《黄仁勋离任或将永远改变AI行业》— Dylan Patel
- 黄仁勋若离任,英伟达的决策速度、供应链议价能力和客户融资都将同时承压。 谈及有关黄仁勋与中国关系的指控,Patel认为,很难有人接替他协调这些事务。若把决策交给委员会,“那只会让决策变慢”。
- 在英伟达之外,Patel认为开源将是最大输家。 英伟达支持美国的开放模型开发者,而对华限制收紧可能冲击另一个重要的开放权重来源。Anthropic相对占优:Patel称其对英伟达的依赖不超过三分之一,而OpenAI超过90%,并总结道:“总体而言,闭源正在胜出。”
- 风险从模型供应延伸到获取算力所需的融资。 Patel追问,推理服务商没有信贷、兜底支持和持续进步的开源模型,如何将营收从10亿美元做到100亿美元。他称黄仁勋是“创投生态最有力的盟友”,同时质疑英伟达是否还会像过去一样积极。
- Patel支持收紧对华硬件管制,同时保留部分云端访问。 他认为,Google向字节跳动出租芯片,既能保留美国的控制权、赚取利润,也提出了可对部分芯片公司的出租业务设限。前沿模型生成的数据可能成为转移能力的另一条渠道,受到审查。中国也有反制筹码,因为美国AI服务器包含中国零部件:“中国想停就能停。”
- Patel对《AI 2027》的判断转趋积极,但仍对技术扩散存疑。 他说,截至当年,该报告可核实的预测约70%已被证明准确,尽管他起初认为这“有点过于大胆”。递归式自我改进“看起来越来越可能”,但中国的应对会带来供应链风险。
- GDPX显示,编程和芯片设计能力大幅提升,其他领域进展则弱得多。 一位主持人谨慎地将受测模型称为“Mythos 5.2”,并提到约16%;Patel强调,领域专属的强化学习环境和数据至关重要。他对有价值的数据供应商给出的判断是:“是专家。就是专家。”
1. 黄仁勋离任将暴露英伟达的协调难题
- 主持人将有关黄仁勋与中国关系的指控称为“黑天鹅”,随后追问没有他坐镇,英伟达还能否维持交易推进能力。一位主持人原以为,至少未来一年黄仁勋会阻止任何估值超过100亿美元的AI公司倒闭,部分原因是要避免出现负面头条。Patel担心决策权转移到委员会:“那只会让决策变慢。”
- 被问及黄仁勋是否亲自设计芯片架构时,Patel说并非如此;他的作用是在多个选项之间推动英伟达作出取舍,并在某个方案行不通时“立刻转向”。他举了Volta为例:在流片前约3个月加入了Tensor Cores。他认为,如果把这项改动推迟到下一代,英伟达就无法确立AI领域的主导地位。
- 供应链议价能力同样高度依赖个人。Patel怀疑,继任者能否以低于市场价的条件拿到供应商60%–70%的产能。谈到Nikesh Arora时,他质疑在Palo Alto积累的硬件经验,能否转化为与Google、Amazon、AMD及前沿实验室芯片团队竞争的能力。“这些人是真有本事。”
- 对英伟达内部人选,Patel看好Ian Buck和Jonah Alben,认为Alben最接近技术负责人;提拔他们中的任何一位,都可能削弱他们目前负责的工作。他更偏好的外部人选是Broadcom的Charlie Kawwas和Apple硬件负责人Johnny Srouji,两人都精通技术与供应链。他说,Hock Tan或Lisa Su会是更好的人选,但他不认为两人会接下这个职位。
2. 开放模型与创投融资都依赖英伟达兜底
- Patel说,没有黄仁勋,“美国开源就不会存在”,并举出英伟达对Reflection和Thinking Machines的支持。应用公司和推理服务商也依赖中国开放模型。如果限制收紧,他质疑这些模型能否继续进步、开发者是否还会公开所有内容:“我认为最大的输家肯定是开源生态。”
- 硬件多元化会改变各家的风险敞口。Patel说,智谱支持7种中国加速器,DeepSeek与华为合作密切;依赖英伟达的中国实验室,处境不如硬件来源多元的同行。类似的对比也让Anthropic胜过OpenAI:他称OpenAI对英伟达的依赖超过90%,Anthropic则不超过三分之一。开源竞争减弱,也会让Anthropic受益。
- Patel认同,随着大型实验室公司逼近上市,创投投资人正逐渐退出这笔交易;OpenAI“可能刚完成最后一轮融资”。下游公司仍离不开融资。他追问,Baseten、Fireworks及同类公司如果没有算力、信贷和兜底支持,如何把营收从10亿美元做到100亿美元;中国模型持续进步也是它们需要的条件之一。
