AI’s hidden storage bill: What inference leaves behind

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AI inference operations generate substantial hidden data storage costs that often exceed the size of user-facing outputs by orders of magnitude, with an 8-second video example showing 500MB of backend data retention versus 3.97MB delivered to users. Storage demands for AI inference are projected to grow at 35% annually through 2030, outpacing compute spending and becoming a significant portion of total AI infrastructure budgets that organizations frequently underestimate.


Source: MIT Technology Review

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