脑机接口的未来，对话《科学》杂志的马克斯·霍达克

这也太酷了。

That's so cool.

我想聊聊你早期是怎么踏入科技领域的。

I wanted to jump to your start in tech broadly.

你是一开始就搞生物、软件和工程的吗？

I mean, did you start in bio and software and engineering?

你是怎么一步步走到今天的？

What was your sort of journey into what you're doing now?

你现在的事业——让人重见光明，简直太疯狂了。

Which is, I mean, giving people blindsight is the wildest thing.

观众可能在想：听多了B2B SaaS，可我到底该怎么变成你这样的人？

People watching might be asking themselves, well, hear a lot about B2B SaaS, but, you know, how do I actually become something more like you?

我确实一直做软件，最拿手的硬技能就是编程。

I was certainly doing software, and my deepest hard skill is software.

我虽然学的是生物医学工程，但打小就写代码。

I have a degree in biomedical engineering, but I grew up programming.

所以我做软件的时候，还没碰过任何生物技术呢。

So And I was doing that well before I was doing any biotech stuff.

我爸妈总跟我讲，我小时候坐在巴诺书店的地板上，哭着要他们给我买一本Visual Basic的书。

My parents tell me a story about how I sat on the floor of a Barnes and Noble and cried until they bought me a learned visual basic book.

我一直对大脑特别着迷。

I was always interested in the brain.

我确实深受科幻作品的影响。

I was definitely inspired by science fiction.

《黑客帝国》对我影响特别大，不只是因为那个全是代码构成的世界听起来太酷了，更因为它触动了我一些根本性的想法。

The matrix had a big impact on me, both because the idea of this, like, world of bits was just so alluring for for a bunch of, like, fundamental reasons.

你看这个世界，想造点东西真的很难。

Like, when I look around at at the world, like, it's hard to build things.

空间太受限了。

Space is constrained.

地球就这么点大。

It's like the Earth is small.

资源竞争太激烈了。

The resources are intensely contested.

空间倒是大得很。

The like, space is large.

光速又慢得要命。

The speed of light is low.

但在机器里，这些限制全都没有。

Like, you don't have any of those constraints in in the machine.

所以如果你能模拟一个世界，那里面几乎啥都能实现。

And so if you could simulate a world, kind of anything was possible there.

但反过来想，如果你真能造出这样一个世界，而且让人分不出真假，那就能得出一个结论：真正重要的，其实是大脑。

But then also, if you then kind of turn that inside out, if you realize that you can build this and that you couldn't tell the difference, then the corollary of that was there must be like the thing that matters is the brain.

只要你能设计并支撑起大脑，其他所有东西都可以被替代。

And if you can engineer the brain and support the brain, then all the rest of it is replaceable.

这想法明明这么深刻，可现实里却没人当回事，这让我觉得特别奇怪。

And that just seemed like a fairly deep insight that was not being borne out in the world in the way that it seemed like it should be.

一部分在于，如果你能给这种意识提供正确的输入环境。

Some of it is if you can surround that consciousness with the correct inputs.

对。

Yeah.

这其实也引出了一个问题：意识到底是什么？

I mean, this also gets into questions of what is consciousness.

大脑是怎么创造出我们的主观体验的？

How does the brain create our experience?

现在网上有个说法，认为脑机接口只是人工智能的周边话题，说我们得把人和机器融合起来——我觉得这话确实有点道理。

There's this meme out there that BCI is an artificial intelligence adjacent story, and that the goal is to we need to have to merge humans and machines, and I do think that there's something to that.

但我觉得更直接、更紧迫的是，我把脑机接口看作是与长寿和医疗健康紧密相关的事。

But I think in the more immediate thing here is that I see BCIs really a longevity, like, health care adjacent story.

如果人工智能的终极目标是造出超级智能机器，那我觉得脑机接口的终极目标其实是造出有意识的机器。也许到最后我们会发现，根本没有任何外部测量能告诉我们某物有没有意识、它体验是什么样的，唯一能确定的，只有你自己的感受。

If the end of the quest of artificial intelligence are super intelligent machines, and I think the end of the BCI quest are actually conscious machines, it might turn out that there's actually no measurement that we can take that will tell us if something is conscious or not or what it's like, and the only thing that you can actually know on that is your own.

所以如果真是这样，那想研究意识，我们就得靠脑机接口，亲自去‘看见’它。

And so if that's the case, then to study consciousness, we will need to use brain computer interfaces to see it for ourselves.

等你搞定了这个，就能慢慢理解那里到底在发生什么根本性的物理原理了，不管是全新的物理规律，还是某种涌现现象。

And once you've developed that, then I think that you kind of can understand the fundamental physics of what's happening there, whether that's new fundamental physics or it's emergent in some way.

但如果你能学会去把握大脑在利用的、宇宙本身允许的那种机制，迟早能造出超级智能又具备意识的机器，而我们能通过这些超高带宽的连接，真正融入其中。

But if you can learn how to build, like, kind of understand whatever the brain is taking advantage of that our universe supports, then eventually, get super intelligent conscious machines that we can be part of through these these ultra high bandwidth connections.

我觉得，这跟现在大多数人对脑机接口的理解完全不一样。

I think that's a very different narrative than how people usually think about BCI today.

我的意思是，我们现在才刚起步。

I mean, we're at

对，才刚开始。

the beginning of that.

对吧？

Right?

是啊。

Oh, yeah.

我们真的才刚刚开始。

We're at the very beginning of that.

你现在的这个试验，带宽确实还比较低，但以后肯定会大幅提升是肯定的。

The current trial that you have, I mean, it's low it's relatively low bandwidth, but it's going to get much higher bandwidth.

而且就像做任何事一样，你得先从能跑通的东西开始，而你现在的成果，本身就已经是个明显的突破了。

And then, I mean, like anything, you sort of bootstrap with the thing that works, which I think what what you have is a clear breakthrough as it is.

再看看个人电脑的革命，谁能想到，今天我们用的这些东西，当初是从Altair里那个小蓝盒子起步的？

And then if you look at the PC revolution, for instance, it's like, could you believe that all of this that we have today started with a little blue box in Altair?

这确实需要一点想象力，因为生物技术过去一直太循序渐进了。

It still takes some suspension of disbelief because I think biotech has just been so incremental.

以前虽然也有大进展，但整体节奏太慢了，你花十年做一件事，感觉还是在原地打转。

Like, it's been so like, there's there's been big advances, but at the same time, these time constants historically, I mean, you could easily spend ten years on something that feels very incremental.