- Patel的框架是,应用层公司的关键在于能否掌控底层模型。Harvey、Sierra这类公司如果被迫使用闭源模型,就会沦为套壳产品;如果使用开放模型,同时掌握客户关系,就能拥有另一种竞争位置。黄仁勋是“创投生态最有力的盟友”,但Patel不确定英伟达今后是否还会像过去一样积极投资。
3. 对华限制或将从硬件延伸到训练数据
- Patel不愿对Mercor单独作出预测,但说许多数据公司有大量业务面向中国。它们会用前沿模型生成、提取和筛选材料,包括环境数据。出售这类产出,等于间接转移信息:“这和传统的蒸馏不一样。”他预计,芯片销售与出租将受到更严格审查;此前主要聚焦硬件的限制范围,也可能纳入数据。
- 他主张限制芯片出货、TSMC和存储器公司的销售,以及先进芯片制造设备,并认为数据也可能成为限制对象。他建议不要普遍限制芯片出租,同时提出可对Megaspeed等芯片公司的出租业务设限,随后又补充说明这一建议仍需斟酌。Google可以在需要或接到指示时收回出租给字节跳动的芯片,同时收取利润,让字节跳动相较Meta盈利能力更弱。目标是:“如何让美国赢。”
- 对于主持人所说的“蜜罐”说法,Patel表示,他不认为涉事女性是间谍,也不认为她属于“狭义上的蜜罐”,并将其描述为一位人脉广泛的商界人士。他认为,这类关系可能带来配合情报机构工作的压力。至于黄仁勋是否违法,Patel称:“我不知道。”
4. 《AI 2027》预测渐显可信,中国让发展路径更复杂
- 一位主持人认为,AI能力的发展正紧贴《AI 2027》的预测,并询问报告对2026年11月中国“醒悟”的预测。Patel说,尽管他对AI一直非常乐观,起初仍觉得这个情景“有点过于大胆”。他说,截至当年,报告中约70%可核实的预测已被证明准确。他仍对技术扩散持怀疑态度,但递归式自我改进看起来越来越可能。
- 另一位主持人反驳称,把GPU留在香港似乎意味着中国的发展时间线更长。Patel认为,中国显著加速的可能性很高,但警告不要让限制政策摆向不加区分的另一端:每台Nvidia服务器和Google TPU服务器都包含中国零部件。北京可以切断这类供应,这也引出一个问题:需要保留多少最低限度的访问,才能避免对方报复?
5. GDPX表明,专业数据是能力继续提升的关键
- 一位主持人谨慎地将模型称为“Mythos 5.2”,并提到它在GDPX上的表现约为16%。Patel说,他测试Anthropic的模型花了约2天,发现软件工程和芯片设计能力有了显著提升。他起初称其他领域毫无进步,随后修正说,这些领域“也都有小幅提升”。
- Patel的解释是,强化学习环境决定哪些能力可以扩展:没有独特的数据和环境,特定领域就不会进步。Anthropic的芯片研发说明了这一变化。他说,以前做芯片看起来太慢,赶不上AGI的发展;现在则是“模型可以造芯片”。单纯扩大规模不会让所有基准测试都提升:“真正需要扩展的是技术、算法和数据。”
- 被问及数据是来自产品工具链还是数据经纪商时,Patel说,据他了解,Anthropic购买的芯片设计数据很少,而是自行构建数据。生物学领域则两种方式并用:公司通过自有湿实验室收集数据,同时也大量采购外部数据。不同领域适合不同的内外部数据获取策略。
- 随着模型进步,只负责把实验室和勉强合格的标注人员对接起来的通用供应商,价值正在下降。“是专家。就是专家。”Patel认为,生产专业材料科学数据之类的业务有机会做大,但最终能扩展到多大仍未可知:“这到底能扩展到多大?”
完整逐字稿
And we have Dylan Patel from SemiAnalysis coming back on the show. We missed him. It’s been over a week since we hung out with him. Is that a—
And he’s not—
Is that a foldable?
No, it’s not a Duo. It’s a Samsung.
Oh, Samsung. Living in the future. How long have you had that?
