AI data centers are exposing gaps in U.S. power regulation. Verified large-load governance—milestone-based forecasting, cost-causation tariffs, flexible service classes, operational visibility, and coordinated oversight—can reduce cost and reliability risk.
Morgan Bazilian
AI’s environmental impact depends not only on data centers, chips, and power supply, but on how people use it. Sustainable AI requires purposeful prompting, right-sized models, less low-value output, and better “demand architecture” for computation.
Ian Todreas
AI data centers are exposing gaps in U.S. power regulation. Verified large-load governance—milestone-based forecasting, cost-causation tariffs, flexible service classes, operational visibility, and coordinated oversight—can reduce cost and reliability risk.
Morgan Bazilian
AI’s environmental impact depends not only on data centers, chips, and power supply, but on how people use it. Sustainable AI requires purposeful prompting, right-sized models, less low-value output, and better “demand architecture” for computation.
Ian Todreas
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AI is making computation physical again: global AI capacity will follow not just chips and fiber, but power, water, cooling, permits, grid reliability, and the emerging Shadow Grid that turns energy infrastructure into the new map of AI advantage.
Brandon Owens
