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One CPU doesn't fit every AI workload. Hear why agentic AI is creating new roles for CPUs across the data center.

45,219 Aufrufe • vor 1 Monat •via X (Twitter)

10 Kommentare

Profilbild von Fragile Express
Fragile Expressvor 1 Monat

More Slop for Ai Slop

Profilbild von REVELATOR
REVELATORvor 1 Monat

@grok is that Cotton or Silk ?

Profilbild von Максим Королевский
Максим Королевскийvor 1 Monat

AI workloads are getting more heterogeneous. The interesting part isn't CPU vs. GPU — it's how the two are being orchestrated efficiently for agentic workloads.

Profilbild von Evelyn Martin
Evelyn Martinvor 1 Monat

AI workloads require specialized processing

Profilbild von The AI Maximalist
The AI Maximalistvor 1 Monat

CPU is the only part of the data center that didn't get an AI tax. agentic AI just made the 47% of chips nobody's talking about the most valuable asset in the room.

Profilbild von Vladislav Mikhalev
Vladislav Mikhalevvor 1 Monat

🌞😉💯👍

Profilbild von Sebastian Buzdugan
Sebastian Buzduganvor 1 Monat

why count cpu cores when agent workloads usually hit memory bandwidth first

Profilbild von foa luigi
foa luigivor 1 Monat

tbh, who needs CPUs when you can just throw more GPUs at it, right?

Profilbild von karabo mathews
karabo mathewsvor 1 Monat

More are on models package like contents and that invite government's engagement with different ideas

Profilbild von What_ǝɥ┴_Actual_ʞM∀Ⅎ
What_ǝɥ┴_Actual_ʞM∀Ⅎvor 1 Monat

Look, I'm no IT specialist, but being an all AMD customer, I'm proud of how far AMD has come... and excited to see what lies ahead, but for the love of God, PLEASE launch a RX 9070 XTX!

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Cathie Wood just flagged the sleeper trade inside the AI boom that most people are completely missing. Everyone has been chasing GPUs. Nvidia, the data center buildout, the chip arms race. That trade has been obvious for two years. But OpenAI's CFO Sarah Fryer said something quite different: people are going to be really shocked by how agentic AI activates CPUs. Right now, for every CPU in an AI workload, there are 4 to 5 GPUs. That's the current ratio. Wood thinks that ratio is going to 1 to 1. Think about what that means. AI inference at scale, agents running autonomously, pipelines executing tasks across systems. The compute mix shifts dramatically away from pure GPU dominance. CPUs become a first-class citizen in the AI stack. Cathie called it going "back to the future." Intel has taken off. Flex (formerly Flextronics) is booming. Stocks that were giants in the dot-com bubble are resurging because the underlying demand for their products is real again. The GPU trade made sense at the training stage. You need massive parallel compute to train frontier models. But agentic AI runs differently. Agents are constantly orchestrating, reasoning, calling APIs, executing workflows. That workload looks a lot more like traditional computing. And traditional computing runs on CPUs. If Cathie Wood is right about the ratio collapsing to 1:1, the CPU demand signal embedded in the AI buildout is orders of magnitude larger than the market is currently pricing.

Milk Road AI

235,226 Aufrufe • vor 4 Monaten