Financial Times reporting on how much power AI needs puts a hard constraint underneath the industry's biggest promises. Model launches can sound weightless, but training clusters, inference demand, and data-center buildouts are now tied to grids, permits, and energy politics.
AI capacity is becoming a physical infrastructure race. Whoever can secure electricity, land, chips, cooling, and transmission will have leverage over what models can be built and how cheaply they can be served.
For readers, the story is simple: AI progress is no longer only a software curve. It is also an energy, capital, and public-policy problem, and the constraint will show up in prices, availability, and where the next AI hubs get built.
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