Perspective: Towards sustainable exploration of chemical spaces with machine learning

ArXi:2604.00069v1 Announce Type: cross Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspective, we examine resource considerations across the AI-driven discovery pipeline--from quantum-mechanical (QM) data generation and model