TBPN - FULL INTERVIEW: Dylan Patel Says We’re Still Underestimating AI

Episode Date: February 3, 2026

This is our full interview with SemiAnalysis Founder and CEO Dylan Patel, recorded live on TBPN at the Cisco AI Summit in San Francisco. We discuss data centers in space, the limits of today’s AI hardware, and how chips, power, and geopolitics will shape the future of AI infra.TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to podcast platforms immediately after. Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has recently featured Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella.

Good to see it. Good to have you. Data Center in Space, which you got. Right now. Where are we going? Coming in hot. Me, you, the International Space Station. Let's break it down.

You know, the space tourism industry is quite a fun one, right? Yeah. Would you go? Would you do the Blue Origin thing where they blast you out past the Carmen Line line? It's good enough for Katie Perry. It's not good enough for you? What's going on? It's like, you know, like you're in free fall.

You're not actually in space. Oh, it doesn't count. Shouts fired. Oh, Carmen Line denier. I want to be like going around for day. I want my bone density to start to atrophy, right? I truly want to feel the negative effects of space. Yeah, yeah, it's not enough just to go on back.

I think I would do it. It's like 90 seconds, right? Yeah, but it's better than being hanging out on Earth. But like all the cool stuff that astronauts do, right? Like, you know, put water and then like they're bubbling, and then you like try and drink the water. So they'll be unplugging the GPU and plugging it back. Oh yeah, yeah, yeah.

That's what you pay for your space tourism. You gotta go unseat a ship. 90 seconds of ship. traversing, SpaceX satellite. One 90-second trip at a time. No, but people were wondering, you know, TPUs and video going on the Starlink V-5 or whatever something gets up there,

it feels like this will be something more like a Tesla silicon per chip and AI chip. Do you have any insight into like what the process, if you wind up figuring out how the heat dissipate, if you wind up figuring out the costs, what might the chip look like? So I think, I think, you know, everyone freaks out, oh my God, putting stuff in space is expensive. Yeah.

But if you look at like starship launch costs and, you know, they keep falling, you're like fine, right? Like I think that's not, you know, by the end of the decade, the cost of space launch will be fine. The heat dissipation, I mean, it's a challenge, but you just put a massive, massive, effectively radiator. And it's fine, right? By the end of the decade, like, you'll be good. I think the big challenge is that chips are just really unreliable, right? And so how do you deal with, like, a couple things, right? Satellites can only be so large before they like, you start needing a lot of support and structure

before they tear themselves apart. So when you look at like the launches, right, these things are shooting out like tiny satellites and many of them. Okay, so you can't have like a big fully connected cluster of chips. And then like on top of that, right, how do you deal with any random error?

On Earth, you have text running around the data center, unplugging stuff, putting in spares, things like that. What do you do in space? RMA it to the factory where they like might unsodder it and re-sodder it and then like test it and it works and go back out. Sometimes it is just trashed but like you know that's the challenge to me. Is that is that I feel like maybe the pattern we should be looking at is like how often do the Tesla self-driving chips need to get serviced because that's like the team that would probably be building or like bridging the gap there like the Starlink satellites certainly go down

but like the service works like you're you're just relying on some sort of like you know, 90% uptime stuff's coming down. But most people that are in a way, mo, like the chip keeps working, right? Most people that are in a Tesla self-driving, like they're not, like, you don't hear about Tesla owners being like, I love FSD, but I'm constantly in the shop getting my custom silicon chips unseated and reseated, right?

Well, I mean, it's also a function of like the complexity of a chip, right? Sure. You know, if a chip is twice as fast, yeah. And let's say the bit error, right? Right, like how often a bit flips is the same, then it's erring out twice as often. Yeah.

But let's say the chip is 10x as big, right? And so when you look at like a Tesla FSD chip, very, very good, very, very efficient, very, still like relatively inexpensive and cheap compared to, you know, a big old GPU or TPU or whatever, right? Those things are extremely large. And, you know, again, like if the error rates are the same, then it fails 10x more, but in fact the error rates are a bit harder,

higher because they're pushing these things to the absolute limit. Yeah. Whereas you know, Tesla does have some level of like, well, First of all, the Tesla car has two chips, sort of redundancy already built in, right? Maybe you do that on the satellite, but that's more power, more... Yeah, right? So the whole all the lure, right, of it is, is... You know, effectively power is free, right?

And solar panels, you look at the cost curve of solar panels, you'll get the cost curve of satellite launches. You're like, this is free, this is great. But power is less than 10% of the cost of the cluster. Sure. Right? So, so like, it's that 90% you're not saving anything on. Yeah, yeah.

And insofar as much as... For potentially a hundred times the hassle. Yes. Yes. There's this whole like, you know, like if you look at Nvidia GPs, right? When you first turn on the cluster, about 10 to 15% of them fail RMA in the first two weeks. Wow. And then that's fine. Like you have to receipt them, whatever.

And like the industry knows how to deal with this, right? And over time, like Hopper's now at 5%. But Blackwell's still 10 to 15%. Right. Actually started out higher than that. Sure. And when a new generation comes out, it's going to be higher than 10, 15%. It'll have its curve gradually decline down.

