Sustainable AI
AI has real energy, water and infrastructure costs. We support more transparent, measurable and resource-conscious computing. These are practical resources worth watching now.
A global initiative coordinated by France, UNEP and the ITU, focused on aligning AI development with environmental goals and sharing current research and policy resources.
A consensus-based method for measuring AI carbon intensity across the lifecycle, from data preparation and training through inference and end-of-life.
Free, open-source tools for estimating the environmental footprint of local compute and third-party GenAI API use.
Real-time and forecast grid carbon-intensity data that can help identify when and where electricity is cleaner.
Examples of AI-ready data-center infrastructure using closed-loop, waterless cooling and lower-overhead energy design.
These links are offered as starting points, not endorsements. Sustainability claims, technologies and standards change quickly; favor measurable disclosures over vague environmental marketing.