons acclimated to like what sweetness is and what contrast between sweet and saltiness is and what a peach should taste like. Because damn it, they had peach gummies, and that tastes like a peach. You know?

因此我们可以贬低那些我们称之为低层次或感官输入减弱的事物。是的。但这很大程度上取决于那些神经回路最初是如何被塑造的。

And so we can be disparaging of the kind of what we would call the lower level or diminished sensory input. Yeah. But it depends a lot on the neural what those neural circuits were weaned on.

我有几点看法。我特别喜欢桃子派的例子。制作面包也是类似的例子。九十年代时，我认识的每个人高中毕业都会收到一个面包机，方盒子形状的那种，能做出这种——对，就是中间插着根大棍子的面包。

Couple of comments. I love the peach pie example. Making bread is another example of that. And in the nineties, everyone I knew when they graduated from high school got a bread maker that was shaped like a box and, you know, created this Yep. Like, loaf of bread with a giant, you know, rod through it.

这曾是多少年来的标准毕业礼物。但现在你看不到这些了。再看看千禧一代过去五年，尤其是疫情期间，突然之间手工面包和酸面团制作成了潮流。区别在哪里？同样是面包——

And it was just it was the graduation gift for many years. And, you know, you don't see those anymore. And, you know, if you even look at what happened with, like, the millennial generation in the last, you know, in the last five years, especially during the pandemic, suddenly bread making and sourdough, that became a thing. What's the difference? You know, you've got bread.

面包机做的面包是温热的、新鲜的。但比起需要长时间制作、充满触感体验、过程繁琐的手工面包，它完全不受青睐。关键在于对面包的欣赏中，制作过程本身就是体验的一部分。

It's warm. With the bread maker. It's fresh. And it is not at all desired relative to bread that takes a long period of time and is tactile and in the process and the making of it and is clearly much more onerous than the other in its process of development. I think the key part is in the appreciation of the bread, the process is part of it.

这个过程培养着相关知识、投入感和对人类发展本质的联结，同时这种触觉投入、付出的劳动会得到真正的珍视——就像那个桃子派，它承载的不仅是味觉数据，还有嗅觉、触觉、视觉的完整时间序列，让人见证整个演变过程，从而构建出不同的体验预期。我认为这正是人类体验丰富性的组成部分。这会成为人类与AI互动时的丰富性吗？绝对会。与机器人互动呢？

And that process is development of sort of the germane knowledge and the commitment and connection to that humanness of development, but also the tactile commitment, the work that went into it is really appreciated in the same way that that peach pie for one comes with that whole time series of data that wasn't just about my taste, but was also smell, also physical, also visual, and saw the process, you know, evolve and build a different prior going into that experience. And that is, I think, part of richness of human experience. Will it be part of the richness of how humans interact with AI? Absolutely. Or interact with robots?

毫无疑问。关键在于我们正在建立怎样的关系，这些工具——无论是所谓的伴侣还是什么——如何融入我们的存在，将以不同方式塑造我们。我特别看好且期待的是那种能优化我的健康、舒适度和环境意图的机器人，无论是在汽车座舱里，还是在我的房间、我的空间里。

Absolutely. So it's what are the relationships we're building and how are they you know, how integrated are these tools, these, you know, companions, whatever they may be in our existence will shape us in different ways. What I am particularly, I guess, bullish on and excited for is the robot that optimizes my health, my comfort, my intent in my environment, you know, be it in the cabin of a car, be it in my my rooms, my spaces.

那会是什么样子呢？你能给我举个最基础的例子吗？比如，是不是就像一个今天帮你返回湾区时协助旅行的助手？这个非实体机器人到底是什么？

So what would that look like? If you could you give me the lowest level example? Like, like, would it be an assistant that helps you travel today when you head back to the Bay Area? Would What is this nonphysical robot?

我认为我们已经拥有部分这样的技术。当暖通空调系统变得迷人时，就达到了那个临界点，对吧？不是那种意义上的迷人，而是它们确实变得非常有趣，因为它们是...

And I think we already have some of these. It's point where HVAC systems actually get sexy, right? Not sexy in that sense, but they're actually really interesting because they are the heart of

暖通空调系统的核心。

HVAC systems.

在我看来，供暖与通风同理。但想想恒温器——当前AI恒温器根据我的行为进行优化，旨在节省资源与开支，却无法感知我的冷热。如你所言，它不理解我的意图或当下目标，这正涉及你过去研究的诸多课题——它不知道那一刻我的最佳状态应为何。

Heating and ventilation is the same way I see. But you think about a thermostat. A thermostat right now optimizing for an AI thermostat optimizing for my behavior, but it's trying to save me resources, trying to save me money, but it doesn't know if I'm hot or cold. It doesn't know, to your point, my intent, what I'm trying to do at that moment, and this speaks more to a lot of things you've studied in the past. It doesn't know what my optimal state is for my goal in that moment in time.

但坦白说，这很容易实现。它既能与我对话，也能监测我的身体状态。比如凌晨1点我需要赶论文时，房间不该变冷——但对我而言也不该过热。当然，有些人可能需要不同设置。

But it can very easily, frankly. You know, it can talk to me, but it can also know how my state of my body right now and what is going you know, if it's 1AM and I really need to work on a paper, you you know, my house should not get cold, but it also should be very it should for me, it shouldn't. I know. For some people, it should.

没错。我超爱的Eight Sleep智能床垫（对，他们是播客赞助商，但我向所有人推荐），它能自动调节整夜温度。我设定初始值后，它通过动态传感器持续更新——现在每晚我能获得近两小时REM睡眠，这对我简直不可思议，深度睡眠也大幅增加。

Yeah. My my Eight Sleep mattress, which I love, love, love, love and yes, they're a podcast sponsor, but I would use one with anyone. It knows what temperature adjustments need to be made Right. Across the course of the night. I put in what I think is best, but it's updating all the time now, because it has updating sensors, like dynamically updating sensors.

