Dylan Patel

“Well our, your, our friend Dylan Patel at his company, so he's an ASI maxi, but he's at 30%.”

“You will get to the point, and Dylan Patel was at the conference talking about, from Semi-Analysis that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't…”

“Your ability to implement something is not actually that important. Your ability to choose the correct idea for AI to implement, and then your ability to sell that idea, or sell what the AI has implemented, is what matters. Your ability to garner capital towar…”

“Even if they wanted to build as fast as possible, it doesn't come till 28 early, late 27 at best.”

“DRAM will double or triple from here still, because That's how much capacity is required, and they have to steal capacity from somewhere else, and the only way to steal capacity from somewhere else in a capitalist economy is demand destruction via higher prici…”

“Sincerely, they may spend a hundred billion dollars on capex in twenty-twenty-eight, and people, like, just can't fathom that”

“And this is just the beginning, so I think we'll see large-scale protests against AI in three months.”

“Dylan Patel said on Dorkesh, the TAM for GPC 5.4 is north of a hundred billion dollars, but there's adoption lag. That's considered AGI as far as the Microsoft OpenAI contract is concerned.”

“What you are explaining right now by what Dylan Patella does, it's this exact same B to B publication in a technology boom owning a very small niche and just kicking ass and doing the same playbook of research media events. And it has created many billionaires…”

“What I think is most likely is that there is some sort of political coup or action. That destabilizes Taiwan in some way but doesn't actually, doesn't necessarily lead to an invasion, a full-scale invasion, and so sort of this is the best of the both worlds fo…”

“Just in January, it went from four percent of or two percent of commits on GitHub to four percent of GitHub commits were done by Cloud Code, right?”

“This happened for a company. I was an advisor for NVIDIA acquired in Fabrica just maybe a few months before they did Grok and similar style of deal, right?”

“He used, like, 10,000 dollars of Claude in one week and built an entire RTS from scratch about, like, but instead of, like, being a standard RTS where it's like, oh, Age of Empires where you advance through ages or Starcraft, it is an RTS where it's China vers…”

“That's what's happening today is that people are spending all this infra money on infra and there's no return for a lot of it, right? A lot of it is just doing research and like trying to get adoption and it's free users.”

“Yeah, yeah, and Jensen's used it now, so I've like, I've convinced him to use the word. He's used it as sovereigns, and so I think we've won.”

“Just like a lot of companies have stopped hiring L four engineers because it's useless.”

“Give it six months, the models will be good enough that the UX can be like, talking to it.”

“So I think everyone's, like, cloud code is for coders, and it's like, no. Cloud code is for people who don't code now. Right? And that's the big realization this year.”

“We're, you know, we're getting an office together, Leopold, myself, Dwarkesh, and then a client of mine, another hedge fund.”

“Digital god is like, well, one, I, like, kind of believe in embodiment, and, like, you need non-digital god, you need a physical, you need the capability of, like, having touch and Feel and all that to truly be, ah, have an experience like humans and be smarte…”

“I think the robotics world is huge. I think we're, you know, we're like, we're literally warming up. We haven't even left the dugout dugout, right? Like we're like nowhere close to, you know, the scaling on, on robotics. There's a ton of like, The data flywhee…”

“Like, AI data centers are like three, four percent of the US economy. Power, not economy. Or just data centers, period. Of that, like, two is regular data centers, and two is, like, AI data centers.”

“500 megawatts is twenty five billion dollars of CapEx, like, come on, like, once you put in the GPUs and everything, right, it's like, that's a ton of money”

“Like, Yann LeCun and, like, these kind of people who are AI bears. I respect them. I like what they, like, their ideas. I think they're completely wrong, but, you know.”

“Because the supply chain stuff means that five X actually turns into a two and a half X, and then NVIDIA can compress their margin a little bit if you're actually competitive. And then that two and a half X becomes like a 50% better. And then, yeah, so it's li…”

“I explicitly told Lip Bhutan. He had never talked to the guy because it was like four layers down. The company has like absurd amounts of hierarchy. It's like four layers down. He goes and talks to the guy and he's out, right?”

“Dylan Patel says December is when Stargate's coming online, and that should be a big like the biggest cluster ever”

“And when you talk to Dylan Patel, I was asking him about deep seek and how deep seek was doing all these innovations and like moving to floating .8, like smaller smaller, basically smaller numbers, storing the weights. And he was like, oh yeah, but open AI was…”

“So you don't want to just filter out everything so that the model doesn't know anything about it but at the same time, you don't want it to output, you know, how to build a bomb so there's like a fine balance here, and that's why pre-training is defined as pre…”

“We track all 1500 fabs in the world. For your purposes, only 50 of them matter, but like, you know, all 1500 fabs around the world.”

“I would say every semiconductor company in the world sucks at software except for NVIDIA, right?”

“They get chips out faster than other people from Thought design to deployed.”

“We have barely, barely, barely tapped video data, right? So there is a significant amount of data that's not tapped, it's just video data Is so much more information than written data.”

“We may actually see models improve faster in the next six months to a year than we saw them improve in the last year. Because there's this new axis of synthetic data generation and the amount of compute we can throw at it is, we're still right here in the scal…”

“I think there were some errors in that analysis. In particular we were trying to decode it, and one of the things we noticed is that it assumed that input tokens weren't being priced. So I think that may have been an error in the model.”

“Just being clear, I talked about mixture of experts in January, it's just people didn't really notice it.”

“Everything that we've seen so far is that large-scale training has to happen in an individual data center with very high-speed networking.”