I’ve had foldables for three or four years.
Wow.
Ahead of the curve.
Truly.
Ahead of the curve, always.
Truly. What is your Duo review? Is that gonna be enough to pull you over? Were you only in—
iPhone Air.
iPhone Air? Okay.
iPhone Air.
Okay.
Foldable Samsung. This is the elite class.
Oh, two phones.
You know?
You’re—
The priestly class.
This is screaming a firewall between the investing arm and the research arm here.
One for—
This is secure.
One for work, you know?
Yeah.
One for work.
Okay, okay, okay.
One for personal.
Okay. There we go. There we go.
Good.
Well—
Good.
I am afraid to say that both Jordy and both of you guys, Jon and Jordy, only have this phone number, not this one.
Ooh.
Ooh. Wow.
We’ll have to fix that.
Wow.
We’ll have to fix that.
Wow.
To be fair, I only have this one.
I’m updating my priors.
Three or four months ago. Yeah.
No.
I’m updating our priors on our friendship. I thought I was texting the personal the whole time.
Wow.
I thought we were like that.
Like that.
Look, look.
Is this—
Only Chinese friends have this one.
Okay, okay.
—
Stay safe out there.
1. The Black Swan Nobody Saw
Do you guys try to predict black swans? It’s effectively impossible by definition, but I found myself two weeks ago thinking—
Hm.
Actually trying to rack my brain on what the most unpredictable outlier scenario could be that changes the game on the field. I think we got it. Unfortunately, I didn’t—
What were your guesses?
I don’t know. I think a lot of them were much more around individual players in the financial web of the entire trade, but—
Well, the big one that everyone’s been waiting for is some result from the next training run that shows there’s not another leg up beyond coding, that there is something—that taste is the new mode. For so many white-collar jobs, it really does matter that you can sit across the table from someone and shake their hand. We’re never gonna replace the lawyer or the doctor, or even augment them to the tune of—because you don’t even need to do the job displacement thing. It’s just the fact that a software engineer can deploy $100,000 worth of AI in a year without people blinking. That hasn’t happened for the marketer or the salesperson yet. If that does happen, the revenues do go to a trillion dollars. But if it doesn’t—
I don’t know if it’s a black swan, though. That’s not a—
No, it’s not a black swan.
That’s a—
That… yeah, that—
I think that’s something we can all debate, right?
Exactly.
Yeah, yeah.
Exactly.
No, but another thing I would say is, I was very confident that at least for the next year, Jensen would not let an AI company valued at north of $10 billion fail. Period. He was like, “I don’t—I’m not gonna have that headline. I have the ability to give any company a meaningful up round and keep everyone in the game.” A lot of people want the headline. Even though, in the grand scheme of things right now, a $20 billion company could go to zero and it wouldn’t really have that much impact, it didn’t feel like Jensen would even tolerate that kind of headline, just because the bears would sink their teeth into it and have a nice, tasty meal.
Yeah.
Yeah. I think the black swan is this, right? We’ve all predicted all sorts of things.
Totally.
Even with all the knowledge and insight and rumors. I’d even heard rumors, which I didn’t put much credit to, but people in the industry would be like, “Oh, yeah, Jensen does this with someone at Nvidia.” And I was like—
Whoa.
Palmer Luckey.
No, no, no. At Nvidia.
No, but that’s another—
Like, I—
Yeah.
That’s another thing we’ve been asking.
Well, you would never predict it, right?
No, never.
And you don’t—you hear something—
And certainly not to this extreme degree.
It’s impacting.
There have been plenty of other—
You hear rumors of stuff impacting.
This is so different than the Bezos story, so different than the Gates story, so different than the Elon story. It is so entwined with the actual business and the business dealings and geopolitics and domestic politics.
Well, Elon has slept with employees.
But not to this—
Not with his wife.
Yeah.
But his get-out-of-jail-free card is that he has 15 baby mamas, so you can’t pin that on—
Yeah.
Yep.
And he has a lot more control. I think the question that we’ve been asking ourselves—
Way, yeah, way more control.
We’ve been asking ourselves: on October 10th, 2025—
Hm.
We specifically named—
About Alice.
Megaspeed. We specifically named Alice Huang. We talked about how the whole situation was suspect. A lot of the details were basically out—
Yeah.
In the open, and all these videos were public. You could read into the videos and be like, “All right, this looks like, at the very least, a pretty close relationship.”
