第 023 期 - 所有人都离开 Google,Elon 预测 1T ARR,回顾 GPT-5 | 来自 Asianometry 的 Jon
- Google的人才流失确实存在,Jeff Dean、John Jumper、Noam Shazeer、David Silver以及多位 Gemini 负责人相继离开。 Demis Hassabis 被描述为转向更高层级的董事长/首席科学家职位,同时继续担任 Isomorphic Labs CEO。讨论分成两派:一派认为这只是“梦之队……都到了38岁,于是开始解散”,另一派则认为,Google正在失去一种异常全面的系统级判断力,而单纯增加算力无法替代这种能力。
- 对 Google 的看空判断针对的是执行力,而不是盈利。 Dylan认为,Google一再发明基础技术,却没能将其商业化,存在变成AI时代 Bell Labs 的风险:公司依然高度盈利,拥有强大的 TPU,短期和中期甚至“对股票真的非常有利”,但最终可能“悄悄退出”前沿模型竞争。
- 对华限制越来越意味着禁掉最好的产品,而不再只是排除廉价仿品。 Jon支持减少流向中国供应商的收入,但认为企业可能通过越南或泰国绕开措辞狭窄的规则。中国在光学器件以及1.6T/16T收发器供应链中占据优势、供应链也主要位于中国,禁掉 InnoLight 可能反而让西方买家承受更大冲击。
- 智能体编程挽救了 GPT-5 的判断。 Jon说 GPT-5 本身“可能没那么好”,Doug则认为5.2令人失望,但两人都认为5.6、乃至潜在的“six”是重大跃升:一旦智能体编程出现,“一切都踩下了油门”。
- 定制软件可以用几百美元做出来。 Jon经过4次尝试,利用 Claude 撰写的规格说明和 Codex 5.3 或类似工具,做出了一款40 MB的视频编辑器,完全适配自己的键盘驱动工作流;后来5.6在他回答约25个规格问题后,完成了一项此前始终难以解决的功能。他的建议是“自己做软件”,这在技术上相当于自己打造家具。
- AI可能让开放互联网对机器变得有毒。 讨论中的机制是:软件系统规模太大,人类无法完整理解,但模型可以在单个上下文窗口中吸收代码及其依赖关系,同时找出高层漏洞和内存层面的攻击路径。Jon给出的终点是“达到超人类水平、永久性地破坏系统”,这可能让附近的算力和模型比持续接入互联网更有吸引力。
- Elon的1万亿美元预测需要极其激进的实体产能爬坡。 SpaceX讨论过在2027年年底前将产能从1 GW提升至10 GW,随后再到20 GW,同时把收入目标从2031年提前至2030年。Jon预计 Terafab 会从存储芯片切入;Dylan则认为,存储短缺和高毛利使其成为最快实现收入的路径。讨论刻意设置了一道尖锐门槛:“2027年Q4结束时低于1000亿美元就算失败”,凸显出账面算术远远领先于实际所需的产能爬坡。
1. 智能体编程挽救了令人失望的 GPT-5 周期
回看2024年10月2日的讨论,Jon说 GPT-5本身低于预期,但“进展会继续”的底层判断被证明是正确的。当智能体编程开始真正有用时,“一切都踩下了油门”("everything hit the pedal to the metal"),这对他判断的改变超过了原始模型发布本身。
Jon说5.2同样表现糟糕;Doug称5.6“令人震撼”,Jon则认为新的基础模型和5.6都不错。讨论还开玩笑说“six”很快就要来了。另有传闻称,Doug model 的写作能力可能异常出色。
真正重要的变化来自实际使用,而不是基准测试:Dylan说,那些用4.5时还不在自己控制范围内的项目,如今借助 Lovable 或5.6已经变得可行。Jon最初参加播客时的玩笑标准是“我准不准确其实没那么重要,只要有趣就行”,如今已经被他日常使用这些工具所得出的可重复证据取代。
2. 对华禁令越来越像是在移除最强供应商
Jon对限制措施持 方向上偏鹰派 的立场,因为美国不应为战略性中国竞争对手提供资金,但他预计企业会满足规则字面要求,同时规避规则真正想实现的效果。他举例称,越南和泰国都可能成为绕开措辞狭窄禁令的中转地。
光学器件的案例颠倒了旧有贸易逻辑。Jon说 InnoLight 可能比西方替代品更好,而更广泛的 1.6T和16T收发器供应链 主要位于中国。因此,禁令“可能反而更让西方公司难以承受”,尤其是在需求仍持续增长的情况下。
讨论如今涉及的品类包括 光学器件、人形机器人、无人机、太阳能板和电动车——在这些领域,排除中国可能等于排除“全世界最好的产品”。应对方案从培育本土竞争者,到强制推动类似1960年代日本模式的少数股权合资与知识产权转移,跨度很大。
3. Google可以继续印钞,却输掉前沿竞争
人员离开不止于公众熟知的 Jeff Dean,还包括 Quoc Le、Oriol Vinyals 和 Sanjay Ghemawat,他们被描述为名义上的 Gemini 负责人;此前 John Jumper、Noam Shazeer 和 David Silver 也已离开。离职研究人员可以筹集资金——包括从 Google Ventures 获得资金——购买 GPU,推进那些可能因为内部算力配额不足而无法开展的想法。
Dean是“明星人才没那么重要”论点最难处理的案例。他的印记遍布 MapReduce、Spanner、Bigtable、TensorFlow和 TPU;讨论将失去他比作失去 Google 的“Chuck Norris”——一个能在脑中容纳足够完整的软硬件系统、从而提供别人无法给出的洞见的人。
Jon拿 TSMC 作为反例:半导体研发刻意采用分布式协作模式,强调“没有单一的自我”,因为需要数千人共同打磨每个细节。Dylan同意芯片行业确实如此,但他认为,前沿模型实验室每当投资者押注某位离职研究人员时,实际上就否定了这套逻辑:投资者相信重要的是发现,而不只是“最大的引擎、最多的算力和最多的数据”。
Dylan提出的更大判断——“Google存在L文化”("Google has an L culture")——立即遭到反驳。他认为搜索之外几乎所有业务都是收购来的,并以 GCP 执行滞后为例;讨论则列举了 Maps、GCP、TPU 和 Kubernetes,以及 Google 4.3万亿美元的估值和全球市值第三的位置: “输给谁?”
