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我们现在是不是处在人工智能的泡沫里？
Are we in an AI bubble?
我觉得现在并不存在人工智能泡沫。
I do not believe we're in an AI bubble today.
从某种角度来说，我当年作为科技投资人，赶上了2000年那场泡沫，其实那主要是电信泡沫。
I was, depending on how you look at it, the privilege and the misfortune of being a tech investor during the year two thousand bubble, which was really a telecom bubble.
我觉得把今天和2000年对比一下，特别有帮助。
And I think it's really helpful to compare and contrast today to the year 2000.
2000年的互联网泡沫或者电信泡沫，核心是所谓的‘暗光纤’。
The year two thousand internet bubble or telecom bubble was defined by something called dark fiber.
那时候，铺设的光纤中高达97%都是闲置的。
At the peak, 97% of the fiber that had been laid was dark.
但看看现在的情况。
Contrast that with today.
现在根本不存在闲置的显卡。
There are no dark GPUs.
新闻标题一直在变。
The headlines change.
但背后的根本问题没变。
The underlying questions don't.
随着人工智能投资持续重塑科技格局，创业者和投资者依然在应对那些核心问题。
As AI investment continues to reshape the technology landscape, founders and investors are still grappling with the same core issues.
我们是不是建了太多基础设施？
Are we building too much infrastructure?
现在的商业模式能撑多久？
How durable are today's economics?
长期的价值到底会落在哪里？
And where will the long term value accrue?
大卫·乔治与Atreides管理公司的加文·贝克展开对话，深入剖析人工智能领域——从GPU和数据中心，到前沿模型、软件和机器人。
David George sits down with Atreides Management's Gavin Baker to unpack the AI pool, from GPUs and data centers to frontier models, software, and robotics.
无论你是投资者、创业者，还是只是想搞清楚人工智能的走向，这场对话都提供了一个清晰的思考框架，帮助你理解这一数十年来最重大的科技变革之一。
Whether you're an investor, founder, or simply trying to understand where AI is headed, this conversation offers a thoughtful framework for thinking about one of the greatest technology shifts in decades.
这就带我们进入今天的开场对话环节。
And that brings us to our opening fireside chat.
我们一开始就来聊一个有点敏感的问题。
We're gonna start with a taboo question right out of the gate.
你们准备好了吗？
Are you ready for it?
如果AI是当下全球最大的趋势，那它的证据在哪？
If AI is the biggest trend in the world right now, where is the evidence for it?
为什么它才刚刚开始在经济中显现出来？
Why is it only just beginning to show up in the economy?
就像安德烈·卡帕西问过的，智能体真的只是幽灵吗？
And as Andre Carpathi asked, are agents really just ghosts?
为了开启这个话题，帮我们解答这个问题，有请阿特里德斯基金的管理合伙人兼首席投资官加文·贝克上台。
To kick this off and to help us answer this question, please join us in welcoming Gavin Baker, managing partner and CIO of Atreides.
有些人可能在推特上见过加文，就是那个特别有想法的人。
Now some of you may know Gavin as that really thoughtful guy on Twitter.
每次有重大AI新闻出来，我都知道有不少人指望盖文来解释到底发生了什么。
Anytime some big piece of AI news comes out, I know more than a few people who count on Gavin to explain what the f is really going on.
非常感谢盖文今天能来和我们交流。
So a huge thank you to Gavin for being with us today.
和他一起的是我们a16z的普通合伙人大卫·乔治。
Joining him is our very own David George, general partner at a16z.
你们知道刚才那首音乐是出自哪部剧吗？
Who knows what that music was from?
总算把开场的燃曲放对了。
Glad to get our pump up music right.
对。
Yes.
《太空堡垒卡拉狄加》，就是1977年那版原版，万一将来我们真得跟赛隆人干一架呢。
Battlestar Galactica, the original nineteen seventy seven one, in case we have to all fight Cylons in a few years.
没错。
Yeah.
这倒是自然地引出了话题。
Good segue into the topic, I guess.
谢谢你今天能来。
So thank you for being here.
每次和你聊天我都特别开心。
I always love talking to you.
我也是。
Same.
非常感谢你邀请我，也感谢你的同事们给我这个机会。
Really grateful to you for inviting me, grateful to your colleagues for having me here.
接下来两天我特别期待。
I really look forward to the next two days.
我觉得一定能学到很多，真的谢谢你。
I think I'm gonna learn a lot, so thank you.
是的。
Yeah.
好的。
Okay.
行吧。
Alright.
所以今天主要聊的是AI泡沫，从宏观角度来看看整个情况。
So the big topic is AI bubble, kind of macro view of things.
咱们先看几个数据，铺垫一下，然后我想听听你的看法，我们现在到底处在什么阶段。
So maybe just to start with a couple stats to set the stage, and then I wanna get your take on where we're at.
目前美国的数据中心投资已经达到了大约一万亿美元。
So we have about a trillion dollars of data centers in The US.
未来五年，计划再增加三到四万亿美元的投资。
The plan is to add 3 to $4,000,000,000,000 in the next five years.
过去三年里，我们在数据中心上的投入，已经超过了整个美国州际高速公路系统四十多年累计的总投资，而且还是按通胀调整后的数字。
Over the past three years, we have already built out in data center capacity, a larger amount of dollars than the entire US interstate highway system, which took forty years just in terms of dollars, and that's inflation adjusted.
仅OpenAI一家，就已敲定了超过一万亿美元的项目承诺，这个我们待会儿可以细聊。
OpenAI alone, I think has more than a trillion dollars of deals set up that they've committed to and we can talk about that.
但与此同时，这些基础设施的数据都大得吓人，让人觉得肯定是泡沫。
But at the same time so those are all like big numbers on infrastructure and they're scary and they say, oh, bubble.
谷歌最近公布了一个数据，说过去十七个月里，他们处理的令牌数量增长了150倍。
And Google released a stat recently that they have seen a 150 x increase in the amount of tokens processed in the last seventeen months.
一方面，这种疯狂的建设听起来确实让人担忧。
So on the one hand, you've got this crazy scary sounding build out.
但另一方面，实际使用量也在实实在在地增长。
On the other hand, you actually have a bunch of usage that's happening.
那么，我们现在是不是处在AI泡沫里？
So are we in an AI bubble?
我认为，今天并不存在AI泡沫。
I do not believe we're in an AI bubble today.