But, you know, who's going to, are you going to test it and burn it in on the ground? Or are you going to say 5% of my chips or 10, 15% of my chips are trashed? Yeah, yeah. Because someone can't go up there and like do these things. Or am I saying, oh, I need robots who can do all this stuff in space and now that's like an additional engineering problem when sacks of meat are actually very cheap. Yeah. Speaking of my video, we haven't talked since the Grock acquisition. What does that look like in the bull case?

Like if it's a good, if the next version of GROC is a great chip, is it sitting next to the, you know, H200, H-100s in the rack, GB-200? How does it fit into the actual, like what NVIDIA deploys? Is it just a separate chip? I think it's a big vibe shift from NVIDIA, right? Before they were like, all right, I got this big GPU. Everyone's going to use this GPU. Software ecosystem of the GPU is so good.

It's one-size-fits-all. Everyone, you know, like everyone's trying to, make all these like specific point solutions but we've got the thing that's good at everything okay and then they had a vibe shift right they launched this thing called CPX okay which is a chip made for pre-fill okay with you know prompt processing creating a KV cache and also good at like video generation and image generation and that's coming out later this year they were really talking about video generation as well so yeah you've got like CPX you've got like

the standard GPU and now you've got the GROC chips and they all fill a different niche okay but really it screams oh crap we don't really know exactly where AI is going, which I don't think anyone does, right? I mean, it's moving so fast, the software is, the model architectures, et cetera. So we're just going to like engineer solutions that are along multiple points of the parietal optimal curve and then, you know, one of them will win, right? And I think it's like sort of like a big vibe shift from Nvidia. Also they just knew opening I was going to do the service deal so they freaked out, but.

Got it, okay. Yeah, well, yeah, getting up to speed on what makes Cerebrus important in the ecosystem right now. So, you know, you have people thinking like, Oh, latency matters in terms of where our data center is. It doesn't matter at all. What matters is, you know, as we've moved from, you know, chat applications, which were like, or search response immediately, chat applications, let's say response takes 10, 20, 30 seconds.

You've got agents, you know, I don't know, my cloud codes are working in the background for a long time, right? It doesn't matter where the data center is. But what does matter is that these streams of inference take, you know, 30 minutes versus 10 minutes versus five minutes. And for a lot of people, I'm fine to spend 10x the price on something that completes 10x faster. Yeah. And so Cerebus sort of just makes a ton of sense there. So open eye, you know, they've got these like long horizon. There's there's like Codex 5.2

extra high thinking or whatever. It's terrible. Can you guys teach them how to market? Oh yeah. You have to sponsor this podcast. Yeah, yeah. There's too much. Yesterday and I did actually ask him like I had the Codex app pulled up on my desktop and I was like there are six different models and then there's a thing there's another button that I can pick to me. Well, how many different products are called Codex now? There's a lot.

And now there's an app, yeah. Yeah. We actually have another guy on just to do branding. Lexicon branding came on the show yesterday talking about the all the naming. Naming architectures. It is complicated, but hopefully. You could tell he's just blood's boiling because all the AI companies just have the most chaotic.

Anthropic, Claude, Claude Code, but also you can use Claude code for other stuff. Yeah. But yeah, I mean, with Surrey-Ris, it seems like, Like there is a value to it, but are they constrained on the supply side? Like can they actually scale up to, you know, a colossus-style data center that could actually speed up codex not just for like one user, but all the users. So I mean, Cerebrus can speed up multiple users for sure. Yeah, yeah. The question is sort of like where you use it and that's where they have to like figure out where within codex, right?

Because there are times where codex is running for like 10 hours. And sometimes you don't mind, right? Like screw it. I've put off this nice prompt, gone. work on it, refactor my code, do this thing, do this task. Other times I want this iteration feedback loop. So how do you expose it to the user without saying, hey, actually there's another toggle.

So your presentation is 18 times. Well, hopefully a really robust model router, but it feels like that's been a process. Yeah, so the opening ideal is like for 750 megawatts. It's not that much capacity. On the order of like what open eyes talked about, by the end of 28, they'll be at like 16 gigawatts. Sure.

Of that. So it's like the absolute cutting edge, the most price insensitive customers in that specific use case of this is the type of prompt that you need to return fast, then you'll get the speed up potentially. Right, right. And they've got to figure out how to do it from a product, exposing to the user, et cetera. But it's clearly something where there is demand, right? Like I don't know, like Andre Carpathie doesn't care if you spending a thousand bucks

per his agent per second or whatever, right? Like, you know, so whoever it is, these like super cracked engineers don't care at all. And then obviously there's like a long tail of like actually cost does matter for most people. And so all along that curve, they've got to have solutions, right? Yeah. Yeah. When did you first think that XAI might end up at another Elon company? I mean, this has been rumored for a long time, right?

Like people are saying Tesla, Tesla, Tesla for the longest time. It's harder with a public company. Yeah, yeah. And then a bit ago, people were like, oh, SpaceX, I'm like, wait, this makes no sense. No, but there was a very coordinated, like, narrative pump. Oh, yeah. And then the space data centers. At the end of last year.