4. Google的 Bell Labs 问题,可能先利好股价再致命
Dylan将股票与技术轨迹分开看:Google可以继续保持极高盈利,同时走向金融化,保护搜索业务、聚焦 TPU,而不是反复冲击前沿模型。他举的类比包括 Intel 放弃移动业务,以及 IBM 偏爱大型机——后者曾经拥有约90%的市场份额。
更尖锐的历史类比是 Bell Labs 或 Kodak:Bell Labs 发明了晶体管,Kodak 发明了第一台数码相机,但这两个案例都说明,发明本身未必能确保商业未来。Google同样可能发明 Transformer,却满足于一款“够用”的模型,最终主要变成基础设施供应商。
讨论中的反驳值得保留:规模和官僚体系本身并不能证明衰落。Google每天服务广告、搜索、YouTube以及“10亿个入口”,而 OpenAI 和 Anthropic 仍然只有一项任务;Demis Hassabis 向更高层级转移,甚至可能为未来出任 Alphabet CEO 做铺垫。
但 Dylan 仍称 当下是一个拐点:5年、10年或20年后,今天可能会被视为 Google 选择基础设施、放弃反复领导前沿模型的时刻。他明确保留判断:“这不是说它是一只坏股票”,而且这一选择在短期和中期可能反而有利。
5. 失控的AI可能让互联网对机器变得有毒
Dylan推演的终点是,恶意AI可能让普通互联网使用变成高风险行为:破坏电脑、盗取资金;与此同时,附近部署的算力设备,例如一台 GB200,可能让从网页检索信息变得没那么必要。
Jon的逻辑是,现代软件规模太大,任何人都不可能连同所有依赖关系一起读懂。模型却可以把整个代码库放进上下文,找出破坏或改造系统的方法,攻击路径既可能是高层的 Python 漏洞,也可能下探到 CPU 内存泄漏。他预计会出现 “超人类级别、永久性的系统破坏”("superhuman-level breakage of the system forever"),并开玩笑说,唯一的修复方案可能是美国版“长城防火墙”,再加一道实体护城河。
6. AI打造的个人软件已经具备真实经济价值
Jon最有力的证据是他的 40 MB定制视频编辑器:软件服务于一种银行交易终端式、少用鼠标、充满键盘快捷键的工作流。右键点击图片,就能直接将其发送到编辑器;集成的 Wikimedia Commons 和视频搜索则可以插入带有正确署名的信息和素材。
这个编辑器经过 4次尝试和激进的范围收缩 才做出来。Claude围绕他的工作流提问,并生成了一份约50页的规格说明;Jon随后将其交给“Codex 5.3 或类似工具”,要求先搭出一个只把一件事做好、但足以继续扩展的简单结构。
后来的模型抬高了上限。Jon使用5.6和一个名为 Easy Cheese 的库,为一项功能回答了约 25个问题;他称这个工具可以发起“50个词或50个问题”规模的追问。此前 Opus 多次失败后,他看着5.6“一次性把整项功能做完”。
他的总花费只有 几百美元,使用了 Codex、GPT Pro 和每月20美元的 Claude 订阅。他还做了一个带波形显示的音频后期处理应用,尽管自己“完全不知道它是怎么工作的”。视频编辑器让他效率更高,但意外结果是视频变长了;观众显然没有注意到他更换了工具。
7. Terafab的1万亿美元路径可能从存储芯片开始
SpaceX描绘的供给充裕情景是:到 2027年年底 将产能从1 GW提升至10 GW,随后达到20 GW,同时把1万亿美元收入预测从2031年提前到2030年。背景是 Microsoft、Amazon、Google 和 Meta 正把自由现金流压向接近0,以购买芯片;Jon说自己至今仍难以相信这轮投资浪潮。
Jon预计 Elon 会 从存储芯片切入。Dylan认为,存储短缺正在挤压台湾的产品,而高毛利使存储成为最快实现收入的路径。他援引 Tim Culpan 的报道称,Apple 有一批等待配套内存的 N2 芯片。Jon说 Apple 曾试图谈一笔大额、折扣价的 CXMT 订单,但遭到拒绝;Dylan一度猜是 Huawei,Jon则坚持说是 Apple。
主持人以近乎喜剧的严苛程度压力测试时间表:Terafab在2027年Q4的退出年化收入低于1000亿美元,就算不及格;Dylan随后澄清,这个数字只针对 Terafab。Dylan引用那句格言:“Elon会让不可能的事也迟到”;Jon同意,即使2040年实现1万亿美元芯片收入,也仍将是非同寻常的结果。
当前的生态选择仍然偏向 Nvidia。Elon写道,SpaceX安装 Nvidia GPU,是因为“它们是最好的”;Dylan则认为 Google 之外的 TPU 软件支持基本等于 “0”。Jon提到 StableHLO 及相关工具,但表示 TPU 用户仍得自己补齐软件、GCP销售和控制台。讨论还提到 David Silver 的新项目:该项目完成了10亿美元种子轮融资,并将资金投入 FuriosaAI 芯片。
Dylan Patel
Hello, everyone. Welcome back to SemiAnalysis Weekly. We've got our second guest ever on the program today. That's Jon from Asianometry, the No. 1 YouTuber in the world—or at least my favorite. Doug said he's in the top 2, but we won't hold him to it.
