Our Objectives
This project is based on the insight that in order to significantly reduce the CO2 footprint of ML applications power-aware applications must be as easy to develop as standard ML systems are today. Users with little or no understanding of the tradeoffs between different architecture choices and energy footprint should be able to easily reduce the power consumption of their applications. We envision a sustainable, interactive ML framework development for Green AI that will comprehensively prioritize and advocate energy efficiency across the entire life cycle of an application and avoid AI-waste.

Expected Impact
The SustainML framework will address the carbon and resource footprints of ML models and offer multiple pathways to avoid AI-waste from the very early stages of AI life-cycles. This will not be a limiting factor for the rapid growth of both AI research and AI adoption, but rather an enabling tool focused on sustainable growth.