这还只是微观环境。你讨论的是将这种智能整合到整个家居环境中。

I'm getting close to two hours of REM sleep a night, which is outrageously good for me. Much more deep sleep. And that's a low micro environment. You're talking about integrating that into an entire home environment.

家、车辆，没错。因为它需要将我的状态视为动态时间序列来处理。它需要理解所有影响我内在状态的情境——包括家庭或车内等局部环境中驱动我状态的因素，以及外部环境对我状态的影响。

Home, vehicle, yes. Because it needs to treat me as a dynamic time series. It needs to understand the context of everything that's driving my state internally. There's everything that's driving my state in my local environment, meaning my home or my car. And then there's what's driving my state externally from my external environment.

目前这些因素很少被协同考虑以实现优化和动态交互。但我们能够认知这些——通过非接触式传感器，我们可以获取大量关于人类状态的信息。

And we're in a place where those things are rarely treated interacting together for the optimization and the dynamic interactions that happen. But we can know these things. We can know so much about the human state from noncontact sensors.

是的。我们正处于传感器能向AI输送信息的临界点，以实现功能优化。举个基础例子：就像能动态调节温度的智能床垫——通过AI我发现，在夜晚后期提升睡眠环境温度能显著增加REM睡眠，而初期降温则促进深度睡眠。这让我大幅缩短了总睡眠需求，对我而言简直是革命性的改变。

Yeah. And we're right at the point where the sensors can start to feed information to AI to be able to deliver what effectively, again, a lower level example would be like the the cooling the dynamically cooling mattress or dynamically heating mattress. Like, discovered through the AI that my mattress was applying that and I was told that heating your sleep environment toward the end of the night Yes. Increases your REM sleep dramatically, whereas cooling it at the beginning of the night increases your deep sleep. It has been immensely beneficial for me to be able to shorten my total sleep need, which is something that for me is awesome.

因为我虽然很喜欢睡觉，但我不希望需要睡那么久才能保持最佳状态。

Because I I like sleep a lot, but I don't wanna need to sleep so much in order to feel great.

你希望自主掌控睡眠模式。没错，这项技术正在帮你实现这个目标。

Well, you want to have your own choice about how you sleep. Yeah. Given the date, it's helping you have that.

有时我睡六小时，有时八小时。但有个困扰我多年的问题——我一直想找位对技术开发感兴趣的神经营学家探讨：既然我们对睡眠机制如此了解（慢波睡眠、深度睡眠时的生长激素分泌、REM睡眠对记忆巩固和情绪调节的作用），还能通过温度调控、避免咖啡因等手段优化睡眠，AI和药物也在全力改善睡眠质量...

Sometimes I have six hours, sometimes I have eight hours, this kind of thing. Here's where I get stuck. And I've been wanting to have a conversation about this with someone, ideally a neuroscientist, who's interested in building technologies for a very long time. So I feel like this moment is a moment I've been waiting for for a very long time, which is the following. I'm hoping you can solve this for all of We're us, talking about sleep, and we know a lot about sleep.

那么问题来了：我们掌握了所有这些构成'睡眠'的已知状态要素，AI技术和药理学也确实在提升睡眠质量方面做得很好。但如何将这些知识整合成系统性解决方案？这正是我期待与专业人士深入探讨的命题。

You've got slow wave sleep, deep sleep, growth hormone release at the beginning of the night. You have less metabolic need then, then you have rapid eye movement sleep, which consolidates learning from the previous day. It removes the emotional load of previous day experiences, we can make temperature adjustments, do all these things, avoid caffeine too late in the day. Lots of things to optimize these known states that occupy this thing that we call sleep. And AI and technology is, I would say, doing a really great job, as is pharmacology, to try and enhance sleep.

睡眠质量正在改善。尽管智能手机、噪音和城市喧嚣等干扰因素增多，我们却越来越擅长睡眠了。但在我看来，核心问题在于——我们对清醒状态的理解和分类极其匮乏。我们只会用目标来命名状态，比如'我需要工作状态'。

Sleep's getting better. We're getting better at sleeping, despite more forces potentially disrupting our sleep, like smartphones and noise and city noise, etcetera. Okay. Here's the big problem in my mind, is that we have very little understanding or even names for different awake states. We have names for the goal, like I wanna be able to work.

那么'工作'具体指什么？写书的一个章节？什么类型的书？基于什么内容的非虚构作品？

Okay, what's work? What kind of work? I wanna write a chapter of a book. What kind of book? A non fiction book, based on what?

虽然我们会谈论α波、β波、θ波，但作为神经科学领域，我们在定义不同清醒状态方面做得很糟糕。因此AI等技术不知道该瞄准什么目标，不知道要帮我们优化什么。相比之下，慢波睡眠和REM睡眠的研究就成熟得多。

But we talk about alpha, beta waves, theta waves. But I feel like as neuroscientists, we have done a pretty poor job as a field of defining different states of wakefulness. And so like the technology, AI and other technologies, they don't know what to shoot for. They don't know what to help us optimize for. Whereas with slow wave sleep and REM sleep, like, we've got it.

我经常自问：如果要在一天的头三小时和最后三小时都保持工作状态，这两个时段大脑的需求是否相同？我们其实不知道应该调整什么。所以我的问题是：你认为AI能帮我们理解白天大脑和身体经历的不同状态吗？

I ask questions of myself all the time. Like, is my brain and what it requires in the first three hours of the day anything like what my brain requires in the last three hours of the day if I want to work in each one of those three hour compartments. And so I think we don't really understand what to try and adjust to. So here's my question. Do you think AI could help us understand the different states that our brain and body go through during the daytime?