但我觉得现在最让人兴奋的是，这种‘慢吞吞’的感觉真的没了。

And I think that one of the things that's so exciting about what's happening now is that no longer really feels so incremental to me.

在我看来，我们现在已经真正进入起飞阶段了，地球上发生了全新的事情。

To me, feels like we're firmly in the takeoff era now, like something new has happened on Earth.

不过也别忘了，这事可不是从2019年或者1999年才开始的。

But I think it's also important to remember that this didn't start in 2019 or 1999.

这其实从19世纪末就开始了，工业革命刚要爆发那会儿，说白了，人类的生活方式几千年来都没啥根本变化。

This started in the late eighteen hundreds with the Industrial Revolution, Just a few years before the Industrial Revolution really kicked off, I mean, life was more or less unchanged in a fundamental sense for several thousand years.

那时候的人甚至压根儿就没有‘进步’这个概念。

And they didn't really even have a concept of progress in many ways.

他们根本没法想象，蒸汽机刚出来后的头十年、十五年，生活会变成今天这样。

And I don't think there's any way they could have imagined the way that their life would have changed over the course of the first ten, fifteen years of the steam engine.

我现在看未来十五年，感觉就跟那时候一模一样。

And that is how I feel looking at the next fifteen years right now.

是的。

Yeah.

我们现在既有电刺激，同时也在做生物耦合。

I mean, so we have an electrical stimulation right now, and then at the same time, you also do have a biocoupling.

这可不是单纯的电刺激那么简单。

Like, it's not purely just electrical.

你觉得这是v2.0，还是说，算是下一个前沿？

Would you call it a v two or, like, sort of a next frontier?

这完全是另一个领域。

So this is a totally different area.

我的意思是，你或许可以用它来恢复视力。

I mean, the you might be able to use it for vision.

我们那个电刺激设备PRIMA治不了青光眼，因为青光眼是视神经本身坏了。

So one of the diseases that PRIMA, our electrical stimulator, doesn't treat is glaucoma, which is loss of the optic nerve itself.

理论上，我们的生物杂交BTI技术或许能用在那儿，但目前我们没往这个方向做。

And so it's possible that you could use our biohybrid BTI technology for that, but that's not what we're doing right now.

我们在科学领域有三个主要方向。

There are three elements to our pipeline at at Science.

第一个是视网膜和失明方面的研究，特别是PRIMA植入物。

The first is our work in the retina in blindness, especially with the PRIMA implant.

第二个是神经接口，第三个是我们的VESL灌注项目。

The second is our work in neural interfaces, and the third is is our work in perfusion with our VESL program.

说到生物杂交神经接口，核心想法是：既然大脑就是一堆神经元，那大自然会怎么解决这个问题？

The biohybrid neural interfaces, the idea here is, like, if your brain is a bunch of neurons, like, how would how would nature solve this problem?

我们常常从大自然中找灵感。

Like, we often look to nature for inspiration.

进化这工程师，比咱们强多了，至少在搞生物方面是这样。

Evolution is a way better engineer than than we are, at least when dealing with biology.

其实这个想法一开始是来自这样的观察：你的大脑分成两个半球，各自处理世界的不同部分，但你并不会感觉到两个半球、两个半视野。

But I think the intuition here kinda started from your brain is is composed of two hemispheres, and they kind of process different halves of the world separately, but you don't experience two hemispheres or two hemifields, we would say.

你感受到的，是一个完整的瞬间。

You experience one integrated moment.

而连接大脑两个半球的，有一条叫胼胝体的神经纤维束。

And this is there's a cable that connects the two hemispheres of the brain called the corpus callosum.

大概有两亿条纤维。

It's about 200,000,000 fibers.

我就在想，如果大自然真想造个超高带宽的大脑互联通道，它会怎么搞？要是让你设计一条新的颅神经，你会咋设计？

And I was thinking, like, if nature wanted to build a ultra high bandwidth brain to brain connection, like, what would how did or if you wanted to make a new cranial nerve.

所以与其搞视神经、前庭耳蜗神经，不如直接整一条‘互联网神经’。

So instead of having an optic nerve or vestibular cochlear nerve, it wanted to have like the Internet nerve.

那大自然会怎么解决这个问题呢？

Like, how would nature solve this problem?

它可能会长出一根新的神经。

Is it would grow like a new nerve.

再弄个新的神经束，末端带个USB接口。

It would have a new fiber bundle with a USB port at the end.

所以这里的思路是，如果你的大脑里有这么多神经元，那要是我在你的神经元上再培养一些神经元，会发生什么？

So the intuition here is like, if your brain has a bunch of neurons, what happens if I culture some neurons on your neurons?

在实验室里，你这么做的时候，神经元通常会自己长到一起，连上线，形成新的生物连接。

Do they like when you do that in a lab, the neurons will typically grow together and wire up and form new biological connections.

所以我们设计的这个设备，会在植入物里提前种上活的神经元——这些是我们专门改造过的、来自干细胞的神经元。

And so we have an approach to the device where we seed the implant with living neurons, these heavily engineered stem cell derived neurons that we've created.

它们和你自己的神经元有关系吗？

Are they related to your own neurons?

还是

Or

不是。

No.

其实这背后是一个非常深入的研究领域。

So really interestingly, this is actually one of the deep areas of research.

我们用的是单一细胞系，而这项技术最核心的知识产权就在于，我们让这些细胞逃过了免疫系统的识别。

So we there's it's one cell line, and the probably the single deepest area of IP on this is that we've hidden them from the immune system.

我们是少数几家能做出相当靠谱的‘低免疫原性’干细胞的公司之一。

So we're one of a a really small number of companies that have, I think, like, pretty convincing what we call hypoimmunogenic stem cells.

不需要为每个病人单独定制，那样成本太高，耗时也太长。

You don't need to manufacture it per patient, which would be really expensive and take much longer.

我们把这种经过工程改造的低免疫原性神经元，种在培养皿里，等它们长好后，再整体植入大脑。

We've got this hypoimmunogenic stem cell derived engineered neuron that we load into the device in a dish, and then that kind of gets stuck there, and then you engraft this onto the brain.

我们根本不会把任何电线插进大脑里。

So we don't we don't place any wires into the brain.

也不需要对你的大脑进行基因改造。

We also don't need to genetically modify the like, your brain.

