Paul Lessard

Dr. Paul Lessard, a Principal Scientist at Symbolica, dives into making neural networks more interpretable through category theory. He discusses the limits of current architectures in reasoning and generalization, suggesting they're not fundamental flaws but rather artifacts of training methods. The discussion explores mathematical abstractions as tools for structuring neural networks, with Paul enthusiastically explaining core concepts like functors and monads. His insights illuminate the potential of these frameworks to enhance AI's reliability and understanding.