帮我们通过体温、专注力等指标理解这些状态，然后像优化睡眠那样优化它们。无论是心理治疗、听播客、陪孩子玩耍还是刷剧放松，人们投入大量时间精力金钱——从饮酒咖啡因到服用利他林、跑步等等——整个人类文明都在研发技术以提升行为能力，却仍不理解清醒状态。AI能教会我们吗？

Give us some understanding of what those are in terms of body temperature, focus ability, etcetera, and then help us optimize for those the same way that we optimize for sleep. Because whether it's a conversation with your therapist, whether or not it's a podcast, whether or not it's playing with your kids, whether or not it's Netflix and chill, whatever it is, the goal and what people have spent so much time, energy, money, etcetera, on whether or not they're drinking alcohol, caffeine, taking Ritalin or Adderall, or running or whatever. Like humans have spent their entire existence trying to build technologies to get better at doing the things that they need to do. And yet, still don't really understand waking states. So can AI teach it to us?

AI能揭示我们尚未意识到的目标吗？

Can AI teach us a goal that we don't even know we have?

AI能教会我们吗？我认为AI只是拼图的一部分。但在AI之前，我们需要更丰富的数据支撑——不仅仅是我个人的数据。比如我现在可能处于高度专注状态。

Can AI teach it to us? I would say AI is part of the story. But before we get AI, we need better, more data. Not just me, right? So maybe I am very focused right now.

但抛开我的信念不谈，从我的角度来看，想象我现在非常专注。我需要了解驱动这种状态的环境背景。那个环境里有什么？是内在的专注让我达到这种状态吗？我的环境究竟是什么？

But without my belief, and this is my perspective, is imagine I'm very focused right now. I need to know the context of my environment that's driving that. What's in that environment? Is it internal focus that's gotten me there? What what is my environment?

那个外部环境是什么？因此对我来说，理解清醒状态高度依赖于来自这些不同环境的数据和互动。举个例子，如果我在家里或假设我在车里，对吧？而你正在测量关于我的信息，你知道我处于压力中，或正在经历喜悦，或是此刻注意力高度集中。某些不同状态下，你可能希望我的家或系统做出反应来缓解。

What is that external environment? So the understanding my awake state for me is very dependent on the data and interactions that happen from these different environments. Let me give an Like, if I'm in my home or I'm in a say I'm in a vehicle, right? And you are measuring information about me, and you know I'm under stress, or you know I'm experiencing joy, or I'm or heightened attention right now. Some different states you may want to have my home or my system react to mitigate.

嗯，比如如果你在智能驾驶车辆里犯困，它会做出调整。

Well, like, if you get sleepy in a self driving in a smart vehicle, it will make adjustments.

可能会调整，但不一定适合你。关键在于如何优化个性化设置以及系统响应方式。我们可以判断任何家庭的暖通系统或车辆内部状态会调整背景声音、音乐，提供触觉反馈，调节温度、照明，调整座椅位置，动态改变空间配置——所有这些家庭或车辆系统都能做出反应，对吧？

Potentially, it will make adjustments, but not necessarily right for you. That's an important part is optimizing for personalization and how a system responds. And, you know, we can make a judge any home, HVAC system, or the the internal state of a vehicle is gonna adjust, you know, sound, background sound, music. It's going to adjust, you know, whatever whether it can haptic feedback, temperature, lighting, you know, any number of, you know, position of your, you know, your chair, dynamics of what's in your space, all of these different systems in my home or my my other what if my vehicle if it or some other system can react. Right?

但重要的是你的反应方式将改变我的状态。目标不是测量我，而是真正与我的状态交汇并引导其向某个方向发展，明白吗？

But the important thing is how you react is going to shift me. And the goal is to not measure me, but to actually intersect with my state and move it in some direction, Right?

某种程度上是的。我总认为设备擅长测量或调节。

Some Yeah. I always think of devices as good at measurement or modification.

没错。测量或调节。测量至关重要。但不仅是测量我，还包括对我的环境及外部环境的理解。

Right. Measurement or modification. Measurement is critical. And that's yeah. But measurement not just of me, but also of my environment and understanding of the external environment.

这正是地球观测和理解领域的发展方向。我们正逐步实现从低轨道卫星获取高质量图像数据，这使得技术与所需信息之间的反应时间大幅缩短，从而能更动态地理解和应对变化。对吧？

This is where things like earth observation and understanding We're getting to a place where we're getting you know, good image quality data from set the satellites that are going in the sky at at much lower distances so that you now have, you know, faster reaction times between technologies and the information they have to understand and be dynamic with them. Right?

能举个影响日常生活的例子吗？比如天气分析之类的？

Can you give me an example where that impacts everyday life? Are we talking about, like, weather analysis?

当然，比如天气预报、车辆周边环境监测、突发事件处理等。

Sure, weather predictions, car environment, things happening.

那交通呢？既然掌握了物体流动规律和优化方法，还有能实时观测车流并动态调整车道数量的卫星技术，为什么交通问题还没解决？

And what about traffic? Why haven't they solved traffic yet, given all the knowledge of object flow and how to optimize for object flow? And we've got satellites that can basically look traffic and open up roads dynamically, like change number of lanes. Why isn't that happening?

交通问题将在自动驾驶车辆普及后得到解决，因为那时不再存在...

The traffic problem gets resolved when you have autonomous vehicles in ways that don't have the

人为因素的干扰。问题自然迎刃而解。

human side of things. That gets resolved.

确实。只有全自动驾驶车辆普及后，交通拥堵才会彻底消失

It does. Vehicles Only autonomous vehicles, you don't have traffic in

人类独自转向自动驾驶汽车的方式。

the ways that you do with That's human alone to shift to autonomous vehicles.

正是来自人类系统的这种人为干预，你知道，正在扰乱所有模型。我认为现在的世界，我们经常思考可穿戴设备。可穿戴设备追踪我们。有智能床垫，这对理解非常有用。从智能床垫中你能学到很多，既能测量也能干预以优化你的睡眠，这就是美妙之处。

It is that injection from human the human system that, you know, is interrupting all the models. I think the world right now, we think about wearables a lot. Wearables track us. You have smart mattresses, which are wonderful for understanding. So there's so much you learn, well, from a smart mattress and ways of also both measuring as well as intervening to optimize your sleep, which is the beauty.