其他一些想法，比如用光遗传学或者超声波，都需要做基因治疗，改造你脑里的神经元，但这就像是单程票。

Some of the other ideas out there, for example, using optogenetics or things like ultrasound, this requires using a gene therapy to genetically modify the neurons in your brain, which, first of all, that's like a one way door.

一旦出问题，后果可能非常严重。

And if it goes wrong, that can go really wrong.

而我们不一样，我们只改造了移植进去的细胞，其他什么都没动。

Whereas here, because we're adding the only thing that has been edited are the graft cells that we add.

就算这些细胞最后死光了，你的情况也不会比原来更糟，基本上跟没治一样。

And if if those die off, then, like, you're really not worse off than you were before for the most part.

但好处是，它们有可能在大脑里不断生长，形成遍布各处的生物连接。

But it comes with the potential of growing throughout the brain, forming biological connections all over the place.

我们在动物模型里已经看到这种效果了。

And I mean, that's what we've seen in in the animal models.

不过在人身上还没试过。

That's not in humans yet.

你看过詹姆斯·卡梅隆的《阿凡达》系列电影吗？

But have you seen James Cameron's Avatar movies?

当然了。

Definitely.

就是那些外星人脑后的那种长辫子，你知道吧？

Like, you know the ponytails that the aliens have?

我脑子里想的其实就是这个样子。

That's how I think about it, basically.

就像一条全新的颅神经，末端还带着个接头。

It's like it's a big new cranial nerve with a connector at the end.

我觉得那个‘阿凡达’里的辫子，其实就是对我做的这种生物混合神经接口最直白的比喻。

I think that's actually the avatar queue, I think, is a pretty direct reference for how I think about our biohybrid neural interfaces.

你之前不是说，咱们得找个‘USB接口’吗？

So earlier, you were saying sort of this how do we find a USB port?

当然，外星人那种形态，就是一种体现。

I mean, obviously, an avatar, that's one of the manifestations in the blue creatures.

视神经，某种程度上就像个接口。

The optic nerve, in a way, is like a port.

然后说到Neuralink，你当初联合创办它的时候，那东西是要直接进入大脑的，根本没什么明显的接口。

And then jumping to Neuralink, when you were cofounding it, that sort of enters the brain, and then there is no not necessarily an obvious port.

你是怎么想这个问题的？

How do you think about that?

你到底往哪儿接？它是怎么工作的？

Where do you attach, and how does it work?

从Neuralink那儿，你学到的哪些东西对现在有帮助？

And what did you learn from Neuralink that was useful here?

很多东西都

A lot of

我从Neuralink学到的，说白了就是一场终极的创业博士训练。

what I learned from Neuralink was just the In many ways, was the ultimate startup PhD.

更多是关于怎么去运作一个技术上特别复杂、需要跨学科团队和完整基础设施的公司。

And so that was more about how you execute a technically complex company that requires this type of multidisciplinary team and infrastructure.

我特别想知道，那时候你们的V1版本是什么样的？

I'm very curious from those days, what was the v one?

然后就是假设，接着是结果。

And then there's a hypothesis and then the outcome.

而到目前为止，科学上的结果已经非常非常棒了，当然还没完。

And then here, the outcome is very, very awesome with science so far, not done, obviously.

当你想到大脑的时候，我记得当初对我来说简直太神奇了。

When you think about the brain because I remember it being totally magical to me.

比如说，大脑到底在干什么？你怎么可能理解它？

Like, what is like, how do you even understand what the brain's doing?

它到底在用什么‘语言’交流？

Like, what is like, what language is it speaking?

那么复杂到不可思议的事情，我们该怎么去理解它呢？

How do we understand what's going on there that seems, like, impossibly complicated?

从信息处理的角度来看，我觉得大脑里充满了我们称之为‘表征’的东西。

The way that I would think about, like, the brain from this information processing perspective is the brain is full of these these things that we call representations.

比如，它能形成对手部活动的表征。

And so you can have a representation of, like, hand activity.

所以大脑里其实有个类似几何对象的东西。

So there's, like, a like, a geometric object in the brain.

比如你记录一些神经元的活动，当手指张开时，某个神经元会放电。

Like, if you record from some neurons, then when your finger is is, like, held open, a neuron will be firing.

而当手指握紧时，另一个神经元就会激活。

When it's closed, another neuron will be firing.

几乎每一个可能的状态，都有对应的神经元在负责。

There's neurons that kind of correspond to every possible state here.

在初级运动皮层——很多脑机接口公司都从这儿取信号——它通常只隔一到两个突触就连到肌肉了。

And often in primary primary motor cortex, which is where many of the other BCIs companies record from, primary motor cortex is a couple synapses, often two synapses from the muscle.

所以信号从头顶的皮层一路传到脊髓，再从脊髓跳一次突触到肌肉。

So it projects all the way from the top of the head down to the spine, and then there's another synapse from the spine out to the muscle.

因此初级运动皮层里的这种表征特别好理解，因为它直接对应我们能直观理解的东西，比如手的状态，尤其是关节力矩。

And so the representation that you get in primary motor cortex is kind of easy to understand because it looks like like, it directly corresponds to things that we can easily reason about, like hand state, and specifically often joint torques.

我有时候会拿大语言模型做个小实验，比如挑一个神经元作为起点。

One of the things that I like to do sometimes with the LLMs is I'll pick like a neuron to start from.

比如说视网膜神经节细胞。

For example, like the retinal ganglion cell.

然后我会想，好，往前推一个突触。

And I'll be like, okay, go forward one synapse.

那和它相连的都有哪些细胞呢？

Like, what are all of the cells that we're connected to?

我再选一个，接着说，好。

I'll pick another one and be like, okay.

往前推一个突触。

Go forward one synapse.

那这次又连着哪些细胞？

Like, what are all the cells that we're connected to?

就这么一步步地把大脑的通路走一遍。

Just kind of kind of walk through the brain.

每一代模型，你做这种推演的能力都会更强。

And each generation of model, your ability to do this gets better.

但你注意一点，当你靠近输入或输出端的时候，比如肌肉、耳蜗毛细胞、视网膜神经节细胞、视杆或视锥细胞，这些情况下，我们觉得这些表征是具体的，因为它们对应的是我们生活中很直观的东西——比如颜色、图像亮度、声音频率，或者肌肉控制。

But one of the things that you see is that when you're close to, like, an input or an output, like a muscle or a cochlear hair cell or a retinal ganglion a rod or cone, like, in these cases, we think of the representations as being concrete because they correspond to things that are intuitive for us, like colors and image intensities, or frequencies of sound, or muscle control.