Mm-hmm.
Some of these videos have his wife and his daughter in the same room, right? That’s the thing that’s shocking.
Yeah, yeah, yeah, which kind of meant the basic analysis was like, “Okay, well, if the whole family’s there, probably nothing’s happening. Maybe this is purely—maybe he’s the purely rational economic actor. He’s playing it as aggressively as you can to grow the business internationally.” We don’t like that from a chip export position. If you’re a China hawk, you don’t like that. But there is the letter of the law, and we rarely—CEOs don’t get fired for pushing it right up to the letter of the law. If you’re selling the absolute max, like the H20, which was designed to get around the chip exports, a lot of China hawks didn’t like that, but they were like, “Ah, that’s the letter of the law. You found the loophole. You found the edge.” It is just a complete black swan in that it’s so much further than what anyone could see.
Yeah. So overall—
Total lack of judgment, just given that this guy, for as many friends as he has, has seemingly an equal amount of enemies that stand to benefit from this. What do you think happens to the Nvidia AI central bank deal pipeline?
Mm.
I assume—
Yeah, so I mean, I think—
I assume if you’re a number of these companies, you can’t lean on, “Oh yeah, Jensen wanted to do $2 billion,” and now it seems like those investments, when it comes time to actually sign the docs, will probably be going to committee.
2. Nvidia Without Jensen
Some things are gonna change. Yeah, I think that’s the biggest worry for Nvidia: now it’s a committee of people doing stuff, and that’s just gonna make decisions slow. Technically, they could fall behind because of this. Obviously, the other big aspect—there are three main things, right? There’s the technical side. Nvidia’s so ingrained in helping make decisions there. There’s no one clear technical lead. Maybe Jonah is, but there are a lot of people who are also directly reporting to Jensen doing technical stuff, so it’s hard to move as fast. Supply chain-wise, Nvidia wants to make aggressive things, do aggressive things, lock up supply, convince the supply chain to do things they’ve never done before in terms of technology and supply, and lock it up to Nvidia. That’s probably a lot harder to do, given whoever the CEO is probably isn’t as charismatic as Jensen. They’re not gonna be like, “Yeah, sure, Nvidia, you can have 60% or 70% of my capacity,” at a price that’s below market rate.
That’s probably tough. The third leg is that Nvidia is propping up a lot of things in the supply chain. Open source in America would not exist without Jensen. Both Reflection and Thinking Machines are pushing the open-source frontier in America, and both have massive investments and backing from Nvidia, as do many other companies across the ecosystem. All these application companies rely on open models, whether it’s Harvey, Instinct, or Sierra. They all use open models.
Yeah.
All the inference providers, including multiple companies worth more than $10 billion, rely on open models from China. If we’re slamming the hammer down on China much harder now because Jensen and his team were the biggest defenders against restrictions, what happens next? Their credibility is out the window, and they’re being investigated and subpoenaed. There are going to be a lot more restrictions. Will Chinese models continue to progress at their current pace? If they do, will they open-source everything? These are real questions. I think the open-source ecosystem is the biggest loser, for sure.
How do you think about the technical role of the CEO at Nvidia? You see Jensen making deals, at events, on podcasts, and in the news. If there’s deep technical work happening, it’s behind the scenes. How real is his involvement? Is he involved in the architecture of the next chip, or is his technical role more about recruiting and finding the next generation of great technologists?
I mean, he’s no doubt inspiring people and bringing them in. He’s not designing the architecture. But when there’s a decision to make, I think the common thing everyone following Nvidia sees is that you hear valid arguments for options A, B, and C. Nvidia could be doing all three at once, and then at the last second, Jensen puts all his weight behind one.
Mm.
If there are options A, B, C, and D, which one gets chosen? Is it a committee? Who’s deciding? Who chooses A and gets all the suppliers working on B and C to not be pissed off and actually push behind A?
Oh, yeah, that’s the founder mode thing.
And if A starts fucking up, you switch to B on a dime.
Switch to B, yeah. That’s really hard.
Those are the kinds of things.
I remember at one point at Meta, they had two different operating systems for their virtual reality strategy. They had XR and AR and VR or something, and it was just so much extra work. Then Zuck had to go into founder mode and say, “Look, some people are going to get reassigned. There are going to be some layoffs. It’s going to be aggressive.” That’s the benefit of a founder-mode company. Who’s on the shortlist of potential successors? Can Colette not do it? Does she not want it? How does this develop from here?