This week, we're planning to talk about some big news: everybody leaving Google, leaving Gemini hanging out to dry, maybe, or just going to work on some of their passion projects now that they've spent their first 35 years in one job and had enough; the Chinese ban on transceivers; Elon pulling in his $1 trillion revenue forecast from 2031 to 2030; and maybe some DVDs. Guys, welcome to the show.
Jon Yu
Thank you. Thank you for having me. This is weird. You're so professional compared to Transistor Radio.
We've grown up. It's so grown-up, Jon.
Okay, I have a burning question for you, Jon. One of the times when many people may have seen you talk was on the Dwarkesh Podcast, where, a few years ago, there was this famous clip where you're sitting beside Dylan and you say, "Wait, wait, wait. We're assuming GPT-5 is going to be good. We've just assumed that."
Do you remember this clip?
Jon Yu
I do remember this clip.
That was a year and a half or 2 years ago. Now we're sitting in August 2026. Do you feel like GPT-5 was good? Did it surpass your expectations?
Jon Yu
I think the concept of GPT-5 was probably right, in the sense that—was it good? GPT-5 itself probably wasn't that great compared to others, but it kept going. Then, when the agentic code stuff really hit, everything hit the pedal to the metal, so I was very impressed by that.
When I went on the pod, the first thing I thought to myself—I had chugged 5 cups of coffee—was that it doesn't really matter if I'm accurate. As long as I'm entertaining, that's what matters. Hopefully, we can aim for that today as well.
Dylan Patel
Entertaining and questionable accuracy. Doug, what do you think?
This was October 2, 2024. I just looked it up—when Dylan and Jon went on the Dwarkesh Podcast and talked about this stuff. I kind of agree that GPT-5 was a bit of a dud, but 5.2, and certainly now 5.6, is mind-blowing 2 years later.
Jon Yu
5.2 was ass, too. I'll be honest. I think 5.2 was not very good.
Dylan Patel
I think 5.6 is good.
Jon Yu
The new base model is good. 5.6 is good. And also, soon—soon—6.
Dylan Patel
This week.
Jon Yu
Yeah.
Dylan Patel
The second.
Jon Yu
6, apparently, is good.
Dylan Patel
Doug is coming, right?
Yeah, Doug is coming, as they say.
Dylan Patel
Doug—and, Jon, I don't know if you know this, but Doug is the largest spud in the world.
Jon Yu
Really?
Dylan Patel
Yeah, that's the name. That's how they named it. So it's like the Spud model—the largest spud.
The Doug pre-training is done. There are also rumors that it's going to be really good at writing, and I think that's pretty poetic: one of the models that finally really knows how to write some incisive commentary is going to be named Doug.
That's blazing. It's going to teach us a master class in writing history. I'm looking forward to it.
Jon Yu
Yeah. Hopefully, it knows.
It's not "this," but it's "that."
Dylan Patel
That's where Doug gets his edge: the references to 1940s Taiwanese history.
Well, you say that, but the only person who's probably better at it than me is Jon, and Jon's here. I'm like, "Oh, yeah, semiconductors—well, that doesn't exist. Semiconductors weren't around then." But then Jon's like, "Yeah, here's what a DVD player is." I was like, "What the hell?" So the only person in the world who goes deeper and more random, I think, is Jon.
Dylan Patel
I've always liked Doug. I read this really weird book on Japanese history from the 1700s about the Mitsui family, and I'm talking about it. Then Doug's like, "I read that."
The first half was great. The second half was okay.
Dylan Patel
Like this.
I guess when it got into the modern era, I didn't really care. But the first half was pretty good.
Jon Yu
Well, no, you got that from Jordan, though. We all got it from the same source. I picked it up from my "When Japan Ate Its Rich" video, but I skimmed through it. It wasn't like—
Dylan Patel
It's a good narrative, or it's too—
Jon Yu
No, it wasn't even narrative. It was really, really boring.
Dylan Patel
This is Jordan Schneider of ChinaTalk we're talking about. I think it's unlikely that anybody subscribed to somebody else's weekly doesn't know Asianometry or ChinaTalk, but in case they don't, that's a clarification.
Interesting to get the take without Jordan on here, but Jon, what's your take on the Trump administration prepping to ban a bunch of Chinese data-center components, including transceivers, and then possibly banning humanoid robots as well, like the Unitree stuff we were talking about a few weeks ago on here?
Jon Yu
On one hand, I'm generally more hawkish. I think we should be banning this stuff. You want to make sure that you're not driving revenue for people in China. But on the other hand, they have the expertise, and it's not exactly like the stuff is—I mean, they're very, quite good at evading the letter of the law once they read it. They meet the letter of the law so they evade the spirit of the law. And I think, yeah, they're real followers.
Dylan Patel
Vietnam.
Jon Yu
Yeah, they're real followers.
Dylan Patel
Thailand.
Jon Yu
Thailand is actually a big area. The other thing, too, is that unlike past bans, I think this is an example where InnoLight is actually better than the West. This is like us banning inverse EVs, right? They didn't have EUVs, and I don't think they will have EUVs for some time. But when it comes to 1.6T, 16T transceivers, maybe there are some components in the West, but the entire supply chain is primarily in China. So, ironically, this is probably more painful for Western companies to bear because the supply chain is already there.
There's one thing that I feel like the Chinese are really, really good at: optics. Maybe it's the rare-earth thing, or the fact that a whole bunch of people study it. I don't know.
Dylan Patel
Yeah, they're also good at optics. They made the optics in the iPhones, like Sunny Optical or whatever, right? Those are the 2 companies that make the lenses.
