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Sam Altman discusses the DRAM utilization issue in local inference

2 reports3 discussions5 story updatesUpdated Oct 31 04:48

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On October 30, 2026, OpenAI CEO Sam Altman put forward the view that, from the perspective of global resource allocation, it is terrible to let the world's limited DRAM sit idle in personal computers and use only 5% of it. Rohan Paul cited this view the same day, and added that in terms of cost per token, data centers are clearly superior, and that a local model with batch size 1 is wasteful by any utilization metric, but it is also the only part of the entire technology stack that no one can take down from under you. On October 31, The Verge AI reported that Altman, speaking about the RAM shortage on the Cheeky Pint podcast, said that putting RAM in personal PCs rather than data centers is "terrible," and mentioned that Samsung and SK Hynix have signed long-term agreements with cloud service providers and projects such as OpenAI's Stargate, locking in most of the world's RAM production capacity for the coming years, which is also the reason for the current price increases in laptops, phones, and other devices.

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Sam Altman: RAM is better placed in data centers than in personal computers

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  1. Sam Altman on the DRAM utilization problem in local inference

    Source:Rohan Paul

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Oct 31

  1. The Verge AI

    Sam Altman: RAM is better placed in data centers than in personal computers

    OpenAI CEO Sam Altman, speaking about the RAM shortage on the Cheeky Pint podcast, said that putting RAM in personal PCs rather than data centers is "bad." Samsung and SK Hynix have signed long-term agreements with cloud service providers and projects such as OpenAI's Stargate, locking up most of the world's RAM production capacity for the next few years, which is also the reason for the current price increases in laptops, phones and other devices.

Oct 30

  1. Hacker News · dutchbritRelated discussion

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  4. Rohan Paul

    Rohan Paul on Sam Altman's Remarks About Local Inference

    Rohan Paul quotes Sam Altman's view on local inference: from a global resource allocation perspective, having the world's limited DRAM sitting idle in everyone's computers and only 5% utilized is terrible. Rohan Paul adds that on a per-token cost basis, data centers are clearly superior, and a local model with batch size 1 is wasteful by any utilization metric, but it is also the only part of the entire tech stack that no one can take down on you.

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