And it was like almost like perfectly telegraphed. Well there's there's a bet right between Basically the head of compute of XAI and the head of compute of Anthropic and the bet is what percentage of Worldwide data center capacity is in space by the end of 28 and the bar is 1% Oh wow And so the XAI guy is like really bullish and the anthropic guys like eh Yeah, yeah so but it's it's a really interesting bet I take the under on 1% by 28 because that's a gigawatt in space yeah

But it's actually not that crazy, right? Yeah. It's roughly 150 starship launches. We'll get them to a gigawatt in space. Yeah. So, you know, Starship hasn't worked yet. Yeah. Fully.

I was looking at the energy draw of the current Starlink fleet. And I think they're at like, what is it, 200 kilowatts or something like that. So you get 1,000 of those, 200 megawatts. And like, like, you're starting to be in the territory, something like that. Yeah. So the V2 satellite, I think, are the only ones they've launched. Maybe they've launched a few V3s,

but the V3s are coming soon, and those are like 100x more bandwidth each, right? And more power. And just more power. And so when I'm just thinking of like, can you scale this thing up at all? It's like, are they two orders of magnitude off? Are they three orders of magnitude?

It feels like they're like one order of magnitude off. I think that... Something that looks like an H-100. I think the metric is like 50... It's either 50 kilowatts a ton or something like this per satellite for V3. Yeah. Let's say from V3 to whatever the compute thing is,

they double it again, get to 100. I think the V2s are like 25. Yeah, yeah, yeah. So if you get to 100 kilowatts per ton for launch, it's only 150 or so Starship launches. Yeah. I think that's so reasonable. Maybe not 28, maybe it takes 29,

but like, you know, it's so reasonable. The question is cost and reliability, and, you know, what happens when the chip fails, how do you service it, that kind of stuff? How do you deal with having clusters be much smaller instead of like, you know, these big clusters, even for inference, big clusters are useful. Yeah.

Yeah. How do you think about Google's, response to Grox, ERIS, TPUs, obviously very successful, but are they forking that project to eat more of the Pareto curve? Yeah, so for the longest time, Google's had one main line of TPUs, right? All made by Broadcom, and then sort of next year they've diverged it, right? Where Broadcom makes a TPU and MediaTech makes a TPU. These two TPUs are focused at different things.

And they're fabed at... They're both fabbed at T. Everything at the end of the day goes to RACUS, right? I want to go there next, but everything goes to a racket. So FAPBITOSMC regardless, but both of these TPUs are focused on different things. And they've actually got a third project for another kind of TPP there. They also see this need to proliferate along the curve of like, hey, do I care a lot about super high amounts of flops, not much memory? Do I care a lot about super fast on-chip memory only?

Do I care about 3D stacking memory? Do I care about, you know, this sort of general purpose middle ground AI chip, which is what, you know, an H-100, a blackwell. a TPU looks like today. You know, they're sort of like, oh, we need to hit the entire Prado optimal curve. And it's like, okay, within this, there's training versus inference differences and like what numerics you want and all these other things. There's so much complexity there. Everyone sort of is diverging their roadmaps once they're at a sufficient scale, I think.

Yeah. Is Google still way ahead on cross data center training? Yes. Are the other labs, like, is that important to the other labs to catch up there? Or is it something that will just naturally happen? because everything sort of commoditizes, or do the other labs need to sort of marshal some Herculean effort to like crack the code

on what it takes and what Google's doing? Yeah, so it's a couple of things, right? In 2023, everyone thought that scaling was pre-training, right? You know, more parameters, more data, and that's very difficult to split across data centers. And has Google been able to do that? And Google's been able to do that to an extent, right?

So what they've done is they've got, you know, they don't have the largest individual data center campus, But what they do is they do these like regions where it's like, hey, each data center is roughly 40 miles apart from each other. Sure. So in Nebraska and Iowa and then in Ohio, they've got like these complexes and now they're building one in Oklahoma, Texas. Got it. You know, these complexes where there's all these data centers pretty close to each other.

So it's not really across data center across the world. Right. It's just cross like region. Yeah. And then that makes a lot of the difficulties a lot easier. Flipside is we've also moved to RL, right? And majority of the time of the chips is spent generating data, right, only doing four. forward passes through the model.

Sure. And then you only send the final tokens that you verified sort of back to train on to the training, to train, right? So then you end up with like, oh, instead of in pre-training scaling, you need to like synchronize all the weights every 10, 20, whatever seconds. When you're doing these rollouts, and especially as things get more and more agentic in training, you might not only need to send not the entire weights, but just the tokens that are relevant.

So way smaller amount of data and way less frequently, right? Minutes at a time instead of seconds at a time. Yeah. And so you've got this like now, now it's become like reasonable where, oh, actually, multi-data center training is completely reasonable. And people do this. People do multi-data center multi-chip training. Sure. Right. You know, you do your inference on one set of chips and you do your training on another set of chips. So like Anthropic does this. I don't know if Google does this, but Google's kind of already got the cards. Yeah. Okay. Got it. Let's go to Iraqis. Yeah, talk about Iraqis. Just there's this debate. TSM risk. Is that the bottleneck or is energy the bottleneck? I was doing. in back of the envelope calculations, feels like we're using maybe like 1% of global energy production or Western energy production on AI specifically workloads.

