Beyond Trillion-Dollar Compute, AI Needs a "Stargate of Data"
willdepue · x · 2026-07-07
Analysis indicates that labs are moving towards over $100 billion in annual data expenditures by 2030. As trillion-dollar compute projects advance, a civilization-scale effort of equal magnitude is required for the other core element: training data. The article reviews the scaling laws, where deep networks improve smoothly as model size and training data volume increase simultaneously, emphasizing that data is the other foundation of the scaling revolution.
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