PyTorch Developer Day 2020 | Full Livestream

Join us for PyTorch Developer Day 2020, where we’ll look at technical talks, core updates, and project deep dives. The video will cover a variety of topics, including updates to the core framework and new tools and libraries to support development across a number of domains. You’ll also hear from the community on the latest research powered by PyTorch.


Opening & Keynotes

1:09 – Welcome – Joe Spisak, Product Manager, Facebook AI


5:00 – Open Challenges in Deep Learning Systems – Kim Hazelwood, West Coast Head of Engineering, Facebook AI
23:35 – State of PyTorch 2020 – Edward Yang, Research Engineer, Facebook AI
33:45 – Vision of PyTorch: Focus of the next 3 years – Lin Qiao, Director of Engineering, Facebook AI

PyTorch Core Deep Dives

45:55 – Complex Numbers in PyTorch – Anjali Chourdia, Software Engineer, Facebook AI
53:00 – Making PyTorch More “NumPy Compatible” – Mike Ruberry, Software Engineer, Facebook AI
59:20 – High-Level API for Autograd – Alban Desmaison, Research Engineer, Facebook AI
1:08:40 – PyTorch Distributed RPC – Shen Li, Research Scientist, Facebook AI
1:19:15 – PyTorch Distributed Data Parallel (DDP) – Pritam Damania, Software Engineer, Facebook AI
1:29:30 – TorchAudio – Vincent Quenneville-Belair, Machine Learning Scientist, Facebook AI
1:35:20 – TorchText – George Zhang, Software Engineer, Facebook AI
1:43:15 – TorchVision – Francisco Massa, Research Engineer, Facebook AI
1:48:45 – Latest Profiler APIs and Best Practices – Ilia Cherniasvskii, Software Engineer, Facebook AI
1:51:55 – Visualization with TensorBoard – Siqi Yan, Software Engineer, Facebook AI
1:57:25 – PyTorch Performance – Natalia Gimelshein, Applied Research Scientist, Facebook AI
2:07:35 – PyTorch on Windows – Maxim Lukiyanov – Principal Product Manager, Microsoft Azure
2:19:15 – PyTorch Mobile, David Reiss, Software Engineer, Facebook AI
2:27:15 – PyTorch Mobile and Android Neural Networks API – Oli Gaymond, Product Manager, Android Machine Learning

PyTorch Research Talks

2:33:10 – Torch for R & Hasktorch: Brining Torch to New Programming Languages – Austin Huang, Vice President, AI & Machine Learning, Fidelity and Daniel Falbel, Software Engineer, RStudio
2:46:50 – Graph Convolutional Operators in the PyTorch JIT – Lindsey Gray, Scientist, FermiLab and Matthias Fey, Ph.D. Student at TU Dortmund
2:59:50 – Model Interpretability – Narine Kokhlikyan, Researcher Scientist, Facebook AI
3:11:55 – Hyperparameter Importance – Crissman Loomis, Engineer/Business Dev, Preferred Networks
3:22:00 – DeepSpeed, Yuxiong He, Partner Research Manager at Microsoft
3:32:30 – MLPerf & PyTorch at NVIDIA – Christian Sarofeen, Manager of PyTorch, NVIDIA
3:41:40 – Inspirations from Going Abroad – Thomas Viehmann, PyTorch Guru, MathInf GmbH

Production Ecosystem

3:53:40 – Reproducible AI using PyTorch and MLFlow – Geeta Ghauhan, PyTorch Partner Engineering, Facebook AI
4:07:00 – PyTorch/XLA Internal – Jack Cao, Software Engineer, Google
4:15:30 – TorchServe: Model Server for PyTorch – Lokesh Gupta, Software Dev Manager, AWS

Private AI

4:24:20 – Differential Privacy on PyTorch – Davide Testuggine, Applied Scientist, Facebook AI
4:35:45 – The future of AI tools – Andrew Trask, Leader of OpenMined and Ph.D. Student at Oxford University
4:51:00 – Private AI Education Series Announcement – Andrew Trask, Leader of OpenMined and Joe Spisak, PyTorch Product Manager, Facebook AI

Source of this PyTorch AI Video

AI video(s) you might be interested in …