但一旦你往大脑更深处走，这些表征很快就变得特别抽象了。

But as you go deeper into the brain, it very quickly kind of blows up into these very abstract things.

大脑里有个地方叫下颞叶皮层，它里面有个区域专门处理脸的表征，旁边紧挨着的就是物体的表征，就像两张地图并排放着。

And so there's a part of the brain called inferotemporal cortex where the representation that it has is a map of face like a map of objects or a map another way, right next to it is a map of faces.

我们可以沿着这张物体空间的图谱，也就是大脑对各类物体的神经表征，一路往上走。

We can go up this map of object space, this neural representation of general objects.

在某个点上，

There's one point.

你可以把它想象成一长串数字，其中某个位置就对应着一个花瓶。

You can think of it as a long list of numbers, and there's some point in that that's like a vase.

某个位置对应的是埃菲尔铁塔，

There's some point that's like the Eiffel Tower.

某个位置则代表一辆车。

There's some point that's a car.

有一个点代表一个人。

There's some point that's a person.

有一个点代表斑马。

There's some point that's like a zebra.

当你在这个流形上移动时，就能感知到任何可能的物体。

And as you move around in this on this, like, manifold, you get kind of the percept of any possible object.

那里有数百万个神经元，正在表征大脑能识别的所有可能物体的空间。

And there's millions of neurons there that are representing this, this space of possible objects that the brain could be identifying.

听起来像潜空间。

Sounds like latent space.

没错，它就是

It is a

潜空间。

latent space.

对极了。

Exactly.

所以现在人工智能和神经科学之间正在发生一场巨大的融合。

And so there's this huge unification going on between AI and neuroscience.

最有趣的一点是，当你训练AI模型——比如图像模型或者语言模型时，模型内部产生的表征，跟大脑里实际观察到的表征非常相似。

And one of the most interesting things is that when you train AI models, like like image models or and even language models, the representations that you get inside them look a lot like the representations you see in the brain.

太神奇了。

Fascinating.

这其实是个明显的线索，说明AI研究者们

And so this is like a real hint that the AI people I

没错，这确实很棒。

mean, that's really good.

他们走对路了。

Are on the right track.

是的。

Yeah.

不是的。

No.

我的意思是，说AI只是随机鹦鹉或者高级自动补全，这种说法根本就是外行话。

I mean, the the whole idea that, like, there's these things that are, stochastic parrots or glorified autocompletes, like, these people just don't know what they're talking about.

很多神经科学家转去做AI了，因为他们本质上还是在搞神经科学，只不过用模型做起来方便多了。

Many people in neuroscience have gone over to AI because they're basically still doing neuroscience, but it's just way easier to do it on the models.

听起来对你来说这是个好消息啊，说明确实存在某种潜在空间映射，科学就像是通往大脑的API。

It sounds like it's very good news for you in that, like, there is actually some kind of latent space mapping, and then the job of science in terms of being sort of like the API to the brain.

完全没错。

Totally.

就是这么回事。

Exactly.

这完全有可能。

It is entirely possible.

你从大脑里记录下来的神经活动，其实也是一种潜在表征。

The neural activity that you when you record neural activity from the brain, this is just another latent.

如果你能把这种活动翻译成另一个模型，那我们就能做出特别酷的东西。

And if you can translate this into another model, then you can do, we think, really cool stuff with that.

所以你现在有输入了，之前你提到过，早期的脑机接口实验主要是在搞清楚

So you have input now, and then you earlier were saying I mean, a lot of the earlier BCI experiments involved figuring out

比如运动控制。

like motor.

对。

Yeah.

运动解码是个特别经典的任务，实现方式其实有很多。

So motor decoding is kind of this very classic task, and you can do it in any number of ways.

但人类第一次实现光标控制或键盘控制，那是在90年代末。

But getting cursor control or keyboard control in a human, that was first done in the late '90s.

所以我觉得现在好多脑机接口公司都在做这个，就是因为咱们已经确定它肯定行得通。

And so I think a lot of the BCI companies are doing that now just because, like, we know it definitely works.

毕竟有真实患者的需求，说白了就是个电子工程问题。

You know, there's some patient need, and it really is just like an electronics problem.

只要你能把电子设备做得足够小、功耗足够低，不会产生太多热量，能顺利缝合皮肤，那就是一大突破。

Like, if you can shrink the electronics so that they're small enough and low power enough so that they don't dissipate a lot of heat so that you can close the skin, then that is like a big advance.

我认为这正是Neuralink真正做成的第一件事。

And that I think is really the first thing that Neuralink has done.

以前也有设备能做这种运动解码，但都需要一根线从头皮穿出来。

There were prior devices that could do that type of motor decoding, but they required a connector coming out through the scalp.

只要皮肤是开着的，就容易让感染顺着线往里钻，那可就麻烦大了。

And as long as the skin is open, there's a risk that, like, an infection will climb down that, and then you're gonna have a really bad day.

所以能把皮肤缝上特别关键，但以前这事儿特别难，因为得把电子元件做得足够小、足够省电，才能完全植入体内还不发热。我觉得让这成为可能的关键，是所谓的‘智能手机红利’。

So being able to close the skin is really important, but that was really difficult because it required really efficient electronics that were small enough to fully implant and also were power efficient enough that they wouldn't get And so I think the thing that made this possible is what we call the smartphone dividend.

单靠脑机接口自己搞不定这事，但苹果、三星这些公司砸了巨资把这类电子元件做出来了，我们才能用上。

BCIs couldn't have done this on its own, but Apple and Samsung and others have poured epic amounts of money onto making these types of electronics exist in the world so that people like us can use them.

而且你作为生物混合体，确实有明显的优势。

And then it feels like you have a really significant advantage around being a biohybrid.

我的意思是，这些难题通常都跟长期用电刺激脑细胞有关。

I mean, are all these issues famously about sort of trying to electrically stimulate brain cells for a long period of time.

是的。

Yeah.

我的意思是，这里其实有不同的产品类型。

I mean, I think that there are different products here.

说白了，这正是我做这件事的原因。

I think that on the like, on the one hand, I mean, that's why I'm doing it.

我觉得这主意不错。

I think that's a good idea.

但另一方面，有些人一看就觉得，哎，现在你得对付一个活体细胞了。

On the other hand, I think some people look at this, and they're like, that is now you have a cell to deal with.