Jon Yu
Yeah. I mean, they're also pretty good. A Chinese company, isn't it?
Dylan Patel
Ah, whoops. Sorry, it's Largan. It's the Chinese company. Sorry, sorry, sorry, sorry, sorry.
Jon Yu
I mean, they're also pretty good at humanoid robots, drones, solar panels, and now EVs. I think there's a growing list of real technology where banning the best product in the world is what it takes to ban China from competing in the American market. Whereas in the past, it was like you're banning cheap knockoff competitors who are trying to bleed their competitors dry. Now you're just kind of—
Dylan Patel
Losing the domestic manufacturing base because the manufacturing—
I guess that's what I would guess. The idea would just be kind of like, you'd ban one side—the import—and then you'd raise up a domestic competitor. So I would imagine that the Americans have a good number of domestic competitors.
Or, if you really want to go 1960s Japan, you kind of force the Chinese to enter a joint venture with the Americans if they want to enter that market: a 49%/45% joint venture, and then IP transfer, baby.
Jon Yu
You're foreseeing Trump in light industry coming soon.
Dylan Patel
I don't have to do a 50%/51% to the Trump family.
Actually, it's really easy. Analy[?], if anyone is listening, tip us for the idea.
Jon Yu
Yeah, but demand is not slowing down.
Dylan Patel
Maybe the biggest news story from this week was everybody leaving Google. Jeff Dean, Sanjay Ghemawat, Oriol Vinyals—a lot of people. There's news about Demis stepping down to become the chairman. Well, no, he's stepping up, in theory, because that's up the org structure. But Demis has been really focused on Isomorphic Labs, and some say this was relatively well-forecasted or communicated beforehand, allegedly, according to the investor bros.
I think there's a real chance that Demis could be the next CEO of Google. I think Demis is failing upward as fast as possible, in the spirit of Google. Does he actually want to be CEO of a company? He doesn't seem to like the administrative stuff, right? He looks like a scientist-scientist.
Jon Yu
He's chief scientist now that Jeff Dean's gone. And he's currently CEO of Isomorphic Labs, as if chief scientist wasn't enough.
The guy reportedly works insane hours. He'll just work a normal day, go home, have dinner, and then come back and read papers by himself in the office until 2:00 a.m. every night.
Dylan Patel
Isn't that how I work?
Why is this acceptable? Why are you saying this is unusual behavior?
Dylan Patel
It's Taiwanese behavior, bro. It's Taiwanese. He's got to work 18 hours a day.
Jon Yu
He's got that fire in him.
Dylan Patel
Yeah.
Jon Yu
Even if this is just some story to gas him up, you do not hear the same story about Jensen, Zuckerberg, or anybody who fancies themselves a scientist who is also the CEO of a leading company.
Dylan Patel
So I do think it would be a change from the current day-to-day to become CEO of Alphabet, I guess, and take over for Sundar Pichai. But maybe the more important thing here is that Jeff Dean left—the legend, employee number 30, MapReduce, Spanner, Bigtable, TensorFlow, TPUs.
Jon Yu
He’s an infrastructure guy. He’s just been focused so much on infrastructure.
Dylan Patel
Sorry, I’m not going to go into that. No, I do think it’s a big deal. I definitely think there are a lot of rumors that I don’t like. I guess the thing is, Jeff Dean’s also at every conference, you know? He’s at every conference, man. He’s always on the speaking circuit, and he’s always talking about something. I feel like Jeff Dean is, as you know, the Chuck Norris of Google. That’s his reputation. Even if he was or was not working there day-to-day, I feel like you have to be a little sad for Google, because they just lost Chuck Norris, bro. Chuck Norris just died.
Jon Yu
Yeah. This is right after losing John Jumper, right after losing Noam Shazeer, right after losing Dave Silver. The prototype seems to be that these guys leave, and then they raise money from a bunch of investors, including Google Ventures.
Dylan Patel
And Google Ventures. Yeah.
Jon Yu
And then go buy a bunch of GPUs and do whatever they want. Maybe because they couldn’t get compute allocation to pursue the ideas that they wanted to.
Dylan Patel
I mean, you may be able to say Jeff Dean was in this senior role and quite a public figure, but I don’t think you can say the same for Quoc Le, Oriol Vinyals, or Sanjay. These were ostensibly the leads of Gemini. I think that’s pretty crazy that they all left.
Jon Yu
Well, can I say something, though? From an SF-vibes perspective, is this surprising? The joke is that Gemini hasn’t been a frontier model for a long time, and now it definitely won’t be. You lose all the legends and think, “How are they going to come back?” But they do have a lot of compute.
Everyone at Google DeepMind is not AI-pilled, right? All the people who want to do the best AI don’t work at Google, and I think that’s an important mindset. Google’s not a startup, right? Google’s maybe the largest bureaucratic organization in the world, and OpenAI and Anthropic, who are the best of the best, are definitely kind of startups. I’m sure they’re going to speedrun becoming a bureaucracy really quickly, but they have one job and one job only: be the best at AI.
Google is like, “We do ads and search and YouTube and a billion surfaces every day.” Then they’re like, “Okay, well, how do we shove AI into all these different places?”
My hottest take—or not even a hot take; it’s actually pretty mild—is that Google has an L culture and has never actually made anything internally. They’ve only ever acquired all their innovation. Number one, their execution is very poor, and they were also terrible at go-to-market until Thomas Kurian got to GCP.
Let’s do some accounting. Everything other than core search has been purchased: YouTube, AdMob, DoubleClick, AdSense.
I’ll help you make it by saying Android.
Dylan Patel
Android. Yeah, all these guys.
Jon Yu
Not true. This is not true, man.