I’m not sure what Colette wants. I think she’s awesome, but at the end of the day, she can’t lead the company technically.
Sure.
I think the 2 people internally best suited would be Ian Buck and Jonah Alben. Ian is great. Jonah isn’t as much in the public eye, but technically he’s closest to the leader and is in charge of most of the technical organizations. Those are the 2 most important people from that perspective.
Ian is charismatic and probably pretty good at wheeling and dealing, though not nearly as good as Jensen. But will he be as good on the technical side or the supply-chain side? And will Jonah be good on the supply-chain side or at wheeling and dealing? I don’t know if someone can be propped up to take over Jensen’s role like that. If Jonah or Ian is in charge, does the work they were responsible for fall down to some extent, in terms of the focus they gave it and the relentless effort?
My favorite picks for CEO would be external. They would be Charlie Kawwas and Johnny Srouji. Charlie is number 2 at Broadcom and has been for a long time. He’s fucking awesome. Johnny is the head of hardware at Apple, and he’s basically led the chips team and strategy. Those are the only 2 people in the world I think can navigate a supply chain and technical details like that. Obviously, it would be better if it were Hock Tan or Lisa Su, but I don’t think either of them would do it.
What about leaders from the Trainium or TPU organizations? You’re highlighting Apple, but there are plenty of people leading huge semiconductor efforts who are still 2 rungs below the CEO or founder. This would be an opportunity.
Andy Jassy was the one who wanted to buy Annapurna Labs.
Yeah.
He’s not going to leave his job as Amazon CEO to be Nvidia CEO. You take a few steps down, and I think there are really great people there. I love the teams at Amazon. They work and move super fast.
Yeah.
I think Google’s awesome, but I don’t think they have a single person who can do all of the above. If anything, I think Amin Vahdat at Google leads all this infrastructure stuff, but I don’t know if he’d want to do this. I’ve never asked him; I just have a feeling he wouldn’t. I also have a feeling the leaders of Trainium want to stay in the background. I know they very much want to be in the background on all the Amazon chip stuff. I don’t think they want to do this.
Yeah. What about a wildcard? Sean Maguire was throwing out Nikesh Arora, someone who’s already in the CEO seat but isn’t running a trillion-dollar company. Do you have any expectations?
A humble, you know, just a couple hundred billion.
A tiny company, right?
I don’t know Nikesh too well. I’ve met him once. I think he’s awesome, but technically, Palo Alto has shipped hardware. That’s definitely part of their business. But is it the same thing? Is it Nvidia leading edge, doing crazy stuff? Look at Blackwell. Blackwell was amazing. If they hadn’t done what they did with Blackwell, they would’ve lost a lot of market share. They decided at the last second what to do.
With Volta, they decided to add the Tensor Core about 3 months before they taped it out. Who would’ve said, “Yeah, let’s just push out the current thing. Let’s add it into the current thing”? They would’ve said, “Let’s add it to the next thing.”
Yep. Totally.
If they’d added it to the next thing, how much further behind would they have been in AI? Nvidia never would’ve established dominance. These are technical decisions. And it’s not like you’re fighting—no knocks against Palo Alto Networks, but their competitors aren’t that amazing—whereas Nvidia is fighting an OpenAI chip team, a Broadcom chip team, a Google chip team, an Anthropic chip team, and a Meta chip team.
TPUs.
Amazon’s chip team, too. These guys are fucking good, as is AMD. They’re all really good, and so are all these startups.
That’s what I wanted to ask you about.
If you look at the startups, they’re all good. It’s not like they’re incompetent. It’s very different. As great as Lisa Su is, she took down Intel, which was incompetent. What is it like to be the person who defined and created a category and kept all the invaders at bay? That’s very different from being in second place or making smart tactical business decisions and innovating once a category is already established.
It’s just very different.
Mm-hmm.
How do you think Chinese labs are reacting and updating their road maps?
It’s an open secret that the Chinese labs are working super closely with Nvidia. Even if Nvidia isn’t selling them chips directly, engineers from both the U.S. and Nvidia’s Shanghai offices are constantly going to these labs, talking to them, and helping them optimize—
Mm-hmm.
—understanding what they’re doing and bringing those optimizations over to Nvidia’s software stack and open source. I think the Chinese labs have already started updating. Companies like Zhipu, which is sanctioned, and DeepSeek are heavy users of different types of chips. Zhipu supports 7 different Chinese accelerators. They’re not as good as Nvidia’s, but they work. DeepSeek is super close with Huawei.
