CPU

“So until something's invented that says the CPU has gone away and we're now doing it through some other mechanism, which has yet been defined or invented. The CPU is gonna be doing just fine and there's gonna be a lot of demand for it, a ton of demand, in addi…”

“If every one of those agents ran in a traditional container, like, you know, which is not even a VM, not even its own server, but just a container, right? You would need more than 40 times the current CPU production in an, in a calendar year in order to suppor…”

“So lean still has a lot of shortcomings there. It's CPU based and you know, it's not, Like, getting that onto the GPU has a lot of nuances there. So, you know, a lot of work needs to be done. So what we've started with is a framework, you know, making that mor…”

“CPU manipulates the bits. Storage stores bits. Network moves bits from point A to point B. But if you're digitizing the physical world, you're treating atoms like bits. And you're like, well, I know that CPU manipulates the bits. What manipulates atoms? That's…”

“What I see today that's prominent in AI space is what I consider to be the CPU of intelligence unit. You have this one language model that's really large, that's very smart, that can do very complex reasoning tasks. That's like CPU. What I see coming and what …”

“The, it's amazing how much of simulators, when you call environment.step, is still run on the CPU, and so that's usually the bottleneck for a lot of your on-policy rollouts”

“The big idea of the company that was spot on is that it is possible to augment the CPU to solve problems that otherwise are too difficult to solve. And molecular dynamics is one of them. Image processing is one of them. Inverse physics is another one. And so a…”

“And so, as we do more and more AI work, and more and more agentic work, we're making more and more calls to CPUs, and therefore the demand for CPUs is through the roof.”

“Now with these agentic workflows, you actually need both. In fact, the ratio of CPU to GPU is becoming like one to one.”

“Right now, the authentic AI and inference, CPU become, you know, highly in demand. And so, you know, versus one to eight in the training CPU to GPU, now I can see one to four, maybe one to one, and I'm delighted CPU become important.”

“Agent loops, agent harnesses are all running on CPUs. The tokens are produced by the frontier models on GPUs, but whatever work, like, let's say like Claude generates a coding script that decides to download 500 files from different websites and then You know,…”

“So the GEMA for model is a E to B. That means that it effectively has two billion parameters loaded into the GPU. It actually has almost five billion parameters, but those three billion parameters can be in the CPU, they can be in the disk, which means that yo…”

“The reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at what? A hundred percent the entire time. And so when you're running runs on CPUs, when the CPU cycle is like down and spinning up the…”

“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…”

“And so I think that that is just creating a massive need for more CPUs and more memory. And we're seeing that we're actually just at the beginning of that. I think agents is really what is driving that.”

“Now, the ratio is actually moving from, to one CPU to four GPUs, and so it's improved kind of by two x already, and we think it actually has a chance to flip the opposite direction, which is one GPU to four CPUs, and so, and some people, very aggressive, say t…”

“The most expensive thing is the CPU. Second, the RAM. This is almost free. It's very inexpensive.”

“I don't know it goes to the extreme to where GPUs are because that is very, very, very extreme. But it is quite highly, high probability that there will be shortages of CPUs going forward.”

“CPU-wise, all these reinforcement learning environments plus all the slop code you and I are generating that is now running on some, you know, Vercel instance or whatever it is or some AWS instance or some bucket that we've spun up, all of that requires CPU, a…”

“So the environments can get more and more complex, and those environments run on CPUs. They don't run on GPUs. They don't run on ASICs. The ASICs run the model,”

“Developers are going to think, just like CPUs used to be like so Intel inside, and now nobody cares. I think models will become that.”

“AI agents need more CPUs. The ARM CEO talked about four times more CPU quarter cores versus last year's kind of AI infrastructure model. So we're gonna see this massive Demand for CPUs that people aren't really understanding it. Because AI agents, the whole th…”

“We are currently in what seems like a little bit of a CPU crunch. Intel can't make CPUs fast enough.”

“Agents need CPUs. You need to fill the GPUs constantly with new data and tasks. Also, all of the agents use CPUs to make web queries, search the web, run Python, spin up web servers, interact with anything.”