我有幸——或者说不幸地——在2000年互联网泡沫时期做过科技投资，那时候其实主要是电信泡沫。
I had, depending on how you look at it, the privilege and the misfortune of being a tech investor during the year 2000 bubble, which was really a telecom bubble.
所以，把现在和2000年做个对比，会很有帮助。
And I think it's really helpful to compare and contrast today to the year 2000.
首先，我觉得思科当年的市盈率最高达到了150到180倍。
First, I think Cisco peaked at 150 or 180x trailing earnings.
而英伟达现在大概只有40倍左右，估值完全不在一个量级。
Nvidia's at more like 40x, so valuations are very different.
但更重要的是，2000年的互联网泡沫或者电信泡沫，核心问题是所谓的‘暗光纤’。
Most important, however, is that the year 2000 Internet bubble or telecom bubble was defined by something called dark fiber.
如果你经历过2000年，肯定知道那是什么。
And if you're a veteran of the year 2000, you will know what that was.
暗光纤就是铺在地上却没通电的光纤。
But dark fiber was literally fiber that was laid down on the ground and not lit up.
光纤本身没用，除非两边有对应的光模块、交换机和路由器。
Fiber is useless unless you have the optics and switches and routers that you need on either side.
我记得很清楚，当时像Level 3、Global Crossing或者WorldCom这些公司，总说我们本季度铺设了二十万英里的暗光纤。
And so I vividly remember companies like Level three or Global Crossing or Worldcom would come in and they say, we laid 200,000 miles of dark fiber this quarter.
这简直太惊人了。
This is so amazing.
互联网的规模会大得惊人。
The Internet's gonna be so big.
我们都迫不及待想把它们都激活起来。
We can't wait to light these up.
在泡沫顶峰时，美国铺设的光纤中有97%都处于未启用状态。
At the peak of the bubble, 97% of the fiber that had been laid in America was dark.
对比一下现在的情况。
Contrast that with today.
现在根本不存在‘未启用’的GPU。
There are no dark GPUs.
你只要读任何一篇技术论文就会发现，交易跑量时最大的问题之一就是GPU过热烧毁。
All you have to do is read any technical paper, and that one of the biggest problems in a trading run is that GPUs are melting.
其实有个很简单的方法，能直接点出问题的核心。
And there's a very simple way to kinda cut to the heart of all of this.
就是看看那些在GPU上投入最大的上市公司，它们的投资回报率如何。
It is a return on invested capital of the biggest spenders on GPUs who are all public.
这些公司自从加大资本支出后，ROIC提升了大约一成。
And those companies, since they ramped up CapEx, have seen, call it, a 10 increase in their ROICs.
到目前为止，所有这些投入的回报都非常可观。
So thus far, the ROI on all the spending has been really positive.
关于未来在Blackwell上的巨额投入能否继续带来正回报，现在还存在不少讨论。
It's an interesting and open debate about whether or not it will continue to be positive with the quantum of spend we're gonna have on Blackwell.
我个人觉得会的。
I personally think it will.
但至少目前，AI投资的回报率确实非常高，这一点毫无争议。
But there's no debate that thus far the ROI on AI has been really positive.
从估值角度看，我们现在根本谈不上是泡沫。
And valuation wise, we're just not in a bubble.
我完全同意。
I couldn't agree more.
另外我想说的是，你可以对比一下当时和现在这项技术的实际应用和普及程度。
The other thing that I would say is you can contrast the actual adoption and usage of the technology from then.
对吧？
Right?
当年互联网其实特别难搞，因为你得同时搭建起双边网络。
The internet was actually really hard because you had to build a two sided network.
你得先建网站，还得拉来用户，过程复杂多了。
Like you had to build websites and then you had to get users and it's much more difficult.
而AI工具就不一样了，你只要通过API启动一下，或者打开网站上的ChatGPT，所有人都能立刻用上，对吧？
In the case of the AI tools, all you have to do is kind of light them up via API or turn on your website ChatGPT and everybody has access to them, right?
依托云计算和互联网，一下就能触达十亿用户，瞬间实现大规模分发。
Built on top of cloud computing, on top of the internet, and you can get to instant distribution, a billion people right away.
没错。
Absolutely.
还有一点是关于合作方。
So the other thing is the counterparties.
你刚才提到，这些公司恰恰是历史上最顶尖的企业。
So you mentioned this, they happen to be the best companies in the history of the world.
对吧？
Right?
我觉得，那些自掏腰包、为这些资本支出买单的人，加起来每年能产生大约三万亿美元的自由现金流。
I think collectively, the people who are coming out of pocket, the writing checks for this CapEx, I think they collectively generate like $300,000,000,000 of free cash flow a year.
是这样吗？
Is that right?
大概有个数就行。
Some directionally?
大概估算一下。
Round numbers.
是的。
Yeah.
而且他们账上还躺着五万亿美元的现金。
And they have $500,000,000,000 of cash on the balance sheet.
所以每当有人惊呼‘天啊，这是泡沫，要崩了吗？’
So whenever people are like, oh my god, it's a bubble or is it gonna pop?
我觉得这其实没什么大问题。
I'm like, I think it's kinda fine.
我的意思是，建一吉瓦的设施，成本得有四五十十亿美元。
I mean, it costs, like, 40 or $50,000,000,000 to light up one gigawatt.
是的。
Yeah.
如果是用英伟达的芯片的话。
If you're on Nvidia chips.
英伟达芯片要五十亿？
50 On Nvidia chips?
对。
Yeah.
没错。
Yeah.
所以，实际上相当于有个八千亿美元的缓冲空间，每年还新增三千亿。
So, you know, there's kind of like an $800,000,000,000 buffer growing $300,000,000,000 every year.
是的。
Yeah.
我的意思是，有些公司的自由现金流已经开始出现了，你知道的，这其实涉及到
I mean, free cash flow at some of them has begun to maybe, you know Well, this this goes to
你之前提到的投资资本回报率问题。
your point on return on invested capital.
我们接下来可能会看到稍微下降一点。
We should see that next down a little bit.
是的。
Yeah.
建设节奏上有点不匹配。
A little bit of a mismatch of the build out.
但你知道，拉里·佩奇内部说过，他宁愿破产也不愿输掉这场竞赛。
But, you know, Larry Page apparently internally said, I'm happy to go bankrupt rather than lose this race.
我觉得这种心态在谷歌，可能还有Meta，确实存在。
And I think that is the mentality for sure at Google and perhaps Meta.
这被视为生死攸关的事，你必须赢。
It's just seen as existential, and you have to win.
明白了。
Okay.
