Tess Smidt

In this captivating chat, Professor Tess Smidt, an MIT Assistant Professor with a unique blend of physics and architecture, shares her insights on symmetry in neural networks. She explores how integrating symmetry enhances learning and scientific modeling. The discussion touches on the balance between quantum computing and neural networks, along with the intricacies of AI, machine learning, and deep learning. Tess also looks ahead to future innovations in geometric deep learning, promising groundbreaking applications in areas like self-driving cars and drug design.