这是一个美好的、不可思议的时期，你可以测量这么多东西。但你知道，在我们的家里，我用了恒温器的例子。对吧？它对我的目标或我当时想做的事情相当无知。但它不必如此。

And it's this nice, incredible period of time where you can measure so many things. But, you know, in our home so I used the example of a thermostat. Right? It's pretty, you know, frankly dumb about what my goals are or what I'm trying to do at that moment in time. But it doesn't have to be.

有一家公司叫Passive Logic，我很喜欢他们。他们实际上拥有一些最智能的数字孪生HVAC系统。但你知道，他们的传感器测量声音等东西。他们测量二氧化碳。

And there are you know, there's a company, Passive Logic. I love them. They actually have think, some of the smartest digital twin HVAC systems. But, you know, their sensors measure things like sound. They measure carbon dioxide.

你的二氧化碳水平。比如，当我们呼吸时，我们会释放二氧化碳。想象一下，当我感到压力、快乐或紧张时，我的呼吸中会不断交换丙酮、异戊二烯和二氧化碳的动态混合物。这种动态的混合物既是我状态的指标，也是我周围空间可以提供更多关于我感受的信息，并且可以成为解决方案的一部分，而不需要我身上佩戴任何东西。对吧？

Your carbon your CO two levels. Like, when when we breathe, we give off CO two, you know. So imagine, there's a dynamic mixture of acetone, isoprene, and carbon dioxide that's constantly exchanging when I get stressed or when I'm feeling happiness or suspense in my state. And that dynamic sort of cocktail mixture that's in my breath is both an indicator of my state, but it's also something that, you know, it's just the spaces around me have more information to contribute about how I'm feeling and can also be part of that solution in ways that I don't have to have things on my body. Right?

所以我现在有可以测量二氧化碳的传感器。你可以看我的TED演讲。我举过例子。我们在杜比时请人观看《Free Solo》，亚历克斯·霍诺尔德攀爬酋长岩的电影。

So I have sensors now that can measure CO2. You can watch my TED Talk. I have given examples. We brought people in when I was at Dolby and had them watching Free Solo, the Alex Honnold movie where they're climbing El Cap.

压力山大。

Stressful.

由于二氧化碳比空气重，我们只需通过地面上的管道就能测量二氧化碳浓度，并实时获取其中的二氧化碳差异数据。

So carbon dioxide's heavier than air, we could measure carbon dioxide from just tubes on the ground, and you could get the real time differential of CO2 in there.

他们全程都感到害怕吗？

Were they scared throughout?

不。但我的意思是，我们总会无意识地传递情绪信号对吧？无论身处何地都是如此。通过观察二氧化碳浓度的时间序列数据，你就能知道电影情节的发展，甚至不需要任何注释说明。

No. What well but it's I mean, I like to say we broadcast how we're feeling. Right? And we do that wherever we are. And in this, you could look at the time series of carbon dioxide levels and be able to know what was happening in the film or in the movie without actually having it annotated.

你可以判断出他何时登顶、何时放弃攀登、何时扭伤脚踝。绝对准确。还有另一项研究——我忘了作者是谁——他们让不同观众在不同日期观看《饥饿游戏》，通过数据就能精确定位凯妮丝裙子着火的场景。这就像是人类情绪的数字痕迹。

You could tell where he summited, where he had to abandon his climb, where he hurt his ankle. Absolutely. There's another study, I forget who the authors are, and they've got different audiences watching Hunger Games. Different days, different people, you can tell exactly where Katniss's dress catches on fire. And it's like we really are sort of it's like digital exhaust of how we're feeling.

在体温变化中，我们会辐射出情绪信号。我坚信眼睛能有效反映我们的认知负荷和压力水平。

But in our thermals, we radiate the things we're feeling. I'm very bullish on the power of our eye in representing our cognitive load, our stressors.

我们的眼睛？

Our eye?

对，我们的眼睛。比如瞳孔直径的变化。

Our eye. Yes. Like the diameter.

我们的眼睛。我们的眼睛。抱歉。字面意思就是我们的眼睛。是的。

Our eye. Our eye. Sorry. Literally our eyes. Yes.

我们的瞳孔大小。

Our pupil size.

是的。对，没错。当我还是生理学家时，我曾与许多物种合作研究细胞内信息处理机制，同时也经常使用瞳孔测量法作为感知参与度和体验的指标。

Yes. Yes, yes. Back when I was a physiologist, I've worked with a lot of species on understanding information processing internally in cells, but also then I would very often use pupillometry as an indicator of perceptual engagement and experience.

没错，瞳孔放大意味着更高的唤醒度，警觉水平提升。

Yeah, bigger pupils mean more arousal, higher levels of alertness.

对，可能是更高的唤醒度、认知负荷，或者明显的光线变化。但与十五二十年前不同的是，过去要追踪那种能利用所有自主神经系统确定性反应的分辨率和数据非常昂贵。因为这些反应是确定性的，不是概率性的。明白吗？这些反应就像身体在本能反应，甚至不需要大脑指令

Yeah, more arousal, cognitive load, or obviously lighting changes. But the thing that's changing from twenty years ago, fifteen years ago, it was very expensive to track the kind of resolution and data to leverage all of those autonomic nervous system deterministic responses. Because those ones are deterministic, they're not probabilistic. Right? Those are the ones that it's like the body's reacting even if the brain doesn't say

完全不需要意识层面的觉察。

Below anything about conscious detection.

没错。

Yeah.

是的。

Yeah.