关于这些循环交易，已经有很多讨论了。
So lots has been written about these round tripping deals.
因为从互联网建设的角度来看，循环交易是个很让人担忧的问题。
So because round tripping is a very scary concept from the internet build out.
这曾经是个大麻烦。
That was a big problem.
你对这里的情况怎么看？
Do you make of it here?
这确实在发生，是客观事实。
It is objectively happening.
钱是可以互相替代的。
Money is fungible.
所以英伟达如果和OpenAI签了协议，他们可以说，你们不能用我们的钱买我们的芯片，但钱这东西是通用的。
So Nvidia, if they sign a deal with OpenAI, they can say, Hey, you can't use our money to buy our chips, but money is fungible.
但目前这种操作的规模还很小。
But it's happening at a very small scale.
是的。
Yes.
对。
Yeah.
我觉得
And I think
我知道这听起来像是加密货币或者区块链的事。
I know this is like a crypto or blockchain.
没错。
Exactly.
很好。
Good.
对。
Yeah.
我觉得推动这一切的，不是为了融资买GPU或数据中心设备，而是竞争格局的变化。
And I think what is driving this isn't the need to finance GPU or data center purchases, but it's actually competitive dynamics.
NVIDIA最大的竞争对手不是AMD，不是博通，更不是美满电子，也不是英特尔，而是谷歌。
So Nvidia's biggest competitor, it's not AMD, it's not Broadcom, it's certainly not Marvell, it's not Intel, it's Google.
更准确地说，是谷歌，因为他们拥有TPU芯片。
And more specifically, it is Google because Google owns the TPU chip.
这可能是目前唯一能跟NVIDIA抗衡的方案，无论是训练还是推理，谷歌都是最有力的替代选择。
And this is by far, maybe perhaps today, the only alternative to Nvidia for training and maybe the best inference alternative.
而谷歌是个棘手的对手，因为他们还拥有DeepMind公司，以及Gemini这个产品。
And Google's a problematic competitor because they also own a company called DeepMind, and they have a product called Gemini.
我觉得他们现在可以说是全球领先的AI公司。
And I think you could argue that they are the leading AI company today.
就在过去两三个月里，他们已经抢走了15%到20%的流量份额，这还只是Gemini的流量。
I think they've taken 15 or 20 points of traffic share in the last two or three months, and that's just traffic to Gemini.
这还不包括搜索摘要。
It does not include search overviews.
我猜从实际流量来看，谷歌现在比OpenAI、Anthropic任何一家都大。
I suspect on a actual traffic basis, Google is bigger than OpenAI, Anthropic, anyone today.
而这项业务将完全依赖TPU运行。
And that business is gonna run on TPUs.
另外还有三家目前重要的实验室。
And then we have three other labs that are relevant today.
Anthropic就是亚马逊和谷歌扶持的公司。
There's Anthropic, and that's an Amazon and Google captive.
Anthropic主要会用TPU和Trainium芯片。
Anthropic is really going to run on TPUs and Trainiums.
所以现在剩下的前沿玩家就是xAI和OpenAI。
And so you're left with x AI and OpenAI at the forefront.
如果谷歌对Anthropic这样的实验室说，我来帮你融资、提供芯片，出于竞争考虑，英伟达很难不做出回应。
And if Google is going to a lab like Anthropic and saying, I'm going to help you fundraise and give you chips, for competitive reasons, it's very hard for Nvidia not to respond.
正如詹森所说，他认为这会是个不错的投资。
And as Jensen said, he thinks it's going to be a good investment.
所以我觉得那些关于循环交易的担忧被夸大了。
So I think the round tripping concerns are pretty overblown.
是的。
Yeah.
我的意思是，英伟达真正需要的，是Meta能尽快行动起来，或者出现另一个美国的开源玩家，又或者中美在人工智能领域能达成某种缓和。
I mean, what Nvidia really needs is they need Meta to get their act together or another American open source player to emerge or maybe some sort of detente with China in AI.
对。
Yeah.
当有人问我关于英伟达的各种动作和循环交易时，我的看法是，他们做的每一件事都完全合理。
When people ask me about Nvidia and all the moves and the round tripping, my reaction is everything they've done is completely rational.
百分百合理。
A 100% rational.
没错。
Yeah.
从长远来看。
Long term.
是的。
Yeah.
当然。
Sure.
长远来看。
Long term.
他们做的这些事，可能在资本回报率上不如其他投资，但从战略角度来说，我觉得每一步都挺对的。
Things they do may not have as high of a return on capital as other things, but strategically, I think they're all kind of the right moves.
Jensen 是我认识的最出色的两位CEO之一，和Elon并列，我觉得他把一手好牌打得非常漂亮。
Jensen's one of the two best CEOs along with Elon I have ever known, and I think he's playing a strong hand really well.
是的。
Yeah.
明白了。
Alright.
所以你开始关注模型公司了。
So you started getting into the model companies.
咱们干脆聊聊模型本身。
Let's just talk about the model.
等会儿再回过头谈芯片、内存和网络，我想先听听你的看法。
So we can come back to chips and memory and networking because I wanna get your take on that.
不过既然说到模型这一块，你觉得市场格局会怎么变化？
But, you know, since we're on the model side, what do you think happens with market structure?
谁会在哪里胜出？
Who wins where?
你最看好谁？
Who are you most optimistic about?
你有哪些担忧？
Where do you have concerns?
我觉得对投资者来说，保持谦逊是很重要的品质。
So I think humility is an important virtue for an investor.
如果我们打个比方，说ChatGPT之于AI，就像Netscape Navigator之于互联网，那现在这个阶段，谷歌还没成立呢。
And I'm just if we're gonna make an analogy and say that ChatGPT is to AI, as Netscape Navigator was to the Internet, At this point in the internet boom, Google had not been founded.
马克·扎克伯格还在上中学。
Mark Zuckerberg was in middle school.
特拉维斯·卡兰尼克刚上幼儿园。
Travis Kalanick was in kindergarten.
所以现在还早得很。
So it's just very early.
因此，我觉得在应用层面上，对未来的判断还是要保持谦逊，别太自信。
So I think it's important to be humble about making high confidence predictions at the application layer.
这也是为什么我觉得，在这种新技术浪潮的初期，基础设施层往往是个更稳妥的选择。
It's one reason I think the infrastructure layer is often maybe a safe place to be at the beginning of one of
这些新技术浪潮的初期，基础设施层确实是个更稳妥的选择。
these new technology waves.
