compute

“Foundational models. I think they will get commoditized like compute, and I think the companies who deliver the last mile will be the ones to capture most value.”

“By treating that as a whole system problem I am optimistic we will really surprise the world on the upside.”

“Doing the best research and the best productization of, like, the best innovation on that stuff over the next 12 months, and was it five years for the second there? Sufficient, like, supply chain and compute.”

“So, I mean, we're growing our compute like every companies. We are convinced that we don't need to grow at the same rate because there's a lot of barriers that are not compute related that are appearing on the way and that we're already seeing”

“Capital is equal compute. Then compute is correlated with quality. It's not completely dependent on it.”

“There's obviously compute, but given the amount of data you have we have at hand compute is already running into is no longer the bottleneck. The bottleneck is more the data at that point. You should look at text to text models.”

“Like, we're going to be on a journey, maybe forever, as human beings, of massively increasing the amount of compute available to us in all aspects of our lives.”

“So put another way for just scaling up a base language model you need to double the amount of compute for that language model for it to be predictably consistently smarter.”

“The second way of improving model performance is just starting to be tapped now, and that's also going to absorb a boatload of compute. So because of that, I actually am not worried about diminishing returns to the compute over time.”

“Certainly the last five years, but arguably longer, the story of AI is really a story largely about the deployment of just enormous amounts of compute and enormous amounts of data, and not that many new ideas, candidly.”

“These big tech companies are producers of compute. Startups are consumers of compute. So if you believe there is an overproduction of compute and that compute prices go down, startups win because they are buying those compute. Lower cost of compute directly tr…”

“Yeah, I mean, I think it certainly requires exponential input. You know, you need to continuously be doubling your compute in order to sustain linear gains in, in intelligence. But I think that probably goes on for a very, very, very long time.”

“There are massive amounts of data available, And I think we have not yet figured out how to properly leverage those due to either limitations of compute. I mean, you have to process all that data and it does take, we don't have current models to do this very w…”

“We are nowhere close to hitting the limits of available data in these models. Arguably, we're unable to process it because we don't have enough compute and things like this, but we're nowhere close to data limits in other senses.”

“What we are going to find is that for compute, dollars have a direct one-on-one effect. But when we look at data, when we look at proprietary applied research, and we look at talent, It is not as straightforward as dollars in magic, you know, success out on th…”

“Kind of like electricity, we have infinite demand for compute at kind of, call it modest, at moderate price, pricing. So as long as we can deliver that, we will, demand will completely fill.”

“I think they will continue, but I don't think it's just going to be linear. Like whoever has the most compute is going to win.”

“So for the last five to six decades, like clockwork, once a decade, the cost of compute has gone down a thousand X. People buy 100,000 X as much compute spending a hundred times as much. So every decade they spend a hundred times as much. So you make it cheape…”

“Compute has been more of a less of a bottleneck and more of a sort of a, you know, soft neck or something, right? Where, when you provide even more compute, you can sort of overpower the lack of data, the lack of improvement in algorithms. So it's not a hard b…”

“Probably the number one thing I would say is do not resell compute if you can. A lot of, you know, AI startups That are building on top of AI are trying to make a margin, you know, on top of a very big cake. And ultimately what they sell is compute. If you loo…”

“They are constrained, so they are bound to Bound to do better. They can just not buy their way into better compute. So I think it hinders their success, but I think it's short term to think that way.”

“There are no, there are very few examples in our industry, actually none in compute in 50 years, in which by making things cheaper and faster, the market got smaller. Market always gets bigger. Always.”

“There is no limit to the amount of compute that we can use.”

“We don't have the same supply chain constraints. We can build more compute than anyone else in the world. The most finite resource right now, compute, the thing that people are bidding up and paying these high margins for, we can produce nearly unlimited quant…”

“Compute is the easiest knob because it just keeps getting better and better and better every year. And if I write enough you know, if I write a check for enough money and I'm willing to wait a little while, I'm going to get more compute. It's the most predicta…”

“The countries that control compute will control AI, and you cannot have compute without energy.”

“The greater growth of inference is the number of people who use it, Times the frequency of use. Times the amount of compute needed per use. Right? It is three different variables multiplied by each other. The problem is they're all growing fast.”

“Consumers of compute benefit from a bubble, because if we overproduce compute, prices go down, your cogs goes down, and your gross margin goes up.”

“If you have too much talent and not enough compute, you're wasting your time, so usually like an equilibrium between those two pieces.”

“In my career working in AI, I have yet to meet a single person that ever felt like they had enough compute.”

“I do think a lot of these non-gross margin positive things, the good thing is they're all digital products, so they'll get, yes, time will take care of a lot of that, you know, and cheaper compute.”

“Compute and revenue have a one-to-one correlation. So as long as that holds, it makes sense to consume every single penny of capital on all of Planet Earth.”

“They will become more and more standardized building blocks. And I'm, I think in the future, I'm not sure AI was even going to code that much. It's just going to pick some pieces together and stitch them together to come to what you really need, which also act…”

“And today, compute eats jobs.”

“I think compute is the big one, not just for the obvious reason of scaling up your ideas and your systems as you know, the scaling laws as they're called, you know, keeping on building bigger and bigger architectures with more and more parameters. And as you d…”

“In, in certain domains that are well explored, like coding, for example, yes, there's an increasing amount of compute required to get an incremental gain in some eval that's super saturated.”

“I think if there's any reason why OpenAI, Anthropic, Gemini, and so on don't hit their revenue targets over the next few years, it's because they won't have access to enough compute.”

“Recommendation system space does not need as much compute to create the output that's necessary to succeed.”

“It's possible you look back and see that as the first disconnect from compute equals revenue.”

“I don't know about 24 months time, but I would bet that in five years the average enterprise spends more on compute than headcount.”

“If I abstract, if I step back today there's not enough compute for what the world is demanding. Unequivocally not enough compute, right? You can't buy compute. Compute is costing two to three X or four X more than it used to cost two years ago. There's not eno…”

“I think in the next three, four years we won't be paying for intelligence, we'll be paying for compute through our nose.”

“There were users who were spending a shit you not like 2000 dollars of compute a month, 4000 dollars of compute a month. There's someone on the platform who'd spent in five months was like 26,000 dollars.”