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Intelligence is capped by energy
Compute needs energy
Demand for intelligence looks enormous, so demand for compute keeps growing. That means compute broadly: chips, storage, and everything around them. All of it needs energy, and a lot of it.
The China gap
China is bringing on 10 times as much energy next year as the US. If energy is the bottleneck and demand for intelligence has no ceiling, less energy means fewer tokens or more expensive tokens, and more expensive tokens mean less gets used. That worry outweighs distillation and Chinese open-source models.
Where it shows up
The bottleneck will show up in about twenty different ways: gas turbines, natural gas prices, solar, and rare earths all move. The policy that fits is to foster investment in every source of energy, solar, nuclear, and gas included.
How much electricity do data centers use?
The International Energy Agency reported in 2025 that data centers used about 415 terawatt-hours of electricity in 2024, roughly 1.5% of global consumption. The same report projected that figure could roughly double by 2030. The United States accounted for the largest share of the use. Rising demand from AI workloads drove much of the projected growth.
Why are gas turbines in short supply?
Only a handful of manufacturers build large gas turbines, including GE Vernova, Siemens Energy, and Mitsubishi. The machines are made of precision-cast parts, and the factories that make them cannot be expanded quickly. After years of slow orders, a surge in demand from power plants and data centers filled their order books. New orders have come with delivery dates years out.
Where does a chip's electricity end up?
Nearly all the electrical power a chip uses leaves it as heat. Data centers must then run cooling systems, which draw electricity of their own. The industry measures this with power usage effectiveness, a ratio introduced by the consortium The Green Grid in 2007. A ratio of 1.0 would mean every watt goes to computing and none to cooling or other overhead.
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