不过咱们还是具体聊聊基础设施层的作用吧，因为它们一方面明显在为其他应用提供商提供底层支持，另一方面它们自己也
Well, actually talk about the role they play at the infrastructure layer because there's a piece of them that obviously they serve as an infrastructure layer powering other application providers, and then they also have
它们自己也做应用。
their own application.
我完全同意。
So I think Absolutely.
我想做个区分。
I would draw a distinction.
对。
Yeah.
这一点在谷歌身上最明显，但要说对其他公司有十足把握，我觉得很难，除非你承认互联网当初是个颠覆性创新。
I mean, that's most true of Google, but I think it's hard to have high conviction other than to observe the Internet was a very disruptive innovation.
我认为有合理的观点认为，AI可能是个持续性创新，因为数据、购买算力所需的资本、还有分发能力——这些关键要素，如今所有大型科技公司都样样齐全。
I think there's reasonable arguments that AI could be a sustaining innovation because the raw ingredients of kind of data, the capital to buy compute, and distribution, which is what you need, all of today's biggest tech companies have all of those in spades.
所以只要它们执行得当、招到优秀人才、战略清晰，AI很可能会成为‘MAG七巨头’中许多公司的持续性创新。
So as long as they execute well, hire good people, and have a sound strategy, Like, I think you could see it be a sustaining innovation for a lot of members of the MAG seven.
但另一方面，我也觉得它具有颠覆性。
On the other hand, I do think it's existential.
如果你执行不到位，IBM 可能就是个不错的例子。
And if you don't execute, you know, IBM might be a might be a good fate.
是的。
Yeah.
对。
Yeah.
没错。
Yeah.
这确实挺难的。
That's that's tough.
是的。
Yeah.
数据、分发、算力、资金、人才。
Data distribution, compute, dollars, talent.
是的。
Yeah.
他们完全有资格赢得胜利。
And like They have every right to win.
是的。
Yeah.
他们完全有资格赢得胜利。
They have every right to win.
现在看来，他们比以往任何时候都更认真对待这件事。
And it seems now more than before, they're taking it quite seriously.
是的。
Yeah.
尤其是谷歌，但
Maybe Google in particular, but
哦，不是的。
Oh, no.
没错。
No.
显然，Meta也在做出同样重大的举动。
Obviously, Meta Meta is making the dramatic moves they're making too.
不对。
No.
在我看来，ChatGPT对谷歌来说就像珍珠港事件，我们现在就看他们会怎么应对。
To me, ChatGPT was Pearl Harbor for Google, and we're gonna see how they responded.
他们已经开始慢慢做出反应了。
And they're slowly starting to respond.
是的。
Yeah.
那你对他们的平台和基础设施业务未来有什么看法？
And then what do you think what's your forecast for that sort of the platform piece of their business, the infrastructure piece?
你觉得在商业模式和市场结构上，最终会变成什么样？
What do you think how do you think it shakes out in terms of, like, business model, market structure?
你觉得他们会像云服务或飞机制造商那样成为高利润企业，还是会像航空公司一样陷入低利润的激烈竞争？
So do you think they end up as high margin businesses like the clouds or, like, aircraft manufacturers, or do you think they end up very competitive in low margin businesses like airlines?
我觉得他们不会像航空公司那样，但随便看看2021到2022年任何一家SaaS公司的利润表，都能发现毛利率高达90%。
I don't think they'll be airlines, but you can anybody can just look at the p and l, you know, of a SaaS company circa 2021 and 2022, and you see, you know, 90% gross margins.
而AI的特性，因为 Scaling Laws 的关系，就像理查德·萨顿说的那样，它们对算力的需求更高。
And the nature of AI because of scaling laws, Richard Sutton's the better the better lesson, they're just more compute intensive.
所以它们的毛利率从结构上来看会更低。
So their gross margins are structurally going to be lower.
但这并不意味着它们不能成为优秀的企业。
But that doesn't mean they can't be great businesses.
我只是觉得，要等到哪个AI实验室或前沿实验室的毛利率接近当年SaaS或互联网时代的水平，还得等很久。
I just I think it's gonna be a long time before we see a truly kind of, you know, an AI lab or frontier lab with gross margins anywhere near SaaS or Internet era margins.
它们的运营支出倒是可能低很多，也许这就是平衡的方式，但毛利率本身根本上就不一样。
Now their OpEx can be a lot lower, and, you know, maybe that's how you square it, but just the gross margins are fundamentally different.
在 Scaling Laws 改变、推理阶段的算力需求不再那么关键之前——我看不出这种变化会发生——它们的毛利率都会维持在较低水平。
And until scaling laws change and the importance of test time compute, things like that to change, which I don't see happening, they're they are gonna be lower margin.
是的。
Yeah.
好的。
Okay.
那我们来聊聊应用层吧。
So let's talk about application layer.
你刚才已经稍微提到了一些关于SaaS公司的情况。
So you just you just kinda got into it a little bit with the SaaS businesses.
我不知道你有没有关注过Twitter上这个争论，每隔几个月就会有人跳出来喊SaaS完蛋了，马上就要消亡了，诸如此类的话。
And I don't know if you've waded into this fight on Twitter, but it's sort of, you know, the the like, you know, every few months it comes up and it's like, SaaS is terrible and it's dead and, you know, it's all going to go away.
就在最近，安德烈刚做完那个现金访谈，你懂的。
And then, you know, with Andre's to our cash interview he just did.
市场对他的观点反应挺积极的，结果又是一轮剧烈反转。
It's, you know, like, market's reacting positively to it, and it's like a whipsaw reaction.
那你对SaaS和软件行业的未来怎么看？
So what do you think happens with SaaS and software?
我觉得我大概在2024年初就说过，我觉得所有的应用型SaaS，跟基础设施类的SaaS，本质上可能根本不是一回事。
You know, I think I, you know, first said probably in early twenty four that I thought all of application SaaS might be a zero different than in than infrastructure SaaS.
我现在看法更细致了，我觉得如果瞄准那些分散的中小客户群体，应用型SaaS完全有可能诞生巨头。
I I would say I have a more nuanced view now, and I think there could be some really big application SaaS winners, especially if you serve, like, a more fragmented SMB customer base.
你看谷歌现在做得特别简单，只要你用他们的服务，就能轻松用自己的数据搭建任何SaaS应用，而且数据完全不会泄露给其他人。
You know, Google is making it really easy if you're a customer of theirs to use your data and essentially make any SaaS app you want, and then your data isn't shared with anyone else.