“Reading what do I have to do next? Okay, how do I do that? That is most of the cost on a CPU, whereas if you just keep the same instructions but make the payload a hundred times bigger, then you can shift most of the cost to be in the actual work that you want…”

“You feel like we might actually be seeing a CPU shortage partially because of this refresh cycle, but partially also because like I legitimately believe the cloud code Cloud code is increasing software creation and then on top of that, there is real demand fro…”

“Moving the big recommender systems that power the advertising and the recommendation Systems from CPUs to GPUs, and you've had massive efficiency gains, and that's why all the revenue growth at these companies has accelerated.”

“I do think CPUs are generally aging better than GPUs so I think it's worth taking a look at the speed of GPU development versus CPU development, and we may see those things end up in slightly different places.”

“TPU, I'll use that example again because I know it best for certain computation, is somewhere between 10 and a hundred times more efficient per watt, and it's this watt that really matters than a CPU.”

“They are the single best company in the world at parallelizing workloads across CPUs across multiple data centers.”

“Data processing represents the vast majority of the world's CPUs today. It still completely runs on CPUs. You know, if you go to Databricks, it's mostly CPUs. If you go to Snowflakes, mostly CPUs. SQL processing at Oracle, mostly CPUs. Everybody's using CPUs t…”

“We're going to speed run the last 30 years of CPU efficiency gains. In, in the next, you know, five to 10 in, in GPUs.”

“For most people, one of the things about CPUs that's really nice is with containers, right? You can end up having a single node and you can place many containers on them and all the containers will slowly start eating the compute. It's not really the same with…”

“Like your eviction policy runs on a CPU. Like that radix hashing algorithm and block hashing and all that stuff happens like primarily CPU. That's really important for performance because if you have latency in these steps, like you're not keeping your GPU uti…”

“AI is going to be like water. You're going to get free unlimited AI processing on your CPU. On your phone within three to four years. There's no doubt it's going to free”

“Gusto isn't going to make like, you know, five percent more money. They're going to make zero, like literally zero money from every incremental GPU or CPU after a certain point. This is not the case for anyone who is training models. And it's not the case for …”

“I don't think of an LLM as an operating system. I think an LLM is much more like a CPU, right? It's an information processing unit.”

“They compared a CPU only setup to a GPU setup to a multi GPU setup, and it kind of made no difference really.”

“Right now we have, like, the human CPU doing a lot of, you know, silicon CPU tasks, and so you really have to, like, redesign the work thoughtfully such that, you know, probably not that different from how it's evolved in computer architecture, where the CPU i…”

“Yeah, the traditionally CPUs run in the realm of about a hundred to 200 watts is typically what they would consume in terms of power. GPUs are substantially more, and generation after generation, it's increased And they're 200. And 50 watts to the earlier vers…”

“Everything maybe besides like the battery cell and the GPU and CPU at this point, it feels like we've done what we're doing.”

“And to me, it was clear that the industry needed That powerful combination of the serial, the scalar competing of these traditional CPU workloads and the massive parallelization that you get from a GPU.”

“The fact is the bulk of inferencing done today is done on general purpose CPUs, not the huge LLM inferencing, but, you know, just general inferencing for AI applications.”

“So it's designed basically, you can sort of think about it, you know, as your general purpose sedan, that's sort of the CPU and the GPU. All it does, it gets on the F one track and all it does is go fast on very specific workloads.”

“We deeply believe that, that someday everything will be accelerated. And the reason for that is, is very clearly that, that the CPU will run its course. And there's a limit to how far you could scale general purpose computing and you'll always need it. You alw…”

“What you really see is that if you think about, you know, supercomputing power, so the ability to get to an answer that has actually continued unabated. And if you look at this chart, the reason why this is possible is entirely because we've shifted from CPUs …”

“The more CPU you've got, the more things you can put inside of sandbox instead of letting them run on bare metal.”

“A luxury automobile, not a self-driving car right now, has about a hundred CPUs in it today.”

“It's able to run, you know, AI problems across millions of CPUs and thousands of GPUs using a proprietary distributed computing middleware layer.”