And then we're using like 50% of leading edge fab capacity on AI workloads. And so that feels like, okay, well, even if we all agree, and as a society, we're going all in on AI, we can only double the AI chip capacity before we need to build more fabs. That takes years. Whereas we could say, everyone turn off here,

conditioning we're sending the electricity to the data centers right like we have the ability to digital so we don't create new you know clapping for turning off the AC turn off your quad needs to eat heat strokes for all the grandmothers I need my cat dancing videos you need to feed claws right but but seriously like there's this debate over you know is TSMC the main bottleneck or energy the bottleneck how are you feeling about yeah yeah so so sidebar before I answer the question because I think it's fun

You know, in the U.S., it's insane to say turn off your AC for AI. Yes. Right? And the general public hates AI already. But in Taiwan, they've had droughts before, and they've turned off water to entire cities. They're like, oh, you get water three days of the week. And then the fab still gets supplied water. It's like, this is, you know, you've got to understand the mindset.

We are not ready as weak Americans to do this. Yeah, that's crazy. No, but at the end of the day, right, like water and power are certainly less big of constraints. Now, you've got to imagine, like, you know, semiconductor industries used to, hey, doubling the amount of transistors made every year or two. Part of that is more small. Part of that is more capacity. Whereas the energy industry in America wasn't. And so, like, initially people were like not creative.

They're like, let's do these kinds of gas plants. It's like, well, no, now we've realized, you know, yes, there's three main manufacturers of turbines. And then you've got for a dual combine cycle, then you've got like IGTs. But you've also got like medium speed reciprocating engines, right? It turns out Cummins can make like a million diesel engines a year, and those can make electricity. Like if I don't give a fuck and I put it in West Texas, easy. So now it's more of like a regulation thing, a supply chain thing. Power is not a constraint in so far like that much, right?

I think it certainly is a constraint still today. It was the biggest constraint in 24, 25, data center capacity power because the industry was not ready. People have woken up, they've like sort of been shocked to the system. Now you've got, you know, tens of gigawatts being deployed. You know, next year, 30 gigawatts are being added, and we think the power is there for it. Wow. What was it this year? It's, or this year is like, I think it's like 18-ish, 10-ish.

Okay. 15 to 18-ish, sorry. So almost a doubling. Yeah, almost a doubling, yeah. Yeah, wow. And when you look at, when you look at TSM and the crew, right, there is not really, oh, this random, you know, there's 12 people making medium-speed reciting engines that you can now convert to make power at some random data center. No, no, no, there's like, there is a rackus, right? There is one set of spot.

like you know there's you know that that's it right and so and then and then the flip side is like okay when you have 12 vendors everyone's got a little bit of slack capacity you know there's more likelihood you know you can people like oh turbines you can't get you can call a broker and you can get a turbine you might be paying 50% more 2x more but you can get a turbine yeah right like it's you can't get a 3 nanometer fab exactly and so when you talk about what's the you know the the baton got passed from semiconductor shortages in 23 to power and data centers in 2425.

26, we're still, we're swinging the pedulum, but it will fully be semiconductors again in 27, right? And so we see this across the entire space of the ecosystem. It's not just TSM, it's also memory, both. Because both of them have built at a certain pace. Now TSM's been expanding at some rate. The memory makers, in fact, have just not expanded capacity, basically, they've not built new fabs since 2022.

Because they're cyclists, so undulating. Yeah. And so when you look at it, it's like, oh, even if they wanted to double capacity, they need to build the fabs. Right? And building the fabs, it is the most complex building humans make, right? It's, it's, it's, it's, the entire air of a clean room circulates itself every 1.5 seconds. What? And you don't even feel it when you're inside. Really?

It's like that. And it's like parts per billion of particles, right? Like it's actually insane how you could, you could get coughed in the face by someone who has COVID and not get COVID. And so it gets circulated so fast, it doesn't even hit you. It's like that meme of like the spraying when someone's talking and then it's just, it's circulated. So another sidebar is everyone knows COVID like really popped off in Wuhan. Yeah. Right.

Wuhan also is home to China's largest memory company, YMTC. And so when they were like welding people into their homes, the people who worked in the fab still went to work. Wow. It was because it's, you know, one, it's a national importance, but two, like these people aren't getting sick. This fab is like way too clean. Yeah. Sorry, Jordy. I want to talk about Oracle.

They put out a post this morning that said, our partners financing for the Donia, Anna County, New Mexico, Shackleford County, Texas, and Port Washington, Wisconsin Data Centers, are secured at market standard rates, progressing through final syndication on schedule and consistent with investment-grade deals. Obviously, they were fast following their posts from yesterday, where they said the NVIDI-I deal has zero impact on our financial relationship with OpenAI. we remain highly confident in Open AI's ability to raise funds and meet its commitments and obviously everyone was looking at this being like give me a cigarette

I like it's like bank run language I haven't seen posts like this since like the FTX is it just bad cons or is there something worse it's it's terrible comms yeah like like like uh I I I told by Oracle context is like who the hell is in charge of the Twitter like what are you doing um Nvidia did something similar last year when the whole TPU mania was going on it was yeah it was yeah it was Yeah, it was like, we're thrilled with Google's progress with the TV. That said, and video chips are the only, you know, it's like no one asked you to comment. I mean like I'm sure a handful of people in your DMs and random, but that doesn't mean. Doesn't project confidence. It's sort of the lion shouldn't concern themselves with the sheep.

