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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 просмотров • 1 месяц назад •via X (Twitter)

Комментарии: 10

Фото профиля Fragile Express
Fragile Express1 месяц назад

More Slop for Ai Slop

Фото профиля REVELATOR
REVELATOR1 месяц назад

@grok is that Cotton or Silk ?

Фото профиля Максим Королевский
Максим Королевский1 месяц назад

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.

Фото профиля Evelyn Martin
Evelyn Martin1 месяц назад

AI workloads require specialized processing

Фото профиля The AI Maximalist
The AI Maximalist1 месяц назад

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.

Фото профиля Vladislav Mikhalev
Vladislav Mikhalev1 месяц назад

🌞😉💯👍

Фото профиля Sebastian Buzdugan
Sebastian Buzdugan1 месяц назад

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

Фото профиля foa luigi
foa luigi1 месяц назад

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

Фото профиля karabo mathews
karabo mathews1 месяц назад

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

Фото профиля What_ǝɥ┴_Actual_ʞM∀Ⅎ
What_ǝɥ┴_Actual_ʞM∀Ⅎ1 месяц назад

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.

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