你把一个设备，加上了一大堆生物成分。

You took a device, and you added a bunch of biology to it.

我觉得我们对这个已经有不错的把握了。

And I think we have a good handle on that.

这正是我们这么做的原因，但确实有得有失。

That's why we're doing it, but there's definitely a trade off there.

我觉得脑机接口，最终我们会明白，它不像药物那样是个具体的产品。

And I think that BCI, we're going to come to see is not is not a specific product in the way that, like, pharma is not a product.

我觉得未来会涌现出一大批脑机接口公司，各自深耕不同的应用场景，不同的电极探针方案都会找到合适的用武之地。

I think there can be a bunch of BCI companies going after different applications where different types of probes will make sense.

而生物混合技术这种方案，其实只有在那些最高端的场景里才是真的刚需。

And I think biohybrid in particular is only really necessary for some of the very highest end things.

反过来讲，要是想用它满足其他大量重要的医疗需求、落地其他重要应用，难度会高很多；和其他方案比起来，它要实现规模化的社会影响，节奏肯定会更靠后一些。

And on the flip side, it will be harder to deploy for many other important medical needs and important applications along the way, And we'll probably be a little backloaded relative to some other things in that scalable impact.

刚才你提到科学研究里还有第三个方向，就是和血管相关的那个技术？

So earlier, you're referring to there's a third part of science, which is vessel.

你再多讲讲这个吧，感觉你在这件事上用到了好多

Talk more about that, because it feels like you're applying a lot of

最开始的

the first

第一性原理思维，正是这套思维帮你做出了现在这个突破性的成果。

principles thinkings that got you here to this thing that is also pretty groundbreaking.

其实这个项目是我们目前所有项目里规模最小的。

So this is our smallest project.

现在有个领域叫体外灌注。

So there's this field of perfusion.

你可以把它想象成一种人工心肺机。

You can think of it as they're kind of like heart and lung machines.

大概十年前，我读到《柳叶刀》上的一篇文章，才第一次意识到这个问题——讲的是波士顿一个17岁少年，正在等肺移植。

And I I was first clued into the need here about a decade ago when I read an article in in a medical journal called The Lancet, which was this case study of this 17 year old living in Boston who was waiting for a lung transplant.

在等移植的这段时间，他靠ECMO系统维持生命。

And while he was waiting for this lung transplant, he was being kept alive on an on an ECMO circuit.

ECMO是体外膜肺氧合的缩写，说白了就是人工心肺机。

ECMO is the sacrum for extracorporeal membrane oxygenation, and this fancy word for, like, heart lung machine.

他的心脏没问题，但肺彻底坏了，全靠这个机器吊着命。

And in his case, his heart was okay, but his lungs had failed, and so this was keeping him alive.

等了一段时间后，他被诊断出出现了并发症，不再符合移植优先条件，结果被移出了移植名单。

And after a while on the transplant list, he was diagnosed with a complication that made him no longer a priority recipient for donor lungs, and so they took him off the transplant list.

这篇文章其实探讨的就是一个伦理难题：我们该怎么对待他？

And so this article is kind of about the ethical dilemmas of, like, what do we do with him?

是的。

Yeah.

但他还活着。

But he's alive.

因为他啊，正在打游戏呢。

Because he's, yeah, he's playing video games.

他在写作业，跟朋友一起玩。

He's doing homework, hanging out with friends.

如果我们关掉机器，他马上就会死。

If we turn off the circuit, he will immediately die.

可别这么做啊。

Well, don't do that though.

另一方面，他每个月花掉五十万美元的重症监护费用。

On the other hand, he's consuming a half $1,000,000 a month ICU sweep.

所以这篇文章里，医生们提到，他的家人和朋友从他的存活中得到了安慰，但这引发了公平性的争议。

And so there are these quotes in this article from the doctors being like, his family and friends derived benefits from his continued survival, and how this raised fairness questions.

因为如果我们长期支持他，那为什么不对所有人这么做呢？

Because if we support him for a longer period of time, then why don't we do this for everybody?

我当时就看到了这一点。

And so I saw this.

我觉得这些问题问得真好。

I'm like, those are great questions.

我得找到这些问题的答案。

I need answers to those questions.

因为技术和实际能落地的经济性之间，明显存在巨大鸿沟，不知为啥。

Because there seemed to be this big gap between what was technically possible and what was economic to deploy for some reason.

说白了，这正是当创始人的本质啊。

I mean, that's exactly what being a founder is about.

对。

Yeah.

所以我看到这个之后，想到有个叫PubMed的医学文献数据库，我就意识到，要是我在上面搜‘ECMO伦理困境’，能跳出好几页结果。

So I saw this, and I there's this database of medical literature called PubMed, and I realized that if I searched PubMed for the phrase ECMO ethical dilemma, there were multiple pages of results.

所以这根本不是个例。

So this was not like a one off.

我翻了那些文献，发现里面经常提到，ECMO 不该被当成所谓的‘通往无处的桥梁’，很多医生其实都在劝家属别在重症情况下考虑这个，因为一旦用了，就会陷入进退两难的境地——然后怎么办？这简直是个道德难题。

And when I looked at this literature, there it was often a lot of it was talking about how ECMO shouldn't be used as a as a, quote, bridge to nowhere, and how many doctors were basically trying to discourage families from even pursuing it in these critical care cases, because it would create this bridge to nowhere, and then what do we do, and it creates these dilemmas.

后来我问过一些医生，那是很久以前的事了。

And then I went and asked some doc this was a long time ago.

差不多十年前了。

This was almost a decade ago now.

我就问，为啥不能把它当成最终方案呢？

Like, oh, well, why don't we consider it a destination?

这就是他们用的词。

That's the phrase.

就是‘终点疗法’，而不是‘过渡疗法’。

It's like a destination therapy versus a bridge therapy.

要是这技术本身还不够成熟，还得再改进呢？

What if the technology just isn't good enough yet, and it needs to be improved?

确实得改进，这点没得说。

It needs to be improved, definitely.

但那根本不是我得到的回应。

But that wasn't even the response that I got.

我得到的反应是大喊大叫，还砸东西。

The response that I got was just shouting and throwing things.

我当时就觉得哪儿不对劲，可那时候我也没能力去深究。

And so I was like, something feels wrong here, but I wasn't really in a position then to pursue it.

但这件事一直在我心里，我觉得这里面藏着一个特别重要的共通点。

But this was always a thing that was kind of I saw that there was a really important unification here.

