Explore the integration of constraints into deep learning architectures through structured layers in this 50-minute lecture by Zico Kolter from CMU Bosch. Delve into topics such as deep equilibrium models, explicit and implicit layers, SAT optimization, and the implicit function theorem. Examine weight-tied input-injected networks, the expansion of depth to capture different layer types, and the concept of equilibrium points in deep networks. Gain insights into sequence modeling and smallscale benchmarks as part of the "Emerging Challenges in Deep Learning" series presented at the Simons Institute.