And like, okay, in video is the line. Maybe Oracle is a little bit more bumpy, but I think Oracle is like fine. People are just freaking out because, you know, open eyes is peak. or peak negative on opening eye right now because of how good Anthropics been killing it. Yeah, I think it's just kind of silly. Like they need to hire someone to do comms, like a Lulu or something, right?

Both Nvidia and Oracle, because what are you doing? How did you process yesterday in general, Jensen was clip farming? He was like, I don't know why he does these street interviews, right? No other CEO does those, where they just stick 25 microphones in your face and the paparazzi's flashing. It's a great vibe. It's, you know, Jensen's not been as famous as other CEOs for as long, and yet he's so important now.

And if you've like, if you know of Jensen how he is in meetings, I feel like there's two Jensen's, right? There is like PR, like good at PR, just good at talking, good at like making people hyped up and believe what he's doing. He's great at standing on stage, holding up the chip or delivering like a sermon. And then there's the real Jensen, which is like a business killer. and like actually just knows about every like aspect of the supply chain right all the way from like niche semiconductor you know design and manufacturing stuff all the way to like energy power data center like and and then doing the business deals too right and so like you've got this whole paradeo like of a whole thing a whole range of things that he's good at and he's a killer in and clearly he's like

he was in a meeting where he was being a killer and like negotiating like supply contracts or something when he walks out that he walked out he's still in that mode that's hilarious I Yeah, yeah. This is my inference. But I like it. Yeah. That's awesome. And that's why he was like, you know, like, still killing.

Like, no, we never said we committed to a hundred billion, you know, like. And it's like, I don't know. Wait, where do you even get the $100 billion number from? It's like, well, you did go on CNBC and like, you know, make a big deal out of it. So I think people would assume that it was, but they did say in the press release, I remember, these are early talks. Yeah. But they just kind of jumped the gun. This was the height of the press release economy.

Yeah, yeah. What's funny is, um, yeah. Oracle stock peaked just like a week after they announced the opening I deal. Yeah. And so like the press release of like, hey, open eyes gonna do this humongous deal, stock peaks. Same happened with a couple other vendors who announced deals with Open AI or NVIDIA, like sort of a lot of these like, like they all peaked to that and then it's sort of been like NVIDIA opening eye trade has been going poorly and sort of like the TPU, Anthropic, Google,

Amazon complex has been doing well. It's quite interesting that this happened. There's been good energy back at home with the roommates. What's going on in? I wanted to, yeah, I get one more thing. So, yes, over the weekend, it was sort of drowned out by all the Justice Department stuff. But... Wait, have you guys talked about Elon saying you can smoke a cigar in the fab?

No. Yeah, yeah, yeah. This is part of the whole thing. I didn't realize that was related. Yeah, that makes sense. Indoor heaters. We have indoor heater technology. No one's taking advantage.

Yeah, what does the fab look like if you have a lot? look like if you have no humans inside? Like that's probably his long-term thing. It's like, yeah, there will be an optimist. But no one, like the number of people who work in a fab is like irrelevant. But is it irrelevant because there's all these things you have to do when a human's in there because they sweat and they breathe. And if you don't have to do that because it's a robot walking down, even if it's puppeteered or teleoperated, you might be able to have different considerations. I don't know if that actually affects well, it's like a nesting of like, it's a nesting of the cleanliness, right? For example,

you've got this wafer, you've put like down, let's say you put down copper. And now you're moving it from one area to another. Well, it needs to be stored in a vacuum, but the easiest way to store a vacuum, or an inert gas. And that's like the thing that's being transported in. But then around that, you want it to be super clean as well. If you don't, then the copper starts getting oxidized, it affects our yields, all this sort of stuff happens.

And so like you kind of want it to be a nested layer of like, well, this thing inside the EV tool is super clean, and then the thing feeding it is super clean, and then the thing it sits in is super clean, because kind of, because that's how you get to like there's zero particles. Yeah, yeah, yeah, yeah. Because like, you know, in the FOOP, in the transportation devices, like,

parts per, you know, trillion and maybe poop, it's called F-O-U-P front-operated, front opening, I don't know, something pod. But it's called a FOOP, it's like the thing that moves and it carries the wafer's. Sure, sure, sure. And then the FAB is like parts per billion

and you know, sort of like, you've got to like, got this nesting relationship so everything is super clean. Yeah. You know, I'm bullish on robots, like super bullish on robots, but only for like, not for tasks that have like, TSM's Arizona fabs, or so, okay, let's say TSMC, Tynon, which I think produces like, you know, indirectly hundreds of billions of dollars of global GDP.

Even directly, it's like still tens of billions of dollars. Has like five, 10,000 people in it. Like, it's like irrelevant in terms of the number of people who work there. In terms of the overall economic value is created. Right. It's like, it's like, how many people fold laundry or how many people wash dishes or how many people like do construction work? Like, these are way bigger markets. For robotics.