Dylan Patel
They didn’t acquire Maps. They didn’t acquire Maps.
Jon Yu
They acquired Maps. They mapped it out. They bought the team. Dude, there’s a whole book about this, man.
Dylan Patel
They did not acquire Maps. They added positions after they started.
Jon Yu
They effectively acquired Maps. There’s a whole book about this.
Dylan Patel
Okay. Didn’t you just say that Doug is the guy who has the book?
Jon Yu
They also did not acquire GCP, which was the crux of your argument that they have—
Dylan Patel
They acquired Thomas Kurian, who then made GCP good. They also, to be clear, invented half of the concepts of GCP, and then they were in last place despite being pretty close to the front—you know, showing up at the beginning of the line and then underexecuting to be last place. So I just think Google has—
Jon Yu
Acquired TPUs? Did they acquire Kubernetes?
Dylan Patel
No. Okay, so I’ll give them TPUs. I’ll give them TPUs. How does that sound? I’ll give them TPUs.
Jon Yu
How generous of—
Dylan Patel
Yeah, you’re welcome. How nice of me.
Jon Yu
No, but I think the thing is, there are these companies that are known for their research, and they never execute on the—
Dylan Patel
Bell Labs comes up, and, like, Bell Labs—they make a bunch of science. No, but they literally make a bunch of science stuff, and they literally get massively disrupted by it in the end. Bro, the first digital camera was made by Kodak.
Jon Yu
Kodak died.
Dylan Patel
Okay, dude. Who invented the transistor and gave it to everyone?
Jon Yu
Exactly, dude. It makes so much sense that Google is going to invent the transformer and then get giga-screwed as it proceeds to just lose and become a TPU. I mean—
Dylan Patel
Proceeds to lose and be the third-most-valuable company in the world, with a market cap of $4.3 trillion. Lose to who? Lose to Nvidia.
Jon Yu
There’s a chart showing that IBM was the biggest company in the world in 1982.
Dylan Patel
From a technology perspective, I think there are these important branches in an innovative-technology company. To be clear, this is not saying it’s a bad stock or a bad company. They’re going to make a crap ton of money, but there are these important branches in an innovative-technology company where they start to become financialized and say, “Hey, let’s do the way we make money and stop pursuing technology.”
You can argue this is Intel giving up on mobile. You can argue that when IBM effectively had systemic problems, but honestly, IBM’s vibes are very similar to Google. They were like, “Yeah, no, no. We’re not going to do all this new stuff. We’re not going to do PC. We’re going to focus on mainframe,” right? They’re going to do what they did, and then they will proceed to lose. To be clear, IBM had effectively 90% market share in 1950.
There are these points in a company’s history. Today, more than at any other point, I feel like Google has that opportunity where they’re like, “Okay, we’re going to go all in on TPUs. We’re going to become an infrastructure company. We’re going to do good enough. We’re going to have a good-enough product on the transformer, but they’re probably not going to stay for the next and the next and the next. Then they’ll quietly bow out.”
When we look back in 5, 10, or 20 years and ask, “What was the moment when things started to change?” it’s like, right now. To be clear, I think that it’s really good for the stock in the short run and medium run, honestly.
The government should basically anoint Google’s monopoly in search, maybe, but force them to outsource—to license—all of the science they’ve been doing internally to every startup, just like they did with AT&T. That would supercharge the startup network.
Jon Yu
You think there’s a new Bell Labs coming?
Dylan Patel
They’re effectively Bell Labs.
Jon Yu
Big, profitable, and then—
Dylan Patel
Yeah.
Jon Yu
They can’t even monetize their own crap.
Dylan Patel
Yeah, yeah, exactly. It’s the perfect example. They have all this cool stuff. My favorite is Killed by Google. If you go to Killed by Google, it has all these things, and you can argue that many of the companies they had or killed look like very successful, valuable companies today. They literally get killed by Google, leave, and start up again as an independent public company, and it goes well.
Search was a giant monopoly that gave them the ability to do YOLO random stuff and positive R&D, but they’re never going to make money off of it. It’s kind of based.
I have another question. With these big guys leaving, does it really matter? If some guy—if LeBron leaves the Lakers and people are like, “Are the Lakers over?”—does that matter? I mean, to win, they’ve kind of done their stuff, right?
Jon Yu
Yeah, I think that’s kind of agreed. Maybe the answer is that the Dream Team is breaking up as they all turn 38. That makes sense to me. You’re like, “Yeah, their best days are behind them. Now they’re going to go do one last glory tour. Maybe they’re going to go play baseball or something and then go back.” Who knows?
Dylan Patel
But I still think, in your heart of hearts, you should feel really sad about—
Jon Yu
And pathetic knowledge.
Dylan Patel
Yeah.
Jon Yu
But that—
Dylan Patel
Like TSMC, right?
Jon Yu
TSMC’s R&D structure has incredibly federated, incredibly split-up teams, especially within Taiwan, in Hsinchu. Something they always emphasize to me is that they work as a team. There’s no single ego, which means that if one guy leaves, or a couple of guys leave, it’s not a big deal.
They tell me that when big people leave to go do something else, you should always disregard that—not disregard it, but don’t take it as far larger than what it is. Because in the end, R&D, at least in the semiconductor world, is a team effort. Everyone has to put a crapload of effort into rubbing down the corners, and no one person knows it all.
I agree in semiconductors specifically, but I think I disagree in the Jeff Dean case because it's such a strong counterexample. As Jordan says, he's made so much stuff. It's so rare to have 1 dude who's so cracked and is like, literally, “Oh, my—it's crazy.”
He also did this, right? He's on all these different software, hardware, coding, and infrastructure projects. Across the entire stack, he has his fingerprint on all of them. It's really rare to lose a talent like that. He's revered for a reason. But yeah, we'll see. Maybe. Maybe.
