Environmental Imperative
Reducing the carbon footprint of large-scale models without constraining responsible innovation.
Intelligence for planetary resilience
We are building the architectural framework for AI that respects biological limits and advances global cooperation through rigorous peer-reviewed research.
Our mission
“To decouple technological progress from environmental degradation by engineering AI systems that are as efficient as they are intelligent.”
Global Sustainable AI
Why sustainable AI
Model capability cannot be separated from energy, materials, governance, or the communities affected by deployment.
Reducing the carbon footprint of large-scale models without constraining responsible innovation.
Making AI benefits and decision-making power accessible across regions and institutions.
Developing cost-effective systems that preserve capability with fewer resources.
Our framework
Open sourcing datasets, weights, and energy metrics for every publication.
Treating useful work per watt as a primary measure of progress.
Rigorous governance frameworks for long-term social and ecological impact.
Making tools accessible across geographies, institutions, and disciplines.
Research archive
A practical approach to sparse quantization that reduces inference energy consumption without compromising accuracy.
A guide for policymakers managing collaborative climate data across jurisdictions while ensuring algorithmic accountability.
An open collection of rainforest acoustic signatures tagged with machine-learning verified species observations.
Examining the extractive nature of large-scale systems and proposing alternative frameworks inspired by indigenous stewardship.
Global research community
Our network connects independent researchers, policy makers, engineers, and students across more than 45 countries.