MIT AI Model Bridges Science and Art, Unlocking Innovation in Material Design
Briefly

We can accelerate scientific discovery by teaching generative AI to make novel predictions about never-before-seen ideas, concepts, and designs.
Similar to how cells in biological materials interact in complex but organized ways to perform a function, Beethoven's symphony arranges musical notes to create a coherent experience.
By employing methods inspired by category theory - a branch of mathematics focusing on abstract structures and relationships - Buehler's model systematically analyzes complex scientific concepts.
This approach can accelerate scientific breakthroughs by allowing AI systems to generate novel predictions in areas like material science, sustainable technologies, and beyond.
Read at Medium
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