AI Researcher Atlas Wang on Making Neural Nets Explainable and Fast

Atlas Wang discusses his work on neuro-symbolic AI, aiming to compress neural networks into simple, human-readable rules like decision trees. He proves theoretically that gradient descent can find compact symbolic equations, but practical tools remain distant. Wang also applies AI to high-frequency trading at XTX, where tiny predictive edges yield huge profits.