但很多零售商当年跟亚马逊打交道时犯了个关键错误——他们看到亚马逊的利润率低，就觉得这行不能干。
But the critical mistake that I think a lot of retailers made in dealing with Amazon is they looked at Amazon's margins and they said, we don't want to be in that business.
这显然是个巨大的失误。
And that was obviously a terrible mistake.
现在二十五年过去了，亚马逊的零售业务利润率其实相当健康。
And here we are twenty five years later, and, you know, Amazon has really healthy retail margins.
我担心的是，很多应用型SaaS公司现在拼命维持现有的毛利结构，觉得一旦毛利下降，股价就会崩。
And I worry that application SaaS companies are trying to preserve their existing gross margin structures because they believe that if their gross margins go down, their stocks will go down.
但根据我们刚才说的，要在AI领域成功，根本不可能避开毛利压力。
It is definitionally impossible given what we just discussed to succeed in AI without gross margin pressure.
我不明白他们为什么这么焦虑，毕竟微软和Adobe早就证明了，软件公司完全能应对利润率下滑，尤其是在AI兴起之后。
And I do not know why they have concerns because we have an existence proof that a software company can deal well with declining margins in Microsoft and Adobe to the whole AI thing came along.
你知道吗，以前公司都不敢从本地部署转向云，因为云的利润率更低。
You know, it used to be that companies were scared to go from on premise to the cloud because margins were lower.
云的利润率确实更低。
Cloud margins are are are lower.
但还是挺不错的。
They're still good.
微软就成功转型了，从卖永久授权加维护费，变成了云服务模式，之后十年股价表现相当不错。
And Microsoft, they transitioned, you know, from, you know, on premise perpetual licenses with maintenance to a cloud model, and it was a pretty good stock for ten years.
所以，如果你是做应用型SaaS的，我的建议就是别怕，毛利率下降其实更像是成功的标志，而不是什么丢脸的事，没必要害怕。
So I don't if you're an application SaaS company, like, what I would just say is don't be scared and look at declining gross margins kind of has a mark of success rather than, you know, a badge of shame or something to be feared.
你这么说还真有意思，
It's actually so funny you
因为每次我们听公司做汇报，几乎每一家都说自己是AI公司。
say that because whenever we have these discussions about companies, basically, every company that comes to present to us is like, we're an AI company.
我们一看他们的毛利率，发现低毛利率反而成了他们引以为豪的资本。
And we always look at their gross margins and it's become like a badge of honor for them to actually have low gross margins.
天啊，真的有人在用你的AI产品。
Of like, oh my god, people are actually using your AI stuff.
是的。
Yeah.
但如果你跑来说自己是AI公司，结果毛利率高达82%，
But if you show up and you're like, I'm an AI company and it's like, I got 82% gross margins.
那我就会觉得，根本没人真正在用吧。
You're like, I don't think anybody's really using
确实没人用。
You're not.
对。
Yeah.
这挺有意思的。
It's it's interesting.
对。
Yeah.
如果你是一家上市公司，你是更想要十美元收入、九成毛利，还是五十美元收入、六成毛利？
If you're if you're one of these public companies, would you rather have, like, $10 of revenue with 90% gross margins or $50 of revenue with 60% gross margins?
这还用想吗。
Not hard.
其实没那么复杂，真的。
Like, it's not that comp yeah.
没那么难懂。
Not that complicated.
但在公开市场里，这事儿挺难做到的。
It's hard to do in the public market.
在上市公司里确实难，但只要你讲清楚，把情况跟云服务的转型类比一下，大家就明白了。
It's hard to do in publics, but if you communicate it, you draw parallels to the cloud transition.
我是投资者，我看到这种模式会很兴奋。
I mean, I'm an investor, and I would be excited about it.
你懂的。
You know?
是的。
Yeah.
而且我觉得世界上不止我一个人这么想。
And I don't think I'm alone in the world.
这些传统企业级SaaS公司的巨大优势在于，它们已经有盈利稳定的现有业务，所以完全可以把新的AI产品先亏本运营，慢慢追上行业领先者之类的。
And then the big advantage these legacy application SaaS companies have is they do have these really profitable existing businesses, And so you can run your new AI products at breakeven and, you know, catch up to the leaders, etcetera, etcetera.
我只是没想到，居然没多少人这么做。
And I'm just surprised more people have not done that.
比如，为什么那些上市的编程工具公司连尝试一下都不愿意去跟Cursor竞争？
Like, why are none of the public coding companies even trying to compete with Cursor?
事实上，Cursor现在已经有海量的代码训练数据了，迟早有一天，它们积累的代码数据量会大到别人根本追不上。
And the reality is Cursor now, they have a trillion trillion tokens, and, you know, there there will be a point where they have enough coding tokens that it's tough to catch them.
但我觉得，以现在的状况，如果你是一家上市的编程工具公司，决定全力投入的话——
But I think today, if you're a public coding company and you said, I'm gonna lean in.
完全可以先亏本运营。
I'm gonna run at breakeven.
我手头已经有现成的业务了。
I have an existing business.
我要把它整合到所有东西里。
I'm gonna attach it to everything.
喂。
Hey.
你有机会，而且你也知道，回报显然非常可观。
You have a chance, and you know the prize is clearly really big.
我看马丁有点怀疑。
I see Martin is skeptical.
马丁说你有机会。
Martin Martin said you have a chance.
我说的是有机会。
I said a chance.
所以他才说有机会。
So he said a chance.
你跟我说有希望，这感觉就像在讲《笨贼一对》一样，根本不是
It's like a dumb and dumber you're telling me there's a chance, not
真正的希望。
like a real chance.
你说的是真有希望。
You're telling me there's a chance.
对，没错。
So yes, exactly.
是的。
Yes.
这就像是
It's like a
没错。
Yeah.
正是如此。
Exactly.
我完全同意。
I totally agree.
对。
Yeah.
我们其实看到了，我的意思是，大家都能看到，比如Figma当初推出时，毛利高得吓人，但他们说，我们要大力推广AI工具，毛利肯定会降。
We actually saw I mean, know, we see it, you know, we may if we if we, you know, Figma, for example, like when they went out, they are extremely high gross margin and they're like, hey, we're gonna, you know, pretty aggressively distribute our AI tools and our gross margins are gonna go down.
投资者问了几个问题，结果发现，这其实反而是好事。
And, you know, investors asked a few clarifying questions and then they were like, oh, that actually would be a good thing.
所以我挺惊讶的，公开市场上怎么没多少人这么做。
And so I'm surprised more people in the public markets aren't doing it.
