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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.
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They are constantly training and getting rid of older models, they are losing money
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Which part of "over model lifetime" did you not understand?
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That's not a sufficient condition for profitability if both inference and scaling costs continue to increase over time.
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