There have probably been a lot of updates to their priors. The Chinese labs that relied heavily on Nvidia are probably weaker now than the labs that were already diversifying. I think the same applies to Anthropic versus OpenAI. Obviously, OpenAI has its own chip and has been working on it longer, but it’s more than 90% Nvidia, whereas Anthropic is one-third or less Nvidia.
Mm-hmm.
So it’s a completely different level of impact on them. OpenAI works more closely with Nvidia than Anthropic does. This is a positive for Anthropic versus OpenAI. Anthropic is pushing back on open source, and open source being weaker now is great for Anthropic.
Yeah.
These sorts of things flow through not just the Chinese labs, but also the American labs. In general, closed source is winning.
Yeah, yeah, that makes a lot of sense.
Any predictions on how this will impact Mercor and various data companies, given that there’s going to be more scrutiny on basically any type of business relationship with China?
I don’t know about Mercor specifically, but I do know a lot of the data companies sell tons of data to China. It’s actually a really funny way to distill this: even if the Chinese labs don’t directly have the closed-source models, some of their biggest customers are the data companies, like Mercor and so on. They generate data, and their pipelines for generating data involve a lot of language models from the frontier labs for extracting, filtering, and all that. If you’re making environments or whatever with these frontier models and selling them to China, in some way, you’re kind of distilling the information out of them. It’s not traditional distillation.
I imagine selling chips to China is going to get a lot more scrutiny. Renting chips to China through clouds is going to get a lot more scrutiny. Selling data hasn’t had any scrutiny yet, and it probably will. Right now, people focus on hardware, but—
Mm-hmm.
—and Jensen and all the people at Nvidia who were defending Lutnick and David Sacks, and all these people who were sort of preventing some of the restrictions on Nvidia in China—
Mm-hmm.
—are heavily discredited now, especially Lutnick and Jensen.
Mm.
In any argument to allow China to have some stuff, we’ve been in favor of certain types of restrictions for years. It’s been our biggest point of contention with Nvidia. I think they really dislike that. They could understand when we were excited about AMD or Google, and viewed that as, “We can out-engineer them.” But when it came to China, it was a different matter.
Now the cover is gone. I kind of hope the government is smart with the restrictions. Make sure chips of certain kinds don’t get sold. Really ironclad. Make sure TSMC and memory companies don’t sell to China. Make sure high-end equipment for making chips doesn’t go to China. Maybe have some restrictions around data. But don’t restrict renting chips.
There’s a whole waterfall of options around renting chips from, let’s say, hyperscalers. Maybe restrict random chip companies like Megaspeed from renting chips to China.
Yeah.
Or diverting them. But maybe not that. If Google is going to rent to ByteDance, maybe that makes sense, because Google can always pull away the chips when it needs to.
Yeah.
Or if the government tells them to. Google can always charge ByteDance a much higher margin, making ByteDance less profitable than Meta. These are the sorts of things that are relevant for U.S. competition and leadership. Hopefully, all the restrictions aren’t just rash actions as the pendulum swings. Hopefully, the focus is on how to make America win.
Yeah, no, I like it. I remember when you branded yourself not as a China hawk, but as a bald eagle. I thought that was a good way to put it. How are you reflecting on—
The video you guys made is so good. We’ve got to repost that.
Yeah, we’ve got to repost that today. How are you reflecting on the predictions in AI 2027? When I look at the model capabilities, I feel like it’s incredibly accurate. We’re completely on track. Huge congratulations to the whole forecasting team there.
I’m still a little uncertain about 2 predictions. One is that they forecast there would be a 100,000-person anti-AI protest. The midterms were kind of that, so I think the midterms might stave off a little bit of that. But the more interesting question is that around this time, AI 2027 predicts that, around November 2026, China wakes up. I’ve been interrogating that. It’s very hard to get accurate data. How do you feel we’re progressing along the line of China waking up? Is this an example of China waking up because they’re honeypotting our most powerful AI CEO, or are they—
Or—
—still asleep?
The other side of that, John, is that there’s always a possibility that they believe Nvidia chips have back doors in them, and—
Hmm. Oh, they don’t want them there. Okay, yeah.
—and Jensen is the asset.