对他们来说，结果还不错。
We worked out okay for them.
效果很好。
It's working out well.
这是个长远的打算。
Long game to play.
那在消费端的应用层呢？
What about on the consumer side at the application layer?
所以，网页作为进入互联网的入口，现在依然是主要入口。
So obviously, was the portal to the internet is kind of still is the portal to the internet.
整个商业模式都是基于捕捉用户的意图，然后把你引导到别人的网站去完成操作。
And the whole business model was predicated upon taking some intent and directing you to someone else's website where they would do stuff with you.
但以后不会是这样了。
It's kind of not going to be that way.
其实现在有了AI，就已经不是这样了。
It already is not that way with AI.
我今天试了下浏览器，想做点简单的购物，发现还是有不少地方不够顺手，但我相信会慢慢改进的。
Although I tried the browser today and I tried to do some pretty basic shopping stuff and it's, you know, still some work to do, but I think it will get there.
你觉得消费互联网公司的市场格局会怎么变化？
So what do you actually think happens with the sort of market structure of the consumer internet companies?
它们会被整合进聊天机器人的界面里，还是会有别的走向？
Do they get subsumed into a component of a chatbot interface, or do you think it's something else?
第一，这点不好说，得保持谦逊。
So one, humility, hard to say.
第二，我觉得那些推出AI浏览器的公司可能会后悔，毕竟还有个Chrome，用户多达五十亿。
Two, I would just say, I think the AI companies that have launched these AI browsers may come to regret it because there's something called Chrome that has whatever it is, 5,000,000,000 users.
如果你是谷歌，随便一查就能看到Google Buzz后来怎么样了。
And if you're Google, you know, you can just go look and what happened with Google Buzz.
他们一向非常谨慎。
They are very cautious.
你知道，他们现在正和政府打官司呢。
You know, there's you know, they're currently in in litigation with the government.
他们其实完全有能力做这件事，甚至可能做得更好，但他们就是不想当第一个。
And they could easily do this and probably do it even better, but they didn't wanna be first.
现在有两个原生AI公司推出了自己的浏览器，就让他们先跑三到六个月，占点先机，到时候再看吧。
So now you have two AI native companies with their own browsers, let them run for three to six months, get a little head start, and then, wow, here we are.
我们不得不这么做，但真不知道这能行得通吗。
We had to do this, and I don't know how that's gonna work.
也许对于那些不拥有Chrome的公司来说是这样。
Maybe for the companies other than Google who don't own Chrome.
是的。
Yeah.
数据和分发渠道在这方面确实非常关键。
Guess data and distribution is pretty powerful in that.
对。
Yeah.
事后看来，一切都清清楚楚。
Hindsight's 2020.
我想说的是，如今要跟那些拥有庞大现有用户群的公司抗衡，确实很难。
And the one thing I would say is I do think it's tough to bet against the companies with large existing user bases today.
我还觉得，推理能力从根本上改变了这些前沿模型的经济模式。
And I also think reasoning has fundamentally changed the economics of these frontier models.
在推理技术出现之前，我常这么说：如果你是一个前沿模型，却没有独特的优质数据和互联网规模的分发能力，那你就是历史上贬值最快的资产。
You know, pre reasoning, I often said, if you are a frontier model without access to unique valuable data and Internet scale distribution, you're the fastest depreciating asset in history.
我觉得推理能力真正改变了这一点，因为在后训练阶段，强化学习的工作方式让庞大的用户基础如今能启动一个飞轮效应——这正是所有成功的消费互联网公司的核心：产品好，用户就多；用户越多，算法就越智能；算法越智能，产品就越优秀，形成良性循环。
I think reasoning really changed that because the way RL works during post training, having a big user base now kind of unlocks that flywheel that was at the center of every great consumer Internet company where you have a good product, you get a lot of users, the users make the algorithm better, The algorithm makes the product better, and it just spins.
这种循环在人工智能领域还没完全转起来，但你仔细看，已经能看到苗头了。
And that it's not quite spinning yet in AI, but you can squint and see it.
所以我认为，这对Anthropic、xAI和OpenAI的商业模式产生了根本性的影响。
And so I think that fundamentally changes economics for Anthropic, for xAI, for OpenAI.
不过，马克·扎克伯格也在拼命追赶。
But, I mean, Mark Zuckerberg is trying hard.
是的。
Yeah.
咱们走着瞧吧。
And we'll see.
对。
Yeah.
没错。
Yeah.
展开剩余字幕（还有 144 条）
是的。
Yeah.
现在聚集了大量聪明人。
A lot of smart people
确实如此。
in there now.
是的。
Yeah.
没错。
For sure.
我觉得担忧在于，说来奇怪，中国的开源模型生态，反而帮了所有想追赶那四大实验室的美国公司大忙。
I I think the worry is, and I think this is another interesting thing, is if you don't like, in a strange way, the Chinese open source model ecosystem is a godsend to any American company that's trying to catch those four leading labs.
因为问题在于，如果你没有 Gemini 2.5 Pro，或者我们还没看到的 Grok 或 GPT 的后续版本来训练下一代模型，你就处于明显劣势。
Because the problem is if you don't have Gemini 2.5 Pro or a later checkpoint of it or a later checkpoint of Grok that we don't see or a later GPT Checkmate Checkpoint training the next model, you're at a big disadvantage.
顺便说一句，有一件事让我特别烦，就是总有人声称 GPT-5 是规模收益的终点。
Oh, by the way, one thing I just wanna say that drives me crazy is all these people who say that GPT five is the end of scaling loss.
GPT-5其实是个更小的模型。
GPT five is a smaller model.
它根本不是为了变得更强大而设计的。
It was not designed to be better.
它的目标是让OpenAI和微软运行起来更省钱。
It was designed to be more economical for OpenAI and Microsoft to run.
把GPT-5和规模递减扯上关系，简直荒谬。
It any reference to GPT five and scaling loss is crazy.
是的。
Yeah.
不好意思。
Sorry.
扯远了。
Rant.
说完了。
Rant over.
我们把底座搬上来吧，如果你需要的话。
We get the pedestal up here if you want.
是的。
Yeah.
没错。
Exactly.
和你握个手。
Shaking your hand.
好。
Yes.
好好干。
Be good.
那样就很好了。
That'd be good.
你想聊聊芯片吗？
Do you wanna talk about chips?
当然。
Sure.
所以，好吧，我知道你特别看好英伟达。
So, okay, I know you love Nvidia.
