The Ledger, every show

“Power is less than 10% of the cost of the cluster. Right? So, so like, it's that 90% you're not saving anything on.”

“Over time, like, Hopper's now at five percent, but Blackwell's still 10 to 15%. Actually started out higher than that.”

“You've got, like, CPX, you've got, like, the standard GPU, and now you've got the Grok chips, and they all fill a different niche, 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, i…”

“You have people thinking like, oh, latency matters in terms of where a 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, le…”

“Well, 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 capacities in space by the end of 28, and the bar is one percent. And so the XAI guy is like…”

“The baton got passed from semiconductor shortages in 23 to power and data centers in 24, 25. 26, we're still, we're swinging the pendulum, but it will fully beat semiconductors again in 27, right?”

“And my argument is, like, more economic in the sense of, like, if you sell them, like, tens of billions of dollars of equipment, they can make hundreds of billions of dollars of AI value, or chips, with that equipment, whereas if you sell them AI model access,…”

“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.”

“How many people even believe by the end of the year, AI startup revenue is over a hundred billion dollars? I think that's an insane statement for a lot of people, but that's what it's gonna be, right?”

“Meta's licensed all of Midjourney's code, data, models.”

“If they don't move fast enough, and if they don't have the most compute, or like among the most compute, they will get beaten.”

“Your revenue is like fifteen billion ARR this month, maybe, right, on a run rate basis. It'll get to 20 by the end of the year pretty, pretty clearly. Maybe it's like 16 now, but how do you pay three hundred billion dollars of revenue?”

“I think everything has shown that it will continue, and it's continued over more than 10 orders of magnitude.”

“They actually tried that with 4.5. They screwed up some things cause it was really hard to get, you know, a 100,000 GPUs to work properly. There's challenges there. Also, they hadn't figured out the whole reinforcement learning paradigm at that time.”

“GPT-V. It's basically the same size as four O and roughly the same cost. That's actually a little bit cheaper potentially.”

“The challenge today is not necessarily make the model bigger. The challenge is how do I generate and create data that is in useful domains so that the model gets better at them.”

“In fact, it's the base of everything, so you want to keep having gains, because any gains on pre-training, right, i.e. The model learns a little faster, or the model's a little bit smaller for the same quality, feeds into the next stage, which is this whole po…”

“And it's like, but it's like, comparing them, like, these models now can, like, actually, like, figure out exactly what you want, and more than 10% of Etsy's traffic is straight from GPT.”

“The models are going to purchase for you, right? They're going to do actions for you and the model, and then the company that does those actions for you, the model that will be able to take some sort of take rate, right? Even if it's like .1%, even if it's one…”

“It's why these companies need, you know, millions of GPUs to train on. Not for, oh, I'm going to make a million GPU model. But because I need to try a bajillion different things because I don't know what will work.”

“I think it's, like, tremendously hilarious that people are like, oh my god, this person's getting paid a billion dollars? It is infeasible. It's like, how could this person possibly be worth that much? Well, they're running the experiments on chips that cost, …”

“In a sense, a lot of, like, Meta's problems before they did the superintelligence thing was that they just had too many people that weren't led by leadership, that was amazing and they had, like, a lot of failed experiments and wasted time doing things that di…”

“They're wasting a ton of compute. They were, you know, maybe they still are, but you know, like, and everyone's wasting compute, right? OpenAI's wasting tons of compute. Because, you know, what's the Pareto optimal model architecture? Who knows?”

“Like, the gross profit dollars are going to the hardware layer from all of this, for sure.”

“They're gonna, those companies aren't gonna do buybacks ever fucking again, right? Or not, like, ever again, but for a while. Because, like, they have way more, they think there's better ROI for their capital now.”

“At the end of the day, if the models don't improve, we're absolutely screwed, and in fact, the US, like, you know, in another year, if this lasts another year, and then it happens, like, the US economy will go into a recession, like, straight up because of thi…”

“If I could have an intelligence as smart as a Google senior engineer, that's two trillion dollars of software value, right? Because that's how much I pay, the world pays to software engineers today.”

“All of these other revolutions have been human, have been capital goods that reduce the amount of human capital you need, whereas this is just creating human capital, right?”

“And NVIDIA's holding no risk. Everyone in the middle's got a lot of risk.”

“So this has happened in Texas, ERCOT, and it's happening in PJM which is the main, you know, the sort of northeast kind of area-ish. These two grids are putting these, like, rules where, hey, we're gonna actually say, hey, big loads, we can tell you, 24 hours …”

“They have ByteDance, who's, I think, the third largest user of GPUs in the world after OpenAI, and You know, probably Meta, although ByteDance may be bigger than Meta, the third largest user of GPUs in the world, or second maybe, even ByteDance is.”

“Autoregressive pre-trading on the internet doesn't work to get you to AGI.”

“There's just too many things to do. It's too capital intensive. It's too, there's not enough of a revolutionary leap. There's too many predicated things. You know, I wish it could happen, right? It'd be fun. Maybe it does happen, but it would take a hell of a …”

“Nvidia created Blackwell, they had a ton of manufacturing problems and challenges with it for their supply chain balance sheets went up for, you know, various companies in the supply chain are building servers and stuff, because they're trying to figure it out…”

“Like, I think part of the reason Intel's behind is also that, ah, data sharing internally was terrible. And just within the FAP. The lithography team doesn't want to share their data with the etch team, And they can't use, and that data can't leave the fab and…”

“I'm actually more optimistic on Anthropic than I'm OpenAI. Their revenue is accelerating way faster because what they're focused on is more relevant to that two trillion dollar software market versus OpenAI is split between, yeah, they're going to do that, but…”

“XAI can get to the next stage of compute. They won't have more compute than OpenAI. They won't have more compute than any individual company at Google, Meta, et cetera, but they will have the biggest individual data center”

“And the only company in the world who has the full stack From good hardware that is a, you know, what Meta just showed with their glasses, with the screen, plus the good models plus the capacity to serve them, plus the knowledge and know-how around recommendat…”

“It was pretty bearish Google, like, two years ago, but I'm like, super bullish Google. ... They're waking up on every front, you know, they're taking the TPUs, they're selling them externally, they're taking the their models, and they're actually, like, compet…”

“They have the lowest cost of goods sold for any token of any company because they have their own vertical stack on TPUs.”

“I think many software businesses will have a reckoning with the fact that their cogs is gonna soar, their customer acquisition cost isn't gonna fall, And they have a lot more competitors, and so then they don't hit that escape velocity”

“How you buy GPUs is like buying cocaine. You call up a couple people, you text a couple people, you ask, yo, how much you got? What's the price?”

“They were able to acquire three million chips, 2.9 million chips from TSMC through these other entities, right? Roughly five hundred million dollars worth of orders”

“Even though the government says they're for 14 nanometer, the actual equipment that's banned is only for below seven nanometer, and so they'll be able to make a lot of seven nanometer AI chips and maybe even get to five with, you know, using existing equipment…”

“And my number is closer to, like, it's like four 5500 and that's based on, like, you know, all the research we do on, like, data centers and, like, tracking each individual data center in the supply chains, right?”

“They're not turning a cash flow, they're not gonna be profitable until 2029.”

“Do you invest in data centers and energy? Yeah. Do you invest in, because that's the bottleneck for your growth really is, is A, well, how much people want to spend and can spend, and B, the ability to actually put them in data centers.”

“This is the lowest AWS revenue growth will be on a year-to-year basis. For at least the next year, right? And it's re-accelerating to north of 20% again because of all these massive data centers they have online with Tranium and GPUs, right?”