Yeah. Yeah. Yeah. Speaking of China, what are you making of the Dario essay about, I guess his comments at Davos about, you know, selling chips to China as equivalent to, you know, nuclear weapons these days. The Ben Thompson line was something like he's okay selling chips because he wants dependency on the NVIDO ecosystem, Kuta, but he would ban lithography tools from going to China.

And I'm always, I've been wrestling with this idea of like, I don't know if China would accept this, but wouldn't there be a different world where you want them dependent on American LLM APIs? And you don't even send them the chips. And you say, yeah, you're, you can have as much AI as you want, as long as you're paying, you know, Open AI and Anthropic API. Yeah, I think it's, I think it's like a curve of like. What they will accept. It's, it's, you know, one, you, you push someone into the corner. They're going to start swinging, right?

And I'm, like, very concerned that China does this, right? Do they, do you, do you push them too far into the corner? do they say screw this we're gonna start being a lot more aggressive we're gonna we're gonna you know do more military actions or even just invest twice as much in global in supply chains like takeover Africa more than they already have lat am like etc there's there's or just take over Taiwan yeah right because if I can't have the chips what values there in Taiwan existed sure sure sure in its current state right so there's like there's this like game theory aspect yeah at the same time you

don't want China to be able to like you know if you believe AI is gonna be do what I think many, at least in San Francisco, think it's going to do, which is like completely revolutionized humanity and cause GDP growth to accelerate. Do you want to have China also own that technology? And their ability to integrate that into their military and all these other things much faster. So there is like these competing like, you know, interests. Where is the like right line?

And some people think it's like, hey, yeah, sell them AI model. Well, I think Dario would say don't even sell them AI model access. Don't even sell them tokens. Yeah, I think so. I think like, I think atropic does not sell AI access to. China. You know, they loop it through and you can see this in the traffic data. They can go through Korea and Japan and other places, but like, and so they get it.

And then the other side is like sort of like I think like the Ben Thompson view, which is like, and I think I'm more sympathetic to that, although I think I'm not exactly aligned with that, which is like, and we've been saying like don't sell them equipment, don't sell them equipment, don't sell them equipment. And my argument is like more economic in the sense of like if you sell them like tens of billions of dollars equipment, they can make hundreds of billions of dollars in AI value or chips with that equipment. Whereas if you sell them AI model access, then it costs them this much to get the economic,

you know, they're not able to... You're capturing more of the value. Exactly. Yeah, that's sort of the question that is at foot here, right? Do you want them to capture all this value of the supply chain in equipment or by buying the chips or using the models, right, and services? And we've seen, you know, across many, you know, stacks China refuses to accept, you know, using American ecosystem and they'll wait many years before they develop their own.

whether it was like, hey, they didn't use Windows, they figured out a bootlegging economy, or they didn't use Visa, and eventually they came out with like Ali Pay and WeChat Pay or whatever it's called on, and like these things are way better than Visa in fact, right? Lower transaction cost and higher volume. I never use Red Star Linux. It's North Korea's Linux distribution. Wait, really? Yeah.

If you don't, if you put it on a network, it'll immediately call home. So you have to put it on a firewall network or else. It just like steals everything immediately. I'm a fan of Temple OS, you know? Yeah, there you go. Is Doug O'Loughlin suffering from a case of Claude psychosis? Okay, yes, yes. So I think everyone's like, Claude code is for coders.

It's like, no. Claude code is for people who don't code now. Right? And that's the big realization this year. You know, we've got a couple folks now in the firm who have psychosis. But Douglas O'Laflin, who is like, you know, semi-analysis, number two, he's president. You know, he's my boy. In fact, he's the one who encouraged me to make a substack.

to make a substack a long time in the go a long time ago. What were you doing before? I had a WordPress blog. And I was like consulting on the side, but I was like, okay, let me do a substack now. Because I saw him making money off and I was like, this is shit. Like, why are you getting paid for this? There were multiple times where he wrote something. I was like, I could do way better.

And obviously, like, it was good because we both taught each other a lot of things and we've been great friends. And eventually he joined semi-analysis, but like, you know, his background is he was a hedge fund analyst. and then he decided to do a substack slash walk, hike the Continental Divide Trail for like six months, walking from Mexico to, you know, and then, you know, came back to doing substacking,

tried to do a fun. Six months of touching grass, and then he was like, I'm ready to lock it on clock code. Yeah, yeah, and so now he's, you know, like, he's never been a software developer, right? But he's been on a generational run, like, he's not coding anything, right? He's just telling Claude to do stuff.

And like, it's to the point where it's like, our, our, like, head of data, head of IT, is like, oh, can you send me that? And he's like, how do I do that? And then he's like, he zips the whole, thing and sends it to him, and it's like local host. He sends him a leak what, it's like local hosts. It's like, bro, that's not how this works.

But yeah, no, I've talked to some folks who vibe code, and they'll be like, and I'll be like, why'd you choose No. JS? And they're like, what's no JS? That's a very specific choice. Someone? Yeah, Tyler. No, but it's, we went on a little tour of a lot of our clients.