其实，同样的核心技术已经彻底改变了器官移植领域。

It also the same fundamental type of technology has really transformed organ transplantation.

那边他们管这叫NMP，常温机械灌注，不是ECMO，但道理是一样的。

So there, they call it NMP, normothermic machine perfusion, rather than ECMO, but it's the same idea.

二十年前，要是你得做肾移植或者肝移植，车祸要是半夜三点发生的，手术也得在四五点赶紧做。

So twenty years ago, if you needed a, like, a kidney transplant or a liver, if the car crash happened at three in the morning, the surgery would happen at four or five in the morning.

但现在，手术都能安排在下午，甚至第二天了，美国超过百分之七十五的肝移植现在都用这种灌注技术。

But now it gets scheduled for, like, the afternoon or the next day, and over seventy five percent of liver transplants in The US use this type of perfusion technology now.

但现有的设备，价格高达五十万美元。

But, like, the the systems that exist for this are, like, $500,000.

只能靠私人飞机运送。

They can only be moved by private jet.

有个业内大公司，结果发现他们的私人飞机物流业务，比医疗设备业务还大。

Like, one of the big companies in this space, it turns out that their private jet logistics business is bigger than their medical device business.

很明显，这中间还有很大的工程优化空间。

And it just there was just clearly an engineering that could refine this.

所以我们想，要是能把这技术优化到，能像托运行李一样，把肾脏直接送上联合航空的航班，运到东海岸，那该多好。

And so we looked at this, we thought, well, what if you could refine this to the point where you could check a kidney as luggage on a United flight to the East Coast?

或者，要是能做出一个设备，让那个17岁的孩子能背在身上带回家，而不是像他那样，根本没换氧合器的滤芯，一周后血栓堵死了，人就没了。

Or what if you could make a thing that that 17 year old could have brought home as a backpack instead of just what they did in his case is they stopped changing the oxygenator filter, and a week later, it clotted and he died.

事实就是这么发生的。

And that's what happened.

还有其他问题，比如怎么把皮肤好好缝合在脑部植入物周围。

There are other problems here, like being able to close the skin around the brain implant.

还得让连接血液回路的管子能和皮肤长在一起，不然容易感染。

You also need to make it so that the tubes that connect the blood supply to the circuit, the skin can heal to it, so that's not an infection risk.

不然就得天天小心翼翼地清洁。

Otherwise, you have to clean it very carefully.

总的来说，科学突破指明的方向，和实际在做的事，差距大得离谱。

But just overall, there's this huge gap between, like, clearly, like, where the scientific breakthroughs, like, were put were pointing and, like, what was being done.

我觉得很多人没意识到，其实要当个‘缸中之脑’，技术上早就做到了。

Like, I think I think that people don't appreciate is that in many cases, like, there's like, if you you wanna be a brain in a vat, like, this basically already exists.

你完全可以把一个临终病人在ICU里维持生命，几乎无限期地撑下去，但那生活质量简直惨不忍睹。

Like, you can keep a like, an end life, like, patient alive in an ICU almost indefinitely, but this is very poor quality of life.

所以病人常常主动要求撤掉这些设备。

And so patients, like, ask for that to be withdrawn.

没人想躺在病床上，浑身插满管子，就剩个脑子还醒着。

Like, nobody wants to be basically like a brain in, a hospital bed connected to tubes.

你得让人能过上高质量的生活。

You need to be able to provide a high quality of life.

所以你需要一种让人能真正接受、能长期用的东西。

And so you need something that people can live with.

如果你能恢复视力、听力、平衡感、运动控制，让人能重新走出去、做点事儿，那才叫真本事。

And I think to see this, if you can get vision, hearing, balance, motor control, the ability to be out in the world and doing things.

我突然意识到，这其实提供了一种全新的视角，来重新理解医学的根本问题。

I just saw this very fundamental way to reframe the problems of medicine here.

所以就像我说的，虽然现在有好几个不同的项目，但我觉得——

And so that, like I said, at science, even though there's these several different projects, I

在未来十年里，它们本质上就是一个项目。

really see them as one project over the next ten years.

我本来是搞工程的，讲究第一性原理，现在这词儿老跟马斯克挂钩了。

So started as an engineer, first principles thinking, which often now is quite associated with Elon Musk.

Neuralink 是怎么起步的？

How did Neuralink start?

你是怎么认识他的？

How did you get to know him?

那这整件事是怎么凑成的？

And how did all of this come together?

我第一次见你的时候，你还在做Y Combinator，那是好多年前了，也是我第一次在YC工作的时候。

Because I first met you when you were doing Y Combinator many years ago, my first stint at YC.

2016年初的一个晚上，我收到了山姆发来的一封邮件，标题是“一个疯狂的问题”。

So I got an email one night in early twenty sixteen from Sam, subject line crazy question.

大概就是说，马斯克要创办一家脑机接口公司。

Be like, Elon's starting a brain computer interface company.

那该找什么人来牵头运营这家公司呢？

Like, who should who should run it?

我当时还以为他们会同时咨询很多人呢。

And I assumed they're talking to a lot of people.

我第一反应其实是想到了我在麻省理工的几个朋友，我那时候还觉得，这些人都厉害得很，（很适合）。

And my first reaction was actually I I had some friends at MIT that I thought I'm like, well, these guys are really smart.

你该去跟他们聊聊。

You should talk to them.

但一小时后，我突然反应过来。

But then an hour later, I was like, wait a second.

于是我回了邮件，问他：我能跟你聊聊吗？后来萨姆就把我介绍给了埃隆。

And so I emailed him back, I'm like, can I And Sam introduced me to Elon?

那时候埃隆自己早就有了这个想法，也已经想好了公司名字——Neuralink。

And Elon was going around, he'd already had the idea on his own that he wanted to start a company, and he had the name Neuralink.

我觉得他当时也从好几个人那儿听到了我的名字。

I also think that he heard my name from enough people that he was talking to at the time.

2016年下半年，有一群人时不时聚在一起，每周碰一次面，慢慢就发展成了Neuralink。

And over the second half of 2016, there was just this group of people that was kind of some degree ever shifting that would meet once a week or so in the evening, and that snowballed into Neuralink.

最初那批人里，好几个都是我在杜克大学认识的。

And of the initial group, a bunch of them were people that I knew from Duke.

比如蒂姆·汉森，那个最早提出缝纫机点子的人，他跟我同在一个实验室，就在杜克。

So Tim Hansen, the guy who had originally had the sewing machine idea, he was in the lab that I came from at Duke.

