Andrew Dudzik

This discussion features Andrew Dudzik, a mathematician specializing in category theory; Taco Cohen, a researcher in geometric deep learning; and Petar Veličković, an expert in graph neural networks. They delve into why LLMs struggle with basic math by highlighting their pattern recognition flaws. The conversation proposes category theory as a framework to transition AI from trial-and-error towards a scientific approach. They explore concepts like equivariance, compositional structures, and the potential for unifying diverse machine learning perspectives.