Like, you know, roughly like half our business is, or 40% of our business is like hedge funds. So we went to New York a week, two weeks ago, and we went to all of our clients, And like part of it's like them asking me is opening I fucked. And I'm answering like, no, I think they're fine. And then like some like actual ideas. And then like a lot of his Doug's just telling them CloudCode is like, they're like, you don't have to hire any junior hedge fund analyst anymore.

And they're like, the junior hedge fund analyst are like, and then he's explaining, you know, what can you do? It's like, well, like, you can just do like financial models and perform a financial models and like everything in CloudCode without ever opening Excel. And you can generate charts and like you don't need to know how to code. You just need to know how like how this stuff generally works. And you can just do it.

How many hedge funds are just trying to copy trade situational awareness now? I mean, I think everyone who's, I think a lot of hedge funds obviously believe in AI. I think there's a lot of them who don't believe in it, right? To be clear, but a lot of them that have done the best, believe in AI. They believe in it. Why are they selling software everywhere? Oh, you mean selling software stocks? Yeah, yeah.

Oh, yeah. Why the sell-off then? Yeah, I mean, of course, it's like an incremental thing, right? But anyway, so these hedge funds, like, and then the question is like, okay, if you believe in it, how do you manifest that trade? And so when you look across the ecosystem, I would say almost all my clients sometimes think are two years out,

numbers are too high. But there's like Leopold's like, your numbers are too low. And so it's like, it's like in general, right? And I think, I think like if you think about how much do you believe in AI and what's your access to information of AI, you know, there's not many hedge funds

who live in San Francisco and like fully breathe and live and understand it. And then depending on how much you believe in AI, how do you manifest that trait, right? Are you surprised that more hedge funds wouldn't, like, even just smaller shops, wouldn't say, like, hey, this AI thing seems like it's going to be big. Maybe we should set up in San Francisco. There's a number of people, right? So we're getting an office together. Leopold, myself, Dwarkash, and then a client of mine, another hedge fund.

And they have one analyst here, and it's like, and there's like a number of other hedge funds that are like hiring analysts here. But, you know, being plugged into the AI ecosystem does not mean you're just in San Francisco. because you can just walk around and talk to doofus like startups and VCs and like not actually you know see what's coming down the pipeline and you have to combine it with all sorts of information right you have to have a good tune with like what's going on to Asia Supply Chains you have a good tune with what's going on in New York sure you have to good tune with like what's going on like in the financial markets right and then like what's going on in credit markets and what's going on in all you know the data center energy

bubble all these different industries and so it's it's actually not like so simple to like be in tune with what's going on in AI You can easily get like head faked, right? You know, for the longest time people were thinking, you know, Adobe's an AI company and like, and it's like for a bit like Adobe was going down on AI and then they like launched a few AI features and the stock skyrocketed and then now it's going back down again because people realize, oh wait, no, actually it's not an AI company. I think it's the manifestation and thought of like what is actually going to the world going to look like if Anthropic 3 X is its revenue again this year, opening I, two X is its revenue again this year or you know, by the end of the year, how many people even believe by the end of the year AI startup revenue is over $100 billion? I think that's an insane statement for a lot of people,

but that's what it's going to be, right? And who believes that number, right? It's like, very few people. And then you draw the continuation, it's like, and who believes, you know, and when Anthropics says in their funding, like, hey, we're going to have $300 billion of revenue by the end of the decade. And it's like, actually, I think that number's too low because the economic value of what they're going to create is going to be insane. Yeah. And you tell people, oh, you know, opening eye is going to have 18 gigawatts or 16 gigawatts by the end of 28,

and they're going to be able to pay for it. And that's like, well, that's $300 billion to spend. How are they going to pay for it? It's like, you sweet summer child, don't worry. Sam can raise. They're going to blow up on revenue. They're fine, right? Like, it is like a bit of a vibe thing.

It's a bit of like, you know, irrational exuberance almost, right? Like, Leopold in his, you know, mid-20s, like I'm 29. Like, we are irrational, right? because we have not lived through, you know, you've got these PMs who like, you've never been, you've never been that humble. I don't know, like we almost, my family almost went bankrupt in 2008, like, you know, because we lived in a motel and we almost foreclosed and we actually did foreclose on one motel. It was like, yeah, I mean, I was still a kid, right?

Yeah, it was like, yeah, I've never been humble in the same sense. I mean, it's good to live through that and understand how things can go wrong. What are you expecting out of Zoc and META this year? We've been big Zoc defenders, especially, I mean, there's this. pressure of like, oh, meta is spending so much and yet they haven't created it, you know, any, any AI product that's super compelling or that's really working. And our stance has, has generally been meta's making more money from AI than almost any company in the world outside of Nvidia. So it's like, of course Zuck should be justified in saying, hey, this is real,

it's big, like I'm going to like back the truck up and go all in. Yeah, I mean, it's clear if you look at the most recent earnings, I think there are CPM went up. when the consumer's weak, which means like if you were to like try and strip out like what is consumer spending increasing for a CPM of ads versus what is the effectiveness of their algorithms or algorithm got better by double digits in one quarter. Yeah. Right? It's like actually insane how good the algos getting, right? At serving you the slop and the ads, right? So, so in that sense, like, the big sound of the trough. I got a good.

