carbon efficiency

Green AI Carbon Optimizer Recommends Carbon-Efficient Training Locations and Forecasts Global AI Energy Demand

The Green AI Carbon Optimizer, presented in a new arXiv paper, offers two tools: a carbon-aware cloud region recommender for AI training and a power-law forecasting pipeline for global AI energy demand. By combining grid carbon intensity, renewable share, and PUE across 100+ regions, optimal region selection can reduce emissions by 97.2% versus the worst region. The forecasting model, based on 26 anchor models, projects 2030 AI energy demand between 7 TWh and 1,436 TWh depending on scenario assumptions.