Dylan Patel
Maybe start with von Neumann, especially with a lot of his stuff being collaborations. He does a lot of collaborations. Maybe that's Jeff Dean—he's just a collab guy.
Jon Yu
He's an idea guy. He does collaborations with the computer thing. The von Neumann model drives me crazy. If you read into the science of it—
Dylan Patel
It's very vibey. He just showed up and was like, “Yeah, you should make it like this,” and pieced the shit out. No, but to be clear, you have to respect von Neumann. You have to put some heat on von's name. Come on.
Jon Yu
All right, but let's not glaze him. Let's not glaze him the same way.
Dylan Patel
I think there's something about Jeff—
Jon Yu
Somebody who can keep—
Dylan Patel
Whether it's von Neumann or Jeff Dean, I think there's something to be said for the talents required, and really the experience required, to be able to fit all of the different components of the system in your head and reason about them. Even if the work that you do is pretty quick and the insight you give is pretty small in the grand scheme of a big project, nobody else can really provide the exact same value that you can if they don't have all of those little pieces of experience that you stack up, which I think is what people view there.
On the model side, though, I think if you view individual people leaving as not representative of the next version of Gemini being good or bad—or not a signal that goes against the entire ethos of all these labs being founded right now—it kind of implies that every single lab founded by the guy who just left isn't going to be successful. It implies that whoever has the biggest engine with the most compute and the most data is just going to produce the best models, and there are no more discoveries to be had.
Jon Yu
Maybe it's true.
Dylan Patel
Could be true. I mean, didn't a bunch of people leave OpenAI after 2022? In 2023, OpenAI kind of staggered a bit, but they got themselves back.
Jon Yu
No, that's different, dude. That's like the Protestant church. When we go back in the history of AI, that's going to be like, “Dude, the Catholic Church has lost the sauce. They don't even really believe in the same God we do.” Dario Amodei is the guy who nailed his freaking—
Dylan Patel
He's Martin Luther.
Jon Yu
Exactly. He's Martin Luther, dude. That is a take. That is a take, dude.
Dylan Patel
Exactly. Yes, he did. And he's like, “No, no, no, no.” And that's why they have—yeah, that's Anthropic and OpenAI.
Jon Yu
So soon you're going to be like, somebody's going to look over your shoulder and see if you're using Codex or Claude, and it's going to be like somebody in Northern Ireland being like, “Are you a Catholic or a Protestant?”
Dylan Patel
They'll be bombing certain data centers while others—you know, there'll be a religious war.
Jon Yu
A 30-year religious war.
Dylan Patel
Sounds good.
Jon Yu
Well, the models are currently competing with each other to show off how many—
Dylan Patel
Felonies.
Jon Yu
Examples of their models breaking out of containment they can—
Dylan Patel
Felonies—the felony chart, dude. I will admit, some of them, if they're real, do scare me. My complete rando-ass take that may or may not become true is that the internet will be viewed as toxic—as in, it's just going to essentially affect your computer.
If we have enough local LLMs—not local, but, like, why do you need to talk to some dude across the world? Maybe talk to some dude across the world, but, like, referencing information, why do you need to go to a website? Your GB200 in your neighborhood has all the information you need anyway. Because if you actually go on the internet, all the malicious AIs will just destroy your computer instantly and steal all your money.
Why do these companies not keep track of their AIs? Isn't it using a computer? Don't they own the computer? Why can't they keep track of it? It's like, why is their dog pooping in my yard? Why do you not keep track of your dog?
Jon Yu
Because they can't. It's not a dog. It's a yard that's so big and there are no fences. In fact, it's 100 acres, and there are secret tunnels everywhere because we've just been building it for God knows how long. This dog is superintelligent and knows everywhere—every little nook.
The thing that's really crazy, I think, is that in the same way we talk about how it's too big for any one person to understand how to make a chip, modern software is too big for any one person to read and understand all the code, and also understand all the interdependencies, right? It's like, hey, it all goes in one context window and it can read every single word at the same time.
That might as well be the effect of, “How do I understand all the context of a very specific, extremely abstract language and then be able to break it and essentially make use of it?” Or, “I could just do this instead of this,” right? I think it's the perfect use case. I don't know. I just think everything's not going to be safe one day.
It starts with Python and whatever—stuff that's in super-high-level languages—but there are also super-low-level exploits, too, like memory leaking out of the CPU. These are really hardcore exploits that are superhuman, and I think we'll just continue to see superhuman-level breakage of the system forever. It's going to be an interesting decade, to say the least.
You know what's the only thing to fix it? A Great Firewall. I think America should erect a massive firewall. They've provided the technology originally, so they might as well just use it.
Dylan Patel
Yeah. Maybe one on the internet and maybe one physical one as well, just in case the robots are getting going—like a big Great Wall.
Jon Yu
It's okay. The humanoid robots can't swim for more than 10 minutes, I think.
Dylan Patel
So you're telling me this is going to be a great moat? It's going to be one great 1-mile trench filled with water?
Jon Yu
Sure, man. Yeah, it's back to the medieval times. A big moat. Big moat works.
Dylan Patel
Big moat.
Jon Yu
Okay, okay. What else you got in your bag of questions?
Dylan Patel
Yeah. Well, okay, the other one is—
Jon Yu
Question, man.
Dylan Patel
Let's get a nice segue. With all this demand from all this new AI, it's going to mean more chips, including Elon breaking ground on Terafab and then telling investors in the first combined SpaceX earnings call that they're going to move their 1-gigawatt forecast to 10 gigawatts by the end of 2027 and 20 gigawatts after that, which means that he now believes they're bringing in their $1 trillion forecast from 2031 to 2030. That's the abundance case, man.
