Stanford’s 100-year AI study says scaling is running out of road
THE SO WHAT
If Stanford’s AI100 report is right that pure scaling is running out of road, the edge shifts from raw parameter count to data, architecture, and integration into real workflows. For operators, that means less chasing every new frontier model and more investing in domain data, evals, and system design around whichever backbone you pick.
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