This podcast episode explores AOT AutoGrad, a revolutionary framework that seamlessly integrates compilers into PyTorch training, enabling substantial improvements in performance, memory usage, and code efficiency. By considering the operations during training as tensor operations similar to those in inference, AOT AutoGrad empowers users to apply compilers to the training process for optimizations and efficient execution.