他当时是个研究生。

He was a grad student.

我那时候还是本科生，在他实验室干活。

I was an undergrad working for him.

后来他和我们另一个朋友去找了UCSF的一位教授，还有那边的一个合作者。

And then the professor that he and and one of our other friends had gone to at UCSF, and then a collaborator there.

所以当时就那么一小撮人。

So was kind of a very small community.

刚开始聊电脑和人脑连接这事儿，感觉怎么样？

What was that like initially to talk about the idea of connecting a computer to a human being's brain?

埃隆比大多数人更早、更清楚地看到了AI的走向。

Elon, I mean, he saw what was coming in AI much more clearly than many other people much earlier.

我觉得这事不可能跟人类割裂开，必须得融合，这一点对他来说再明显不过了。

And I think the implications of this can't be a separate thing from humanity, and that needs to merge somehow, I think that implication was just very clear to him.

所以真正驱动他的，是怎么让这技术帮人类升级，而不是被甩在后面。

And so that was the genuine motivating factor of how do we make it so that this allows us to upgrade humanity rather than get left behind.

我的意思是，你看看地球的自然历史，这根本不是什么空想。

I mean, if you look at the natural history of Earth, it's not like this is a totally speculative thing.

人类早就统治了整个星球，连我们最亲近的近亲都得关在玻璃箱里，怕它们灭绝。

Humanity has totally dominated the planet, and we keep our closest living relatives in glass boxes so they don't go extinct.

所以历史上，更聪明的物种往往意味着更大的危险。

And so there's a real history here of greater intelligence being very dangerous.

一开始并没有什么具体的技术构想，但那种驱动力是实实在在的。

Like in the beginning, there wasn't a specific technical idea necessarily, but there was that motivating force.

后来我们就想，把能找到的最聪明的人聚在一起，再给足资源，做任何该做的事，最后大家达成共识，就是你现在看到的这种薄膜聚合物细丝。

And then the idea was we'd pull together the smartest group of people that you could find and enough resources to do whatever made sense, and eventually got consensus around what you see now thin film polymer threads.

你就是个绝佳的例子——从纯软件背景跨界到硬科技，现在真正在做能商业化、具有突破性的研究。

You're one of the best examples of someone who came from a pure software world and then went into hard tech and now is actually doing real breakthrough type of research and work that is also commercializable.

看节目的人里，说不定也有不少人正走在类似的路上。

The people watching, they might be on a similar track.

以你现在的见识，回过头来，你会对2016年的自己说些什么？

Knowing what you know now, like, what would you tell to the sort of 2016 version of yourself?

我觉得有两件事。

So I think there's two things.

第一件是我做了的，第二件是我没做的。

The first is, like, the thing that I did, and then there's the thing I didn't do.

我做了的就是，我特别清楚自己想要什么，然后就一直很主动地去追求它。

The thing that I did, I think, was I had I had a a clear sense of what I wanted, and then I was very high agency towards that.

上大学的时候，我就知道自己想搞脑机接口。

When I was in college, I knew that I wanted to work in brain computer interfaces.

我所在的杜克大学有个特别棒的实验室在做这个，我花了点功夫，硬是想办法挤了进去。

There was a great lab that was doing that work at Duke where I went, and I was pretty persistent in figuring out how to place myself into that lab.

那个实验室在医学中心。

It was in the medical center.

他们一般不收本科生。

They didn't usually take undergrad.

花了点时间，我才终于进去了。

They were like, took me a little while to get in there.

最后我发现，可以通过化学系的独立研究项目偷偷溜进那个灵长类神经科学团队，算是走后门吧。

Eventually figured out that I could sneak in by taking an independent study in the chemistry department that would be a backdoor into this primate neuroscience group.

但其实，我在大学里学到的大部分东西，都是在那个实验室里搞出来的。

But then really, most of my education in college happened in that lab.

所以我从小就开始编程，最拿手的硬技能是软件，但从2008年起，我就一直在搞灵长类脑机接口和闭环神经解码这一块。

So yeah, I grew up programming, and my deepest hard skill is software, but I've been doing primate brain computer interface, closed loop neural decoding stuff, since 2008.

所以啊，你要想做成这种事，光有决心和坚持还不够，关键得先知道自己想往哪儿走。

And so that was just like, you had to be pretty high agency and persistent in trying to follow through on that, but that only works if you have a sense of where you wanna go.

所以第一点，就是得搞清楚自己到底想要什么。

And so the first is like, figure out what you want.

我没做的事呢，是大学毕业后我创办了一家公司，叫Transcriptic。

The thing I didn't do was my so after college, I started a company called Transcriptic.

那是个机器人云实验室，说白了，我在大学时也在合成生物学组干过，那时候得每三个小时就去按一次‘酶标仪’的按钮，连着三天，就为了拿个数据。

It was a robotic cloud laboratory, so the idea was mean, I also, in college, had the experience of working at a synthetic biology group, where I needed to go press a button on a device called a plate reader every three hours for three days to take a measurement that I wanted.

我当时就想，搞软件的谁会这么干啊？

And I was like, in software, this doesn't we wouldn't do this.

这明显说不通啊。

This just clearly doesn't make sense.

我们早就该自动化了。

We would automate it.

那时候AWS刚冒头，云计算也开始火起来了。

This was also the time when AWS was just emerging, and cloud computing was becoming a thing.

我觉得特别明显：没必要每个研究员都自己搞个实验室，花几百万买设备，还得每隔三小时去按个按钮。我们应该建一个中央化的机器人云实验室，给科学家们开放API，让他们在网上就能跑实验。

And it seemed very obvious to me that instead of every researcher having their own lab and spending millions of dollars for all their equipment, and then needing to press these buttons, what we should build is a central robotic cloud laboratory that expose APIs that scientists can use to run experiments over the internet.

我干了这事，筹了不少钱，2017年卸任CEO后去了Neuralink。

I did that, raised a bunch of money when I stepped down as CEO in 2017 to join Neuralink.

那公司年收入都有好几百万美元了。

It had millions of dollars in revenue.

我觉得我们当时已经做到了一个很有希望的起步阶段。

I felt like we got it to kind of an early promising point.

但之后这十年，那个愿景一直没实现。

And then since then, over the last decade, that promise was not fulfilled.

那真是地狱模式。

That hard mode.

那简直是一场苦熬。

That was like a slog.