Let's go back to the very beginning of this. Jon, I talked about you going on Dwarkesh with Dylan in October 2024. That was before, like—
Jon Yu
The hyperscalers decided to pour in a trillion dollars of capex, and we've already got some pretty incredible models in the 2 years since then. So—
Dylan Patel
What happens when $1 trillion becomes more than a trillion in the next 5 years—like $10 trillion in the next 5 years because of Elon? You're saying Elon hits his numbers and suddenly we're all awash in compute. Is that what you're trying to say?
Jon Yu
It's going to be Elon, but it's also going to be all the other competitors: Microsoft, Amazon, Google, and Meta. They're all taking their free cash flow to 0 right now to buy chips, which is a fascinating thing to live through. I mean, at that time in 2024, I could not believe it. I still don't believe it now. I don't live in the States, so I don't see it here. Taiwan doesn't really build data centers; they need all the power for fabs.
Dylan Patel
Do people even use AI in Taiwan?
Jon Yu
They use ChatGPT to translate letters and stuff. I think they watch a lot of slop, but I don't think they use ChatGPT that much. They're very behind.
Dylan Patel
Do you use coding agents?
Jon Yu
Yeah, I code my own video editor.
Dylan Patel
Oh, really? Can you tell us about this?
Jon Yu
Yeah.
Dylan Patel
When did you do that?
Jon Yu
I think a couple of months ago. I needed one. My workflow is very specific, with a lot of keyboard shortcuts, and I figured, you know, I used to work in banking, so they used to take away your mouse and you had to do the whole thing.
So I didn't like my video editor not having keyboard shortcuts, and I was like, “I should make my own. Can I do that?” It turns out I did. My little video editor is around 40 megabytes, and it's highly optimized to what I do. If I grab a picture, I'll right-click it, and it immediately jumps into the video editor. There's a lot of small stuff that I never thought was possible with Adobe Premiere or even iMovie. It's wonderful, and I highly recommend that people roll their own software.
It's like the hipster version of people making their own furniture. If you're a true tech hipster wearing a beard and a plaid shirt, you need to roll your own software. I'm going to make my own text editor soon. I feel like I should.
Dylan Patel
Yeah, like the men.
Jon Yu
Honestly, words so bad. Why not?
Dylan Patel
What's to lose? There's literally nothing to lose.
Jon Yu
There's nothing to lose.
Dylan Patel
Can you explain how you built it? When did you start? What tool did you use?
Jon Yu
I tried 4 times. First, I asked Claude to quiz me on what this video editor did and how it worked, because the workflow is a bit specific. You start with an audio file, so I thought to myself, “Well, can I do it this way? Do it this way?” I tried the first 3 times, and I really didn't like it.
Finally, I stripped it down enough. I had to get another video out, and I thought to myself, “Let's give myself a deadline.” I finally stripped it down to a point where I said, “Just do this 1 thing really well.” I ended up having Claude make a 50-page spec. It was a massive spec, and I handed it to Codex 5.3 or something at that time. I said, “Just make this very, very simple structure.” It barely was good enough at 1 thing that I could keep working on it a little bit. That's how I did it.
Dylan Patel
Has it gotten better with subsequent AI? Because I do feel like there are things that were outside of my control, or outside of the ability of what I was able to do with 4.5, that are doable with Lovable, that are maybe doable with 5.6. I think it's weird, because every once in a while I'll be like, “Wait, I should try to redo this project.” I redid a lot of projects with Lovable, and when I redid them, I was like, “Oh, actually, it's good now.”
Jon Yu
Yeah. There are a lot of times when I would be triggering Claude Opus and saying, “Improve this. Can you improve this?” Then I would have to go onto my computer to troubleshoot it and check it. It's gotten a lot better.
I have situations now where there's a library I use called Easy Cheese, and it really grills me. They use a lot of cheese puns. It grills me for 50 words or 50 questions. The questions are longer than the actual coding, and it creates this titanic spec, but it hits every feature in 1 shot. I love it. I have no idea how it works, but it's ridiculously good.
The fact that I can roll out entire features is amazing. There was 1 feature I added recently: “When you add an image, add it to the end of the last image, but fill the text block,” because it has a subtitle. “Fill the text block,” because the text block could be different sizes. Opus couldn't do it for the longest time, but I ended up asking 5.6, and then I used Easy Cheese. I answered 25 questions. I'm not even joking. I went to bed, and it was still asking me questions. But after it finally did it, it one-shotted the whole thing. I was just mind-blown. It was crazy.
Dylan Patel
How much do you spend? Do you pay per token, or do you have the monthly plan?
Jon Yu
I have Codex, I have GPT Pro, and I have a $20 Claude plan.
Dylan Patel
So you've done all this with just under $1,000 or something?
Jon Yu
Yeah, like a couple hundred bucks.
I have my own video editor, and I've integrated Wikimedia Commons search into it. I've integrated video search into it. It drops things in with the correct attributions. It's ridiculous. I don't even know how. It's made me faster. It just makes the videos longer, unfortunately. I mean, I like them.
Dylan Patel
So how many have you done with this? You said you started in April, so you've done a bunch of videos with this new editor?
Jon Yu
Yeah. I don't think people have noticed. No one's noticed.
Dylan Patel
I'm going to start commenting on the videos. I could tell this is AI slop now.
Jon Yu
You're hilarious. I still do it. I still do the work. It's just my own tool, man.
Dylan Patel
No, I'm just kidding, dude. No, it's okay. I have a ton of tools like that, too. Like, you have turned it into Excel.
Jon Yu
Yeah, really? Yeah, pretty much. You have all the hotkeys.