Yeah, there are a million tinfoil hats—
No, but it doesn’t seem like you’re waking up if you’re saying, “Hey, there are a bunch of GPUs in Hong Kong, but keep them there. We don’t want them in here.”
That’s a good point. Yeah, how have you been processing that?
That makes you think there’s—
Yeah.
—some group that has much longer timelines.
Yeah.
As far as AI 2027, I’m very AI-pilled, and I thought AI 2027 was a big stretch. But it turns out 70% of the things they’ve predicted so far this year that we can verify have turned out to be accurate.
Yep.
Which is incredible.
Incredible.
Right? Wow.
Incredible. Yeah.
I’m still skeptical on some of the diffusion aspects, but I think RSI is looking more and more true.
Yep.
China waking up is probably a big likelihood.
Mm-hmm.
That’s the other thing, right? If we go too gung-ho with the pendulum of banning stuff in China, does China swing its pendulum and prevent the supply chain? Every Nvidia server has China content.
Sure.
Every Google TPU server has China content.
Yeah.
Every one of these things has China content. China can stop it if it wants.
So there’s some level of, “What’s the minimal amount of stuff you can give China in AI, and give them in everywhere else, to prevent them from cutting off the supply chain?” That’s a view of the world that could be construed.
As far as China waking up, it’s probably possible. On another thing you mentioned, China honeypotting Jensen, I actually don’t think she’s a spy in the colloquial sense.
Yeah.
And I don’t think she’s a honeypot in the colloquial sense.
Okay.
She’s a well-connected individual in the Chinese business world, and her family is well-connected. If you’re well-connected in China—hell, if you’re well-connected in America—you’ll talk to intelligence agencies when they tell you to, and you’ll tell them the stuff they want to hear. I just don’t think people are going to say no.
There’s just a lot of pressure there.
Yeah. The CIA was asking me for your personal phone number, and I had to tell them to take a hike. It was brutal. We gotta—
I only got this phone a few months ago.
—we gotta figure out where he got that jacket. John, can you get us Dylan Patel’s personal phone number? And I said, “Look, I’m kind of second fiddle in his world.”
Yeah.
Yeah.
Just a professional connection.
This was my personal and work phone up until a few months ago.
Okay, okay. I’m a little less hurt. No.
But anyway, I think—
Yeah.
—I think they were getting some information, right? She was clearly showing everyone on WeChat that she’s close to Jensen and can get them chips in China.
Yeah.
Jensen—did he know? Probably. I mean, I don’t know, but he probably knew.
Yeah.
But Supermicro didn’t have to honeypot Jensen to ship billions of dollars of servers to China.
Yeah, totally.
Right? I think there’s a lot more to this story than—
That we know of. It still hasn’t come out. They might have been having an affair. We don’t know. Let’s not jump to conclusions.
I’m sure, I’m sure.
Anyway, what does this mean for the venture capital community? We’ve seen a lot of VCs rallying around Jensen. Is that purely because of the open-source ecosystem? What does it mean for the other… I mean, you mentioned wrapper companies, but are VCs effectively out of the big lab trade, and is that why they’re rallying around Jensen a little bit more than you’d expect?
Before I answer that question, Jensen has the… It depends on how bad this stuff is, right?
Mm-hmm.
There’s a lot of information coming out. I don’t know.
Yeah.
But if their China stuff is really gung-ho, what if Jensen just goes to China and starts a—
Whoa.
—$100 billion raid? I don’t know. That’s a wild card. I don’t know how it gets stopped.
But why would he not go to Taiwan in that situation?
Well, because the U.S. still has interests in Taiwan, I guess I would say.
Yeah.
I mean, it depends. Did he break laws?
Yeah.
Is he going to be called in front of Congress for months and months and months, berated, and found to have broken laws?
Sure.
I don’t know.
If he didn’t break laws, I think he’s going to St. Barts. We learned that from Bing Lee.
But anyway, as far as the venture ecosystem, you’re totally right. They’re out of the lab trade. The labs are going public. At least OpenAI probably just did their last round.
Yeah.
It wasn’t that great.
Yeah.
And then Anthropic is going public.
Yep.
They got liquidity.
Yeah.
Some of them will… But then everything downstream, right? Like all of these inference clouds—how can they secure compute without credit, financing, and a backstop?
Yeah.
This is a real challenge. Who’s going to be willing to do that? And how do Baseten, Fireworks, and whoever go from a billion dollars of revenue to $10 billion of revenue without access to compute and without Chinese models being continually updated and sold externally?