2012年到2016年那会儿，我特别有共鸣本·霍洛维茨那篇《挣扎》。

That era from 2012 to 2016, I strongly identified with Ben Horace's essay, The Struggle.

我现在觉得，我早该去给像埃隆这样的人打工，那能让我瞬间开窍，真正看懂这个游戏怎么玩。

And I think the thing that I should have done earlier is go work for somebody like Elon, because that just so dramatically leveled up my ability to do this and know how the game is played.

你经常会看到一些特别有潜力的孩子，心里就想：我要自己干。

I think that often, you'll see these really promising kids who are just like, I'm gonna do it myself.

我才不给谁当员工呢。

I don't wanna work for anybody else.

我要自己创业。

I'm gonna start my own company.

我要硬扛过去。

I'm gonna plow through it.

有时候这样也行得通。

Sometimes that works.

我有什么资格说三道四呢？

Who am I to say?

但我可以告诉你，创业这事儿，说白了靠的是口耳相传。

But I can tell you that very often, startup like, running a startup is an oral tradition.

历史上确实有过那么几次，一群特别厉害的人从零开始摸出了门道。

There have been a couple of nucleating times in history where, like, a really remarkable group of people have kind of figured it out from scratch.

我觉得PayPal就是这么个例子。

Like, I think PayPal was like this.

但除此之外，几乎都是靠口耳相传——从硅谷那几个少数文化圈子里传下来的经验，你要是20岁就搞明白了，跟26岁、28岁才明白，人生轨迹能差出十万八千里。

But almost always beyond that, it's like it's an oral tradition that you pass down from one of this handful of Silicon Valley cultures that can make a huge difference on the trajectory of your career to get that right when you're 20 versus when you're 26 or 28.

科学领域接下来也会这样，听起来你已经拉起了一支特别牛的团队。

Well, science is the next, and it sounds like you're assembling You've already assembled a really accomplished crew of people.

这些年我们从创业里学到的一点是，只要一件事真成了，资源和聪明人就会源源不断地聚过来。

And then what we've learned from startups over the years is that once something works, more and more resources, more and more smart people sort of come together.

再放眼一看，我们真希望在你目前所处的这些领域里，这样的事能越来越多地发生。

And then zooming out, that's what we really hope happens a whole lot more in exactly the spaces that you're in right now.

所以科学听起来现在正是一个特别值得投入的方向。

So science sounds like one of those places to go to right now.

这确实挺酷的。

It's pretty cool.

对。

Yeah.

我觉得自己特别幸运，能做这份工作，因为这根本是个跨学科的难题，要突破它，得靠各个领域顶尖的人才通力合作。

I definitely feel pretty lucky that I get to do this, because it's such an interdisciplinary problem, and to innovate on it, you need all these different areas and really great people in each of them.

但与此同时，今天你能做到的事，几年前根本不敢想。

But at the same time, it's just the the things that you can do today were unimaginable a few years ago.

而且说实话，我觉得我们团队绝对是这个领域里最强的。

And and, I mean, I think that I think we have the best team in the field.

那接下来的十年、二十年，科学和脑机接口会往哪儿发展？你怎么看？

So next ten, twenty years of science, BCI, I guess, where do you see this going?

那你最期待的是什么？

And what are you most excited about?

我现在有个‘事件视界’，定在2035年。

I have this, like, event horizon at 2035 now.

以前年轻的时候，我总为自己能看透未来感到自豪。

Like, when I was earlier in my life, I always kind of prided myself on the ability to see the future.

再往后几年的事儿，我还能有点儿感觉。

And that is the next few years, I think, I have a sense of.

但到了2035年，我就完全看不清了，像被一层墙挡住了。

But, like, by 2035, it's just like imp there's like, I can't see past it.

我觉得第一批能活到一千岁的人，现在可能就活着，而且人数可能比你想象的多得多。

Think it is very possible that the first people to live to a thousand are alive right now, and I think it might be many more people than you think.

不可能就地球上一两个人而已。

It's not gonna be like one or two people on Earth today.

地球现在确实处在巨变之中，但这种时刻历史上不是第一次发生，只是这一次特别剧烈。

Earth as a whole is at a not not unique, like, these moments in history have happened all the time before, but right now, it's a time of exceptional change.

这会受到正在发生的科技变革的极大影响，尤其是脑机接口和人工智能这两条并行的线索。

This is going to be really, really influenced by the technological changes that are happening, and the twin plot lines of brain computer interfaces and artificial intelligence.

人们开始意识到，人工智能是真的存在了。

People are beginning to get that artificial intelligence is real.

但它的价值还没被市场真正认可。

It is still not priced in.

大家还是没完全领会它的分量。

People still don't appreciate it.

我同意。

I agree.

但他们根本没意识到脑机接口即将带来什么、能实现什么，这两条线虽然并行，但完全是两回事。

But they really don't get what's coming in and what's possible with brain computer interfaces, and those are really parallel, but very distinct stories.

未来，智能将广泛普及，只要有人有能力和意愿去使用它。

Intelligence is gonna become widely available for those that have the agency to deploy it.

我对这一点总体上还是很乐观的。

And I am generally pretty optimistic about that.

我的PDOM也不是零，但也没到50%，就是没那么高。

Like, don't my PDOM is pretty it's not zero, but it's not 50%.

远低于那个水平。

It's well below that.

是的。

Yeah.

我不确定我们能不能彻底治愈所有疾病。

I don't know if we'll have cured all disease.

说实话，我绝对不会说2035年之前就能根治所有病，但我相信那时候会出现全新的治疗路径，彻底改变我们对人类处境的理解。

In fact, I definitely wouldn't use that term, wouldn't say we'll have cured all diseases by 2035, but I think that there will be new lateral options that totally reframe how we think about the human condition on that timescale.

而且会彻底重塑计算机和人类之间的互动方式。

And totally reconfiguring basically that sort of interface between computers and humans.

对，还有人与人之间的互动。

Yeah, and humans and each other.

在很多情况下，脑机接口其实就是脑与脑之间的接口。

A brain computer interface is equivalent to a brain to brain interface in many cases.

这直接带你进入一个全新的领域。

This takes you to totally new territory.

马克斯，非常感谢你来参加我们的对话。

Max, thank you so much for joining us.

谢谢你为未来做的一切，我们都很期待你接下来的创作。

Thanks for building the future, and we can't wait to see what you build next.

谢谢，加里。

Thanks, Garry.