Bringing Research And Production Together With PyTorch 1.0
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. Learn how PyTorch 1.0 enables you to take state-of-the-art research and deploy it quickly at scale in areas from autonomous vehicles to medical imaging. We'll deep dive on the latest updates to the PyTorch framework including TorchScript and the JIT compiler, deployment support, the C++ interface, and distributed training. We will also cover how PyTorch 1.0 is utilized at Facebook to power AI across a variety of products.
Dmytro Dzhulgakov is an Engineering Manager and Technical Lead in AI Infrastructure at Facebook. He currently leads the core development of PyTorch 1.0, an open source deep learning platform, and is one of the co-creators of ONNX, a joint initiative aimed at making AI development more interoperable. Previously, Dmytro built several generations of large scale deep learning recommendation systems at Facebook that powered products from Ads to News Feed.
Before Facebook, Dmytro graduated with an MS in applied mathematics in Ukraine. While in college, he had a successful career in programming competitions and was ranked in the Top 20 on Topcoder.