Sam Altman warning about unsustainable silliness in compute buildout lands because the market is already asking whether AI infrastructure is ahead of demand. The industry is spending as if model usage, inference volume, and enterprise adoption will keep compounding rapidly.
The hard part is that both things can be true: AI may need far more compute, and some buildout assumptions may still be overheated. Data centers, chips, power contracts, and cloud commitments are being priced before the long-term unit economics are settled.
For readers, this is the financial thread behind every model launch. If compute gets cheaper and demand keeps growing, the buildout looks rational. If revenue lags, infrastructure becomes the place where the AI boom feels most exposed.
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