但今天，我们可以通过开源软件在笔记本电脑或移动设备上即时实现这一点。对吧？每副智能眼镜佩戴时都会追踪这些信息，成为数据通道。虽然这些信号可能存在模糊性，比如光线变化等因素的影响。

And but today, we can do that with a I mean, do well, we can do it right now with, you know, open source software on our laptops or our mobile devices. Right? And every pair of smart glasses will be tracking this information when we wear them. So it is becomes a channel of data. And, you know, you it may be an ambiguous signature in the sense that there's, you know, changes in lighting, there's changes.

我是感到兴奋还是那些

Am I aroused or am I Those

这些都是可以校准的，对吧？比如佩戴能测量瞳孔大小的眼镜，镜片可以搭载感应器来检测我眼睛所处环境的照明强度，评估光线动态变化。我们只需将其作为分母处理。

can be adjusted for, right? Like if you can literally take a measurement, wear eyeglasses that are measuring pupil size. The eyeglasses could have a sensor that detects levels of illumination in the room at the level of my eyes. It could measure how dynamic that is. We just make that the denominator in a fraction, right?

然后把瞳孔大小变化作为分子来观察就行，对吧？嗯，大致如此。

And then we can just look at changes in pupil size as the numerator in that fraction, right? Yep. More or less.

你只需要配备其他传感器。

You just have to have other sensors.

关键是要进行抵消校准。当你从阴影处走到明亮区域时，瞳孔大小确实会变化，但你可以针对这种变化进行调整，对吧？嗯，标准化处理后就能得到兴奋指数。

All you need to do is cancel. So as you walk from a shadowed area to a brighter area, sure, the size changes, but then you can adjust for that change, right? Yep. Just normalize for that. And you end up with an index of arousal.

没错。

Right.

这太神奇了。你还可以将光照指数作为一个有用的衡量标准，比如与你的维生素D水平相比较，或者判断你是否需要更多光照来提升兴奋度。它甚至能告诉你这些：'嘿，下班后去左边户外散步五分钟，就能满足一天的光子需求。' 这类信息，而不仅仅是计步。

Which is amazing. You could also use the index of illumination as a useful measure of like, you getting compared to your vitamin D levels, to your levels of maybe you need more illumination in order to get more arousal. Like, it could tell you all of this. It could literally say, hey, take a five minute walk outside into the left after work, and you will get your photon requirement for the day. You know, this kind of thing, not just measuring steps.

所有这些现在都成为可能。我只是不明白为什么它们没有被更快地整合到单一设备中。因为你也想知道那个人的血糖值，而不是抽血送检整个实验室。想想那些因为行业标准连续工作十三小时的住院医生，他们在病历上频频出错。总有一天我们会感叹：'真不敢相信我们以前是那样做的。'

All this stuff is possible now. I just don't know why it's not being integrated into single devices more quickly. Because you'd love to also know that person's blood sugar instead of like drawing their blood, taking it down the whole lab. Like you think about with the resident that's been up for thirteen hours because that's the standard in the field, and they're making mistakes on a on a on a chart. It's like I think at some point, we're just gonna go, I can't believe we used to do it that way.

太疯狂了。

It's crazy.

是啊。而且很多消费级设备和我们能从摄像头、加速度计或环境数据中进行的计算，都能反映我们的身体状态和你提到的那些情况。为什么没实现？很多原因在于监管流程陈旧，跟不上创新的加速发展。

Yeah. No. And it's a lot of the consumer devices and just computation we can do from, you know, whether it's cameras or accelerant or other data in our environments that tell us about our physical state and some of these situations that you're talking about. A lot of the I mean, why isn't it happening? Lot of reasons are simply the regulatory process is antiquated and not up to keeping up with the acceleration of innovation that's happening.

要知道，即使某些产品被认为属于同类且应该快速通过，FDA的审批流程和监管成本仍然极高。嗯。最终这些技术和数据实际可应用于医院或需要它们的场所时，往往已经落后多年。如今消费级设备对我们生物过程的监测能力，在很多方面已经达到甚至超越了医疗级设备。这仅仅是因为它们...

You know, getting things through the FDA, even if they're, you know, deemed, you know, in the same ballpark and supposed to move fast, you know, with the regulatory costs and processes is really high. Mhmm. You know, you end up many years, you know, down the road from when the capability and the data and technology actually should have arisen, to be used in a hospital or to be used in a place where you actually have that kind of appreciation for the data and use. The consumer grade devices for tracking of data of our biological processes are on par and in many cases surpassed the medical grade devices. And that's because they just have.

但它们必须以消费级产品的名义来描述功能和追踪数据，避免医疗声明，才能继续在这些领域发展。毫无疑问，这是阻碍许多这类设备和功能普及的重要原因。

But then they will have to bill what they do and what they're tracking in some way that is consumer, you know, is not making the medical claims to allow them to be able to be, you know, continue to move forward in those spaces. But there's no question that that's a big part of what you know, holds back the availability of a lot of these devices and capabilities.

我想稍作休息，感谢我们的赞助商之一——Function。去年，在寻找最全面的实验室检测方案后，我成为了Function会员。Function提供100多项先进的实验室检测，为您提供全身健康的关键快照。这份快照能揭示您的心脏健康、激素健康、免疫功能、营养水平等多方面信息。他们最近还新增了毒素检测项目，如检测有害塑料中的双酚A（BPA）暴露，以及全氟烷基物质（PFAS）这类永久性化学物质的检测。

I'd like to take a quick break and acknowledge one of our sponsors, Function. Last year, became a Function member after searching for the most comprehensive approach to lab testing. Function provides over 100 advanced lab tests that give you a key snapshot of your entire bodily health. This snapshot offers you with insights on your heart health, hormone health, immune functioning, nutrient levels, and much more. They've also recently added tests for toxins such as BPA exposure from harmful plastics and tests for PFAS or forever chemicals.

