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Model inference compute over model lifetime is ~10x of model training compute now for major providers. Expected to climb as demand for AI inference rises.

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For sure and growth also costs money for buying DCs etc.

They are constantly training and getting rid of older models, they are losing money

Which part of "over model lifetime" did you not understand?

That's not a sufficient condition for profitability if both inference and scaling costs continue to increase over time.

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