Slop for the. It's, we're going all in on that, all in on the farm. Slops them. So, so, you know, if you think about it, right, like, okay, meta's, where are they going to, like, win, right? You know, I think if you have the galaxy brain take, it's like, well, they've got the best, like, wearables coming down the pipeline. They're going to put AI on it. Apple won't be able to put good AI on their wearables, so they'll seat it all to, like, Microsoft, Google or Anthropical. People have had this narrative.

of, oh, as AI gets better, the value of real world experiences will increase. And I think that's a cool theory. But if you actually play it out, AI getting better means more content that's more, like, effectively crafted for you, more personalized, 100 times more, a thousand, a million times more content. That would imply to me that people will just use digital products more, which means more time on site, more time in the app for meta. So I don't know.

I mean, I'm with you entirely, but I think, I think like the galaxy of intake is that you're just going to have a wearable and that's going to have an AI assistant. Open eye is trying to make wearables, you know. You know, there's, everyone's trying to make wearables, Google is, et cetera, et cetera. I think metal will actually execute, and then they'll have a good AI.

And then you stack on like a few things, right? How do they get users? Well, we've seen, at least if you look at the user metric charts, Google's, you know, open eyes users were growing, growing, they were gonna hit a trillion by the end of the year, they had 800 billion. Why did they not keep growing in the last quarter? It's because nano-banano came out and they took all the incremental users.

Right? And likewise, if you go look at like, you know, Gemini III didn't actually make Google grow that much. It was Nana-Banana and then Pro or two or whatever it's called, right? Those are the ones that made them really grow. Metas licensed all of Mid-Journeys code data models, right? One, two, they're like actually just like focusing hardcore on multiple. Was that a billion-dollar plus deal? The number is undisclosed.

still exists as a company. Yeah. No, it felt, it looked to me like effectively a massive exit, but the best case scenario where they can just keep kind of being artists. I think, I think if you had me guess, I would bet it's over a billion. Every deal that Meta did was over a billion. Basically, like, whether it's an employment contract, a licensing deal, and acquisitions, everything had to be after it.

Well, so the interesting thing is that is you're missing a zero again. Don't never miss the zero again. Yeah, every discussion. How many billions are we spending on hiring this person, buying this company? Well, meta interestingly has gone down market for a compute because there's not enough compute in the big size deal, so they've actually gone and bought like small clusters. Oh. Because it's like, well, I want more compute.

From like long tail neoclods? Yeah, just like, yeah, from a longer tail. Okay. Because that's the only place they can get the compute they need. Interesting. Because they've already like went out and signed big deals with Google and Core weave and so on and so forth. Is Cluster Max 3 going to be a smaller chart because of consolidation in the industry?

No, there's more... It's going to be bigger. It's going to be bigger, bigger. But, you know, so meta... That's the thunder. That's ominous. It's ominous. So I think meta will, you know, capture consumers through generative.

If there's more content, people are just going to go to the content marketplace, right? The creator of the content captures less value as there are more content creators and more diversification of content, right? And so I think meta just wins by being a platform, right? Google does too. denseness too, right? But like those three win by having the platform. And then the real question is can they get in the assistant productivity game, right? And I think this is important. And through that effectively search. Like if you're an assistant, it means that you can like there's some commerce happening. Well they spin out and poached a bunch of people

from Google. Yeah. So this wasn't in the media much, but like they actually poached Google search people with similar sized deals as like these crazy. Yeah. Yeah. And I always, I You know, demoing any of the wearables, you can imagine like Meta wants you to walk around in the world and see like, oh, what are those headphones? And like, while we're talking, I just hit my little thing and buy it, right? And it's like you didn't even necessarily know that it happened. But like, of course Meta's going to want to monetize that. Everyone knows those are the Sony, MDRX, Sue 272s, 4662.

Dude, I've been screaming about them, like, doing some proper marketing. Branding is so wild. It's literally like over here is like WH-1000 XM-5. And then their in ears like WF 1000 XM 1000. It's like, dude, just call them like Bravia buds and Bravia like headphones or some shit. Well, China just bought. Yeah, yeah. Bravia brand's actually a Chinese company now.

Sony sold their TV and PlayStation Buds. Walkman. Walkman. Like, come on. Something, something. For sure. Anyway, anything else, already? No, this is fantastic.

I'm excited for. this weekend. Yeah, yeah, super excited. What are some plays that we don't watch a lot of sports? What are some plays? You are a football guy, right? Yeah, yeah, yeah. Yeah, rural Georgia, so I like football. High school football was the thing. College football was the thing. I think NFL is a little less soulful. Sure. But you know, now college football has has the NIL and so it's also soulless to some extent. It's fine. We we enjoy it, you know, primal desire of seeing heads clash. You know, And sometimes that manifests in like, you know, Twitter drama and sometimes it manifests in real football. Yeah.

All I can say is fuck the Patriots. Okay. Whoa. Okay. Okay. I'm kind of bummed. We're going to, we're going to, since we're going to be at the game, we're not going to really get the great experiencing the ads. I'm going to be like going to my phone.

I want to see all the AI, the different. Well, don't worry. I got some more ads for you. Thank you so much for coming. Thank you so much. Great segue. Yeah.