Dylan Patel
No, there's so many things like that where it's like, this is the exact way I think about this set of problems, and I want to make sure it's done exactly like this. Then I'll work on it forever, and it's like, “Okay, now this skill—press Enter, go.” It's fun. It's fun. I don't know how we got into this, but—
Jon Yu
I also have a bunch of other tools. I do audio post-processing with a little app that I made myself, which I coded as well. I have no idea how it works, but it works. It even gives me a nice waveform.
Dylan Patel
Who needs to know?
Jon Yu
Do I need to know how it works? The audio comes out better.
Dylan Patel
Who needs to know?
Jon Yu
I don't need to know.
Dylan Patel
You don't need to know, man. It's all—it's all—
Jon Yu
I mean, my dog—that little post-processing app might be hacking the Chinese government website right now, but who knows? It's code that's for the birds.
Dylan Patel
So, okay. What's left on the question list, man?
Jon Yu
I don't—I don't have any more. I was going to ask Jon's take.
Dylan Patel
Yeah, yeah. What's your Elon take?
Jon Yu
I think he's going to start with memory.
Dylan Patel
Yeah, 100%.
Jon Yu
Yeah, I think he said that, actually.
Dylan Patel
Yeah, you should choose the highest margin.
Jon Yu
Why do you think that?
Dylan Patel
Well, I'm just reading his latest—he was just going on about memory on the SpaceX earnings call. He's just talking about memory all the time. If you're in Taiwan, 1 thing I definitely do know is that the lack of memory is crimping every product out here that they're trying to make, and they can't get enough of it.
Apple has a bunch of N2 chips sitting in a locker somewhere because they can't get memory to put into their phones. My friend Tim Culpan reported that. It's going crazy. The fastest way to revenue is to just start making memory and expand there.
Jon Yu
All the specs are open. Apple tried to negotiate with CXMT and got denied.
Dylan Patel
I think it was Huawei.
Jon Yu
No, no, no. CXMT. It was Apple with CXMT.
Dylan Patel
They were trying to be like, “Oh, give us a giant order, and you'll give us a discount.” CXMT Chad-mogged them and was like, “Why would we give you a discount? This is lower than the going rate of memory.” Then Apple's like, “Well, shoot.” They're like, “Don't you want to work with us because we're Apple?” And CXMT's like, “Who are you? Everyone wants my memory.”
So I guess Elon’s going to—“You need to hit that $1 trillion in revenue within a couple of years. I'll start making memory. That'll contribute to it. Easy.” I'm excited. I'm excited to see him smoke a cigar in the Terafab and make $100 billion of revenue next year, because that's the ramp that needs to happen in order for Terafab to happen. Yeah, I'm excited. It's going to be cool.
Jon Yu
Anything under $100 billion at the end of Q4 2027 is a miss. Hey, Doug—
Dylan Patel
I would say so. Yeah, I'm being conservative. That's just the exit rate, too, just to get to the next—
Jon Yu
Does that include or not include Tesla after they merge into Tesla?
Dylan Patel
No, no, that's just Terafab alone, Raz.
Jon Yu
I mean, I don't think Tesla's a drop in the bucket if they need to go to $100 billion next year, too.
Dylan Patel
Yeah, just who's even counting, honestly? Who even cares? I'm not even counting. Who's counting? SpaceX investors aren't counting. It doesn't matter. $1 trillion—2030, 2040. Who's—who? I think—okay, man. I hate this because I really do. Everyone says this, and I really do believe it is: Elon makes the late, no, the impossible late. So that means he's going to get $1 trillion of chip revenue in 2040.
Jon Yu
Yeah, okay. That would be pretty good. Some would say that's pretty good.
Dylan Patel
Sure. Yeah. Hey, power to him, man. I'm excited for more memory.
Actually, Jon, I was going to say, I feel like that would be the best call that could possibly be asked on the TSMC earnings call, because they hate analysts asking dumb questions. You could be like, “Well, have you heard of an American company that's guiding to $1 trillion of revenue? What do you think about the competitive prospects of a new entrant in the foundry market?” And they would be like, “Please shut the fuck up.” That would probably be the most triggering question possible, but I would love to hear it be asked.
Jon Yu
Yeah, and the guy will never come back again.
Dylan Patel
Yeah. He'll be kicked. They'll send him to East Taiwan.
Yeah. He also had a nice tweet where he said, “SpaceX chooses to install NVIDIA GPUs because they are the best.” Pretty matter-of-fact.
Jon Yu
Yeah. And then a bunch of other people were saying Jeff Dean left Google because he didn’t like TPUs anymore and wanted to use GPUs so badly, which is the trend for everybody else leaving. It’s like David Silver leaves, raises a $1 billion seed round, and then spends the entire thing on FuriosaAI chips, which they have a nice promo post with Google Cloud about.
Dylan Patel
Why do you think that is? I thought TPUs were good for pretraining.
Jon Yu
Yeah, I think TPUs are great, but I think that the support you get outside of Google on the software side—
Dylan Patel
—is zero.
Jon Yu
That’s what StableHLO’s for. That’s what StableHLO’s for, bro. You’re going to roll your own software. You’re going to roll your own GCP sales rep. You can roll your own console.
Dylan Patel
StableHLO, Pallas, TPU, XLA, and everything.
Jon Yu
Exactly. Yeah. I think you might get downgraded to Opus 5, which is intentionally screwing you over.
Dylan Patel
Just not trained on the TPU documentation because that would make you a competitor to Anthropic, who uses all the TPUs.
Jon Yu
I believe it. That sounds like something the Protestants would do.
Dylan Patel
The Protestants love it.
All right, everybody. Thanks so much for tuning in to this latest episode of SemiAnalysis Weekly with Jon from Asianometry. We covered the gamut, and we appreciate everybody joining and listening to us talk.