说说你对英伟达、AMD、TPU，还有A6的看法吧，你觉得这些玩家各自的竞争优势，市场格局会怎么演变。
Talk about, you know, your view of Nvidia, AMD, TPUs, a six, and how do you think sort of market structure shakes out their, you know, competitive advantage that the various players have.
是的。
Yeah.
我觉得本质上就是英伟达和谷歌TPU之间的较量。
I think it goes I think it is really it's a fight between Nvidia and the Google TPU.
还有一件事，很多人没意识到，那就是博通和AMD其实正在紧密合作进军市场。
And then something that I don't think is broadly appreciated is the extent to which Broadcom and AMD are effectively going to market together.
英伟达早就不再只是一个半导体公司了——我相信明天你听詹森讲就会明白。
Nvidia is no longer just a a semiconductor company as I'm sure you'll hear from Jensen tomorrow.
以前它是个半导体公司，后来靠CUDA成了软件公司，现在又通过机架级解决方案成了系统公司，甚至可以说，凭借在扩展架构、网络互联等方面的布局，它已经是一个数据中心级别的公司了。
You know, not it was a semiconductor company, then a software company with CUDA, now a systems company with these rack level solutions, and now arguably, you know, a data center level company with the, you know, level of architecting they're doing with scale up, scale across and scale out, scale across networking.
所以网络、架构和软件都非常重要。
So the networking, the fabric, the software, it's all important.
Broadcom 对像 Meta 这样的公司说：嘿，
And what Broadcom is saying to companies like Meta is, hey.
我们可以为你打造一套能跟 Nvidia 架构一较高下的系统，那套系统结合了 NVLink 和 InfiniBand 或以太网。
We will build you a fabric that can theoretically compete with Nvidia's fabric, which is a mixture of NVLink and either InfiniBand or Ethernet.
我们会基于以太网来构建它。
It will build it on Ethernet.
这会是一个开放标准。
It's gonna be an open standard.
而且，我们还能给你量身定制一个类似 TPU 的芯片——顺便说一句，Google 花了三轮才把 TPU 做出来。
And, hey, we'll we'll make you your version of of TPU, which, by the way, took Google three generations to get working.
你知道吗？
And you know what?
如果你的专用芯片不够好，直接插上 AMD 的就行。
If your ASIC isn't good, you can just plug AMD right in.
但我个人觉得，大多数这些ASIC最终都会失败，尤其是在
But I personally believe most of those ASICs are gonna fail, particularly if it's in the
是随着时间的推移，还是指在不久的将来？
fullness of like, over a period of time or in the fullness of time?
未来三年内。
In the next three years.
我觉得你会看到很多高调的ASIC项目被取消，尤其是如果Google开始对外出售TPU的话，这事儿最近在X平台上闹得沸沸扬扬的。
I think you'll see a bunch of high profile ASIC programs canceled, especially if Google starts selling TPUs externally, which has been all over x.
然后呢，你懂的，到底具体怎么运作，谁也说不准。
And then, you know, they you know, who knows exactly how that would work?
因为如果你是 Anthropic 的话，据传他们打算花几百亿美金去买 TPU。
Because if you're an Anthropic you know, it's just rumored Anthropic wants to buy tens of billions of TPUs.
如果你是 Anthropic，也许你不想让 Google 看到你的核心机密，但总有办法绕过这个问题。
If you're Anthropic, maybe you don't want Google seeing your secret sauce, but there's ways around that.
所以我觉得，目前这主要是 Google 和由 Broadcom 支持的 TPU 之间的较量，而且 Google 随时可以把 TPU 从 Broadcom 手里收回来。
So I think this is really a battle between Google and its TPU enabled by Broadcom for now, and Google can take the TPU away from Broadcom whenever they want.
是的。
Yeah.
现在他们做不了博通正在做的以太网网络，但他们掌控着TPU。
Now they can't do the Ethernet networking that Broadcom is is doing, but they control the TPU.
所以这实际上是谷歌和TPU对阵英伟达，还有亚马逊，你知道的。
So it's really Google and the TPU versus Nvidia, you know, with with, you know, Amazon.
比如安纳普尔纳团队，这绝对是所有超大规模云服务商里最顶尖的芯片团队。
Like, that's a very talented team, arguably the most talented silicon team at any hyperscaler, the Annapurna team.
我觉得Tranium三代芯片很可能会比二代强得多。
Like, I think the Tranium three will probably be a much better chip than the Tranium two.
谷歌花了三代产品才把TPU做对。
It took Google three generations to get the TPU right.
AMD呢，总会是那个备选供应商，而你确实需要一个备选。
And then AMD will, you know, will always be kind of the second source, and you need a second source.
好吧。
Alright.
真让人兴奋。
Exciting.
你觉得接下来会发生什么？
What do you think happens okay.
我想回到商业模式上来。
So I wanna go back to business models.
现在大家广泛讨论的一个大话题是颠覆性力量，而在座的大多数CEO都是初创公司的创始人，你们的目标要么是挑战现有巨头，要么是开拓全新的市场机会。
So one of the big things that is widely discussed is, like, you know, source of disruption, and most of the CEOs in this room are CEOs of startups who are trying to go beat some incumbent or find, you know, some new market opportunity.
最有可能成功的机遇，往往出现在重大平台变革的同时，伴随着商业模式的革新。
And the most ripe opportunities tend to come when you have a big platform shift that is also accompanied with a business model shift.
我能想到几个这样的领域。
And so there are a couple of areas where I can see it.
我觉得这一点很明显。
I feel like in an obvious way.
比如我们投资了Decagon，做客户支持的，你很容易看出一种按任务解决效果来定价的商业模式，因为效果完全可以量化。
So, you know, we're investors in Decagon, customer support, like you can pretty easily see a business model that is priced on the resolution of a task because it's so measurable.
你看，比如在编程领域，商业模式现在大多转向了按使用付费，尤其是面向开发者的产品，这种模式已经很成熟了。
You can see, you know, like in coding, like a lot of the business model has now shifted to consumption and, you know, obviously, especially for developer facing things like that's comfortable and pretty well known.
那其他行业呢？
What about the rest of the industry?
我总觉得现在大家在那儿空谈，说什么我们要全面转向服务化。
Because I feel like there's sort of this hand wave thing that is going on, which is like, we're gonna go get all of services.
但问题是，你到底该怎么实际操作呢？
But it's like, okay, so how do you actually go do that?
这事儿没那么容易。
It's gonna be pretty hard.