Function不仅提供对身心健康至关重要的100多种生物标志物检测，还分析这些结果并提供相关领域顶尖医生的专业见解。例如，在我首次使用Function的检测中，发现血液中汞含量偏高。Function不仅帮我发现了这个问题，还给出了降低汞水平的最佳建议，包括减少金枪鱼摄入。当时我常吃金枪鱼，同时努力多吃绿叶蔬菜并补充NAC和乙酰半胱氨酸，这两种物质都有助于谷胱甘肽生成和解毒。后续的第二次检测证明这个方法确实有效。

Function not only provides testing of over a 100 biomarkers key to your physical and mental health, but it also analyzes these results and provides insights from top doctors who are expert in the relevant areas. For example, in one of my first tests with Function, I learned that I had elevated levels of mercury in my blood. Function not only helped me detect that, but offered insights into how best to reduce my mercury levels, which included limiting my tuna consumption. I'd been eating a lot of tuna while also making an effort to eat more leafy greens and supplementing with NAC and acetylcysteine, both of which can support glutathione production and detoxification. And I should say by taking a second function test, that approach worked.

全面的血液检测至关重要。许多与身心健康相关的问题只能通过血液检测发现。但传统血液检测一直价格昂贵且流程复杂。相比之下，Function的简洁操作和亲民价格令我印象深刻。因此我决定加入他们的科学顾问委员会，并非常高兴他们能赞助本播客。

Comprehensive blood testing is vitally important. There's so many things related to your mental and physical health that can only be detected in a blood test. The problem is blood testing has always been very expensive and complicated. In contrast, I've been super impressed by function simplicity and at the level of cost, it is very affordable. As a consequence, I decided to join their scientific advisory board and I'm thrilled that they're sponsoring the podcast.

如果您想尝试Function服务，请访问functionhealth.com/huberman。目前Function的等候名单已超过25万人，但他们为Huberman播客听众提供优先通道。重申一次，通过functionhealth.com/huberman即可获得Function的优先体验权。好的。我认同我们需要更多数据，市面上也有各种传感器可以监测血糖、睡眠、体温、呼吸等指标，这就引出一个问题：我们是否需要大量传感器？

If you'd like to try Function, you can go to functionhealth.com/huberman. Function currently has a wait list of over 250,000 people, but they're offering early access to Huberman podcast listeners. Again, that's functionhealth.com/huberman to get early access to Function. Okay. So I agree that we need more data and that there are a lot of different sensors out there that can measure blood glucose and sleep and temperature and breathing, all sorts of things, which raises the question of, are we going to need tons of sensors?

难道我们要像穿衣服一样浑身贴满传感器吗？要同时戴12块手表吗？这到底会变成什么样子？

I mean, are we gonna be just wrapped in sensors as clothing? Are we going to be wearing 12 watches? What's this gonna look like?

我主张尽量减少身体负担，不必佩戴所有这些设备。要知道，通过空间中的摄像头和计算机视觉技术，我们就能从所处环境中获取大量信息——比如房间里的传感器，我之前提到的暖通空调系统。这样你就拥有了一个数字孪生体，传感器在空间里追踪我的代谢率、二氧化碳浓度和声音等数据。

I'm an advocate for fewer things on, you know, not having all this stuff on our bodies. I'm you know, there's so much we can get out of the computer vision side from the cameras in our spaces and how they're supporting us in our rooms, the sensors on our I brought up HVAC systems earlier. So now you've got effectively a digital twin and sensors that are tracking my metabolic rates just in my space. They're tracking carbon dioxide. They're tracking sound.

由此你获得了环境背景信息，获得了智能分析。现在你能够从我的周边环境中获取更多数据。我的车辆同样如此，仅凭我坐在车里的姿势，就能判断我是否处于压力状态或情绪如何。

You're getting context because of that. You're getting intelligence. And now you're able to start having more information from, you know, what's happening in my environment. The same is true in my vehicle. You can tell how I'm whether I'm stressed or how I'm feeling just by the posture I have it sitting in my car.

对吧？你需要人工智能。这是数据的人工智能解读。但驱动这种姿态的可能还来自于对环境其他变化的认知。突然间，这就成了情境智能的结合——由AI驱动的空间动态理解，决定了我的状态，比如为何我总倾向一侧，因为我正思考着移动和坐姿的方式。

Right? And you need AI. This is AI interpretation of data. But what's driving that posture might be coming from also an understanding of what else is happening in that environment. So it's suddenly this con with contextual intelligence, AI driven understanding of what's happening in that space that's driving, you know, the state of me and how do I I keep leaning to the side because I'm thinking about the way I move and sit.

这是我内在状态的间接反映。同时还有来自环境的数据——比如我在开车时的状况，家里的天气变化，外部潜在的威胁，或是空间外的噪音，这些都为系统提供了更智能化的上下文。我坚信，唯有整合身体、局部环境与外部环境的系统，我们才算真正起步。而如今，AI终于能帮助我们开始融合这些数据了。

It's a proxy for what's actually happening inside me. And then you've also got data around me coming from my environment. What's happening if I'm driving a car or what's happening in my home in the weather, in threats that might be outside, in noise that's happening not inside the space, but things that give context to have more intelligence with the systems we have. So I'm a a huge believer in you don't we aren't anywhere until we have integration of those systems between the body, the local environment, and the external environment. And we're finally at a place where AI can help us start integrating that data.

说到可穿戴设备，显然某些大公司已有所作为。我们手腕上的手表载有大量与身体相关的信息。置于耳中的设备或许不被察觉，但耳甲区一枚硬币大小的贴片就能监测心率、血氧——因为眼球运动产生的电信号，仅通过测量耳内的眼电图，我们就能判断你的视线焦点。还能测量脑电图，从中获取眼球运动数据，甚至注意力状态。

In terms of wearables, so obviously, some of the big companies. We've got the watch we have on our hand has a lot of information that is very relevant to our bodies. The devices we put in our ears, you may not realize, but a dime sized patch in your concha, we can know heart rate, blood oxygen level, Because the electrical signature that your eye produces when it moves back and forth, we can know what you're looking at just from measuring a signature measuring your electro oculogram in your ear. We can measure EEG, electroencephalograms. You can also get eye movements out of electroencephalograms, but you can get attention.