Yeah.
This is a big challenge and risk. Likewise with companies like Instinct, Harvey, and Sierra, which are making awesome businesses: can they continue to ramp and improve their product’s capabilities, or do they have to turn to closed-source models? If they have to use closed-source models, their product is a wrapper. But if they can switch to open-source models and they own the customer relationship, they’re not a wrapper.
Yeah.
I think this is a big worry. Jensen is the venture ecosystem’s strongest ally, and he’s propped up a lot of companies.
Yeah.
Nvidia is very active in venture and investing, so I don’t know if they’re going to be as active now.
Mm-hmm. I had one last question. Jordy, do you have anything? I think the—
Yeah.
Yeah. Sorry.
I’ll tell you my phone number.
It’s just—
678—
Okay.
—triple nine, 8212.
Wait, what is that from? Is that a regional commercial from Georgia or something?
No, no, no.
No? What is that?
It’s—
Let me look it up.
Yeah.
Is it that song? There’s a song about it, right?
In L.A., we only know Dos Mantis—
There’s a song. 678—
Dos Mantis, Dos Mantis—
—triple nine, 8212.
—accidentes. Okay. I know 867—
Soulja Boy. Soulja Boy.
Oh yeah, Soulja Boy, who’s now an AI spokesperson. He signed with—
Soulja Boy is so cheap to hire. I went on a boat for some startup’s series launch or whatever. They rented a boat. Hiring Soulja Boy cost $25K.
Really?
And he performed for about an hour. He had his whole entourage.
Amazing.
His own DJ came.
We need him at SemiAnalysis CON 2027. Speaking of GDPX, were you surprised by the moderate jump in progress? I saw the 5.2. Was it Mythos 5.2? It got about 16%. It speaks to the quality of the benchmark that it wasn’t immediately 100%, but take me through your reaction to the results.
Yeah. GDPX in our benchmark we launched.
Yeah.
We tested Anthropic’s model and launched it. It took a day or two to run the test—more like two days. It was such a big improvement in some areas: software engineering and chip design.
Okay.
There were areas where it just didn’t improve at all, which was really interesting. It speaks to reinforcement learning environments being the substrate for scaling.
Yep.
If you don’t have unique data and environments in certain spaces, you won’t scale the quality of the model in those places.
Yeah.
Chip design drastically improved, right?
Okay.
I think it speaks to Anthropic’s focus. We just hired a bunch of chip people, and we’re making a chip. We’re making the model way better at chips.
Yep.
In the past, Anthropic’s view was, “We’re not going to make a chip because it’s not an AGI pill. By the time we get a chip out, it’ll be too slow.”
Mm-hmm.
Now the model can make the chip, so I think they’re really accelerating on that front. Likewise, software engineering continues to gain like mad. Anthropic is so much better than everyone else at software engineering and chip design. It’s incredible.
Mm-hmm.
In other areas, they just didn’t improve. I think it speaks to the importance of data, and to these data companies and vendors. It also speaks to the durability of some of these categories. They didn’t improve in some categories at all, and they’re probably not spending a ton of data on them.
Yeah.
Or maybe the benchmark is just so difficult that—well, it did improve slightly in all domains. But generally, scaling size isn’t going to get you improvement in every benchmark.
Yeah.
You really have to scale techniques, algorithms, and data.
3. The Value of Expert Data
On the data side, how much of it is…
How much value is there in the data flywheel, the data that comes through the harness directly and is given to the company, to the lab for free, versus data bought from a broker specifically? Do you have a sense of how valuable each is?
Yeah. We've established a relationship with a lot of the chip design data companies and AI chip design companies. Anthropic, as far as I understand, buys very little of this. They've been building it themselves. That's the only answer, right? How else would they do this?
That makes sense.
But at the same time, in some spaces like bio, Anthropic started its own wet lab. They're collecting data there, but they're also buying a lot of data elsewhere. I think other folks have different strategies in terms of what they build internally and what they build externally. But I think the data vendors are really important. Given that models are getting so good, a general, large-scale data vendor connecting you to a bunch of people who are just data labelers isn't what's valuable, right? It's experts. It's experts. If you're an expert in material science and you're making data there, you can make a great business. But how scalable is that actually going to be?
Totally. Totally. Yeah. Well, we'll find out next time you're on the show. Thank you so much for coming on. We'll let you get back to work. Have a good one.