那你有没有预测过，这事最后会怎么发展？
So do you have any prediction on how that plays out?
我觉得客户支持领域就是一个很明显的例子，我们手上有大量的文本数据。
Well, I think what you're seeing in customer service, which is kind of like an easy first example, we have a lot of textual data.
大语言模型在处理文本方面确实很在行。
The LLMs are good at text.
你可以轻松地用强化学习来确保系统获得良好的反馈奖励，比如客户满意、一次解决率之类的。
You can kind of, you know, probably really easily run some RL to make sure that they, you know, get a good verified reward, you know, verified reward being happy customer or first call resolution or whatever it is.
但我相信这种趋势一定会显现出来。
And but I do think you will see that played out.
人类本来就是按结果拿报酬的，而很多AI会辅助甚至取代部分人类，未来报酬也会更多地和实际成果挂钩。
Like, humans were fundamentally played for paid paid based on outcomes, and a lot of AI will be augmenting humans, but probably also replacing some humans, and that will involve being paid paid for outcomes.
说到消费端的商业模式，现在大家都在谈推广分成。
You know, going back to the consumer business model, you know, everybody's talking about affiliate fees.
我肯定也会有自己的AI助手。
And for sure, I'm gonna have, you know, my own AI.
它会是Grok的一个版本，毕竟我们都曾是AI公司的股东。
It will be a version of Grok because we're both ex AI shareholders.
它会是了解我、喜欢我的Grok版本。
It will be a version of Grok that knows me and it likes me.
下次我想去度假时，它就会记得我喜欢住哪些酒店，然后说：‘这里有三家不错的选择。’
And, you know, when I when I wanna you know, the next time I wanna go on vacation, it will know the hotels that I like to go to and it'll say, hey, three hotels.
我这边有加文，他提供的价格最划算，房间也最好。
I have Gavin, you know, I have Gavin coming who's got the best price and the best room.
他会大大提升你给贝基的礼物档次。
He's gonna massively upgrade the gifts that you give to Becky.
没错。
Yes.
贝基在观众里提到，她特别喜欢你那个《呆呆和笨笨》的梗。
Case she's As Becky Becky said the audience, she really appreciated your dumb and dumber reference.
我会让你知道的。
I'll have you know.
不过呢。
But yeah.
然后可能会有一些推广分成费用。
And then there will probably be some sort of affiliate fee.
这其实就是按结果付费，把整个闭环给补上，但这种模式可能有点退化——毕竟，谷歌当初为啥没搞个电商平台呢？
And, that's just being paid for an outcome and kind of closing that loop, which will be probably a little bit of a business model degradation because the great why why did Google never start a marketplace?
因为人们一旦通过谷歌拿到了客户，就会系统性地高估自己留住客户的本事。
Because people overvalue systematically their ability once they've acquired a customer through Google to keep it as an organic customer.
所以他们总是付太多钱，还一直这么干。
So they systematically overpay, and they continue doing that.
这就是为什么谷歌从来没做成果导向或电商平台——广告让广告主总是付过头钱。
That's why Google never went to outcomes or marketplace because advertising leads to the advertisers systematically overpaying.
这种低效迟早会被挤掉。
So that inefficiency will be squeezed out.
不过，我们还是会转向成果导向的模式。
But, yeah, we'll go to outcomes.
你知道吗，我觉得埃隆今天发推说，以后工作可能就变成可选的了。
And, you know, I think Elon tweeted today that, you know, work would become optional.
就是说，
You know?
比如买菜，你不用非得去超市，想的话自己种个菜园就行。
Like, instead of buying your vegetables, you know, at a at a supermarket, you can grow your own garden if you want.
现在谁也不知道我们得花多久才能达到那个阶段，但以这项技术的威力来看，我觉得这根本不算离谱。
Now who knows how long it takes us to get there, but I that doesn't sound wildly implausible to me for how powerful this technology is.
就在两天前，卡帕西蒂之类的人说AGI还需要十年，结果就被当成怀疑论者了，这真让我吃惊。
Was just struck, Karpathy, you know, whatever, two days ago, you know, is being painted as, like, a skeptic for saying AGI is ten years away.
你开玩笑吧？
Are you kidding?
太离谱了。
Insane.
十年？
Ten years?
是啊。
Yeah.
这简直不可思议。
That's wild.
没错。
Yeah.
算我一个。
Sign me up.
我们大多数人觉得时间会更短。
Most of we have shorter timelines.
得了吧。
Please.
是的。
Yeah.
嗯，其实不是。
Well, so no.
这太棒了。
That's awesome.
说到这些令人兴奋的未来科技，比如机器人，你对
While we're on the topic of, like, very exciting futuristic things, robotics, do you have
有什么看法吗？
a view on Yeah.
这可是真事儿。
Very real.
以后特斯拉和中国车企肯定会正面较量。
And it's gonna be Tesla versus the Chinese in in cars.
电动汽车。
Electric cars.
对。
Yeah.
没错。
Yeah.
我就说汽车就行，不用特指电动汽车。
I would just say cars, not electric cars.
是的。
Yeah.
汽车。
Cars.
对。
Yeah.
你有时间上的概念吗？
Do you have a sense of timeline?
我的意思是，你完全可以看看Optimus的视频。
I mean, you can you can all watch the Optimus videos.
我认识的每一个机器人专家都特别佩服。
Every roboticist I know is extremely impressed.
其实现在有个很大的争议。
You know, there's there's a giant debate.
是该做类人机器人，还是非类人机器人？
Is it gonna be humanoids or not humanoids?
我觉得这个争议已经结束了，因为类人机器人可以通过看YouTube视频来学习，人穿上动作服给机器人做示范，也更容易上手。
I think that debate is over because humanoids can kind of learn, you know, from watching YouTube videos and that it's easier for a human being, you know, to put on a suit and show the robot how to do it.
你看看那个视频，五十个Optimus机器人同时做五十种不同的任务，其实原理特别简单。
I mean, it's kinda crazy to watch the video of all the, you know, the 50 Optimus robots doing 50 different tasks, and then it's very simple.
你知道吧？
You know?
你把玻璃杯放进洗碗机里了吗？
Did you did you put the glass in
放对了吗？
the dishwasher correctly or not?
这太有趣了，加文。
This is so fun, Gavin.
我每次和你聊天都很开心。
I I always love chatting with you.
给加文鼓个掌吧。
Let's give a hand to Gavin.
谢谢，大卫。
Thank you, David.
谢谢。
Thank you.
谢谢
Thanks
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