通过耳内的信号特征，可以知晓人们的注意力所在。因此我们的耳塞成了窥探状态的窗口。目前已有不少公司正致力于此。那么我们需要佩戴多种传感器吗？不必。

You can know what people are attending to based on signatures in their ear. So our earbuds, you know, that becomes sort of a window to our state. And you've got a number of companies working on that right now. So do we need to wear lots of different sensors? No.

关键在于，无论传感器置于体内外，其数据能否协同工作，而非被某家公司垄断？能否与其他企业系统集成？这才是重中之重。你需要整合系统，让数据能与环绕你、我的空间或睡眠床垫的系统交互。毕竟，许多专业设计本就来自不同的开发者。

Do we need to have the sensors, the data we have, whether it's on our bodies or off our bodies, able to work together and not be proprietary to just one company, but to be able to integrate with other companies? That becomes really important. You need integrative systems so that the data they have can interact with the systems that surround you or surround my spaces or the mattress I'm sleeping on. Right? Because you've had a lot of specialty of design come from different developers.

这部分也是FDA和监管路径的产物——开发成本促使企业走向专业化，除非它们规模庞大。但如今我们已到达这样的阶段：这些数据即将开始大规模整合。但愿我们不必在身上佩戴过多设备，反正我绝对不愿意。

And that's partly been a product of, again, the FDA and the regulatory pathways because of the cost of development. It tends to move companies towards specialization unless they're very large. But where we're at today is you're going you know, we're getting to a point where you're going to start seeing a lot of this data get integrated, I I think. And and by all means, hopefully we're not going to be wearing a lot of things on our bodies. I sure as heck won't.

身上佩戴越多，越影响步态，带来诸多连锁反应。刚到这里时，与你们的工作人员交谈，他们问：‘你戴什么可穿戴设备？’其实我几乎什么都不戴。当然，我戴过戒指。

The more we put on our bodies, it affects our gait. It has ramifications in so many different ways. When I got here, was talking to some of the people that work with you, they're like, Well, what wearables do you wear? And I actually don't wear many at all. And, you know, I have worn rings.

我在不同时期都戴过手表。但对我来说，关键在于能获得洞察的时刻。我坚信穿戴设备应尽可能减少身体负担。值得提及的一家有趣公司是Pison。他们与Timex合作，外形类似Timex手表，但测量的是——你熟悉Pison吗？

I've worn watches at different times. But for me, the importance is the point at which I get insights that, you know, I am a big believer in as little on my body as possible when it comes to wearables. One interesting company that I think is worth mentioning is Pison. And Pison, again, they've got a form factor that's like a Timex watch or the partner with Timex, but they're measuring Are you familiar with Pison?

不熟悉。

No.

好的。他们测量的是心理运动警觉性，实质上是试图理解类似ENG（电神经调节）的数据，持续监测疲劳度和神经专注度，适用于高风险操作或运动训练等领域。我欣赏的是它通过生物特征数据捕捉高阶认知状态。这种能根据认知状态数据决定工作、训练或生活方式的决策能力，是令人振奋的发展方向。

Okay. So they're measuring psychomotor vigilance. So really trying to understand It's like an ENG, electro neural modulation, and they're trying to understand fatigue and neural attentiveness in a way that is continuous and useful for, say, high risk operations or training, whether it be in sport. But what I like about it is it's actually trying to get at a higher level cognitive state from the biometrics that you're measuring. And that to me is an exciting, really exciting direction, is when you're actually doing something that you could make a decision about how I engage in my work or how I engage in my training or my life based on that data about my cognitive state, and how effective I'm going to be.

接着我可以将这些数据与其他数据关联，在特定时间点做出更优决策、获得更深洞察。这实质上就构成了你的数字孪生。

And then I can start associating that data with the other data to make better to have better decisions, better insights at a certain point in time. And that becomes that's really your digital twin.

有意思。你之前说不喜欢'游戏化'这个词，但睡眠领域的'睡眠评分'概念确实有效——人们追求高分，若未达标也不会自我否定，而是调整行为。这不同于'我永远睡不好'的消极认知。

It's interesting. Earlier, you said you don't like the word gamification. But one thing that I think has really been effective in the sleep space has been this notion of a sleep score, where people aspire to get a high sleep score. And if they don't, they don't see that as a disparagement of them, but rather that they need to adjust their behavior. So it's not like, oh, I'm a terrible sleeper, and I'll never be a good sleeper.

它提供了逐夜改进的目标。是的，我认为这很有效。我说的游戏化不一定是与他人竞争，而是自我激励。想象这种模式也能应用于清醒状态的其他领域。

It gives them something to aspire to on a night by night basis. Yes. And I feel like that's been pretty effective. When I say gamification, I don't necessarily mean competitive with others, but I mean encouraging of oneself, right? So I could imagine this showing up in other domains too, for wakeful states.

比如记录高度分心的工作时段。如果每天结束时能知道：'今天至少有三次持续一小时的专注工作'，即使未完成全部目标，也会觉得是充实的一天。但现在这些判断都很主观。

Like I spent, I had very few highly distracted work bouts or something like that. Like, I'd love to know at the end of my day, I had three really solid work bouts of an hour each, at least, that would feel good. Was like a day well spent, even if I didn't accomplish what I wanted to in its entirety. Like, I put in some really good solid work. Right now, it's all very subjective.

