This document discusses scaling deep learning for artificial intelligence applications. It describes how deep learning is being used to solve challenging problems in areas like computer vision, speech recognition, and medical diagnostics. Training deep neural networks is a high-performance computing problem that requires large models, massive datasets, and efficient parallel training techniques. The author discusses their work using thousands of GPUs across many nodes to train very large neural networks and obtain state-of-the-art results in domains like speech recognition.