The state of artificial intelligence is continuing to advance rapidly, with breakthroughs in areas from reinforcement learning to generative adversarial networks holding the potential to transform how we go about our day-to-day lives. Learn about how modern software frameworks and tooling, paired with cutting edge hardware, are enabling researchers to take state-of-the-art research and deploy at scale in areas from autonomous vehicles to medical imaging. We'll deep dive on the latest updates to the PyTorch deep learning framework, focusing in particular on two areas. First, we'll cover PyTorch’s capabilities for distributed training - ModelParallel and DistributedDataParallel - and explain when you should use each. Second, we'll highlight the intermediate representation - TorchScript - to which PyTorch models can be compiled (using the just-in-time compiler), and show how that enables deployment of PyTorch models in a variety of production environments. Attendees will leave with a deeper understanding of the latest features of PyTorch and how to use them to both train large models on massive datasets and run PyTorch models in production to solve real world AI problems.