An Open Multi-Modal Foundation Model for Materials and Chemistry

Abstract

In this talk, we present the latest status of our multi-modal foundation model (FM) for material discovery, along with our open innovation efforts in model development and community building. Our FM integrates over five modalities, including SMILES and SELFIES, providing two key functions: (1) robust feature representations for high-accuracy downstream prediction tasks, and (2) cross-modal inferences. Additionally, we are fostering an open community in the framework of the AI Alliance, bringing together industries and academia to collaboratively advance model development.