我们知道步数游戏化作为公共宣传非常有效。比如每日一万步，现在我们知道你需要超过7000步这个门槛。但仔细想想，我们本可以简单地说：嘿，你每天想以适合自己的速度步行三十分钟吗？然而计步的方式却更有效，因为我认识的那些根本不热衷运动的人都会告诉我，他们确保每天走完11000步。真的，人们会主动跟我分享这个。

We know the gamification of steps was very effective as a public messaging. You know, 10,000 steps a day, we now know you wanna get somewhere exceeding 7,000 as the threshold. But if you think about it, we could have just as easily said, Hey, you want to walk at a reasonable pace for you for thirty minutes per day? But somehow the counting steps thing was more effective, because people I know who are not fanatic about exercise at all will tell me, I make sure I get my 11,000 steps per day. Like, people tell me this.

我就想，哦，好吧。显然这对人们来说很有意义。我认为量化表现能创造这种追求进步的状态。嗯。所以我觉得这非常有用。

I'm like, oh, okay. So apparently, it's a meaningful thing for people. So I think quantification of performance creates this aspirational state. Mhmm. So I think that can be very useful.

数据和对量化目标的理解确实很重要。这些本质上就是统计数据，或许在某种程度上是值得追求的。如果这意味着人们会多运动，我完全支持，对吧？如果以前我不怎么活动，不起身做事，而现在这个机制促使我行动，那就太棒了。

Data and understanding the quantification that you're working towards is really important. Those are, you know, statistics effectively that maybe they're good on some level to aim for. If it means that people move more, all for it, right? And it's something that if I didn't move as much before and I didn't get up and I didn't do something, and this is making me do it, that's awesome. Or that's great.

但更棒的是现在通过计算机视觉应用，我们能理解目标不仅是走一万步，或许还有一系列小任务需要完成——这些任务配合反馈和设定目标，正在从神经层面塑造我，让我更细致地达成目标。这正是我从神经可塑性角度最关注的。我只是不喜欢'游戏化'这个词，我认为一切训练都可以变得有趣并以某种方式游戏化。虽然我的职业生涯主要在工业界，但我始终热爱教学，在斯坦福时我总在思考：如何用技术融合人类系统，从神经回路优先的角度优化学习和训练？我们该如何通过更愉悦易懂的目标来激活神经系统？

But it's also great when now through like a computer vision app, can understand it's not just 10,000 steps, but maybe there's a small battery of things I'm trying to perform against that are helping shape me neurally with the feedback and the targets that I'm getting so that there's a little more there's more nuance towards achieving the goal I'm aiming for, which is what I'm all about from a neuroplasticity perspective. So I just don't like the word gamification. I believe everything should be fun or everything Training can be fun and gamified in some ways. Again, my life has been predominantly in industry, but I've always I love teaching and I've always been at Stanford to really there I try to how do I use technology and merge it with the human system in a way that does help optimize learning and training in a way that is from a sort of neural circuit first perspective. How do we think about the neural system and use this more enjoyable, understandable target to engage with it?

我最喜欢的例子是2018到2020年疫情期间，我注意到学生们发生了显著变化——他们的期末项目可以自由创作，但必须包含脑机接口、VR或AR等项目。

One of my favorite examples though is there was a period it was right around 2018, 2020 and from 2018 to 2020 and into the pandemic where, you know, there became the students, I noticed, had a much more There were a lot of projects. Their final project, they can build whatever they want. And, you know, they've had to do projects where they build brain computer interfaces. They've had to build projects in VR. They've had to build AR projects.

他们需要使用各种传感器驱动的输入设备进行开发。而2018至2020年间，我几乎在每个项目里都看到了健康组件，这种学生群体的显著转变令我欣喜——或许你也注意到了。至今我最爱的是一款VR游戏：我在停尸房醒来，必须解谜逃脱，僵尸从我体内爬出，喘息声在颈后逼近...

They've had to build projects that, you know, use any sort of input device. Yeah, they have to use different sensor driven input devices, and that's all part of what they develop. And around 2018, 2020, I started to see almost every project had a wellness component to it, which I loved. Thought and that it was a very notable shift in like the student body, and maybe you've seen that too. But I still got this like one of my favorite games today was this VR game where I'm, you know, in a morgue, I wake up, I've got to solve an escape room, I've got zombies that are coming out of me and they're climbing out of the morgue and they're getting closer and there's people breathing on my neck and they're, you know, and everything.

结果这竟是个健康应用！开发者说：'这就是我的感受'。游戏通过监测呼吸和心率，让僵尸根据我的生理信号行动——当我呼吸急促心跳加速时，僵尸就会更快逼近解谜中的我。

And it's a wellness app. Go figure. It was their idea of, look, this is what I feel like. I've gotta because I'm also measuring my breath and heart rate. And I've gotta keep those biological signatures, like everything about how the zombies in solving my escape room problems, they're going to get closer to me if my breath rate goes up, if my heart rate goes up.

我必须坚持

I've got to keep

所以这其实是关于压力控制的，没错。

So it was about stress control, Exactly.

是的。但那是在特定环境中，他们才意识到自己的感受。不过确实，你可以用更简单的方式实现。但至少我非常推崇如何运用恰当的量化手段来培养正确的习惯、技能，在某个我们可能无法细分或难以解析的领域里，提升敏锐度或分辨率，这能帮助我们达成目标。因为我的大脑现在需要学习理解那种差异，那种复杂性。

Yes. But it was in that environment and it was realized for them how they felt. But yeah, and you can do it in much simpler ways. But at least I'm a huge fan of how do we use the right quantification to develop the right habits, the right skills, the right acuity or resolution in a domain we might not or an area where we might not be able to break it into the pieces we need, but it's going to help us get there. Because my brain actually needs to now learn to understand that different, you know, that sophistication.

没错。我清楚地认识到，在健康领域，用吓唬人的信息来阻止人们做某些事很有效。

Yeah. It's clear to me that in the health space, giving people information that scares them is great for getting them to not do things.

嗯。

Mhmm.