Sam Altman:

A lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data center.

But from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time.

Like you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment,

And somehow many people's intuition is the opposite of that

TL;DR Guy selling product: "Here's why owning your own product instead of renting it from me is a terrible idea"

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[–] 9 points 1 week ago (3 children)

You can aggregate spare LLM capacity in a collaborative p2p fashion. But my reasons would be to use spare PV capacity to run an uncensored model during daytime with full privacy.

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  • [–] 2 points 1 week ago (2 children)

    Maybe but nothing will beat a dedicated data center in terms of costs.

    Starting with purchasing prices etc etc.

    And what happens if a rogue Ai hits a p2p network might be a funny read a few centuries later....

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