Earlier this year, MIT Technology Review published a comprehensive series on AI and energy, at which time none of the major AI companies would reveal their per-prompt energy usage. Google’s new publication, at last, allows for a peek behind the curtain that researchers and analysts have long hoped for. The study focuses on a broad look at energy demand, including the power used not only by the AI chips that run models but also by all the other infrastructure needed to support that hardware. Another large portion of the energy is used by equipment needed to support AI-specific hardware: The host machine’s CPU and memory account for another 25% of the total energy used. “I think this will be a keystone piece in the AI energy field,” says Jae-Won Chung, a PhD candidate at the University of Michigan and another leader of the ML.Energy effort.