What's PyTorch XLA? Why should you care? How is it implemented? How does PyTorch XLA trade off functionality versus ease of performance debugging? What are some new developments in this space?Further reading.<ul><li>XLA's repo has lots of really good docs. Check out <a href="https://github.com/pytorch/xla/blob/master/OP_LOWERING_GUIDE.md">https://github.com/pytorch/xla/blob/master/OP_LOWERING_GUIDE.md</a> and also the main <a href="https://github.com/pytorch/xla/blob/master/README.md">https://github.com/pytorch/xla/blob/master/README.md</a></li><li>Alex Suhan's RFC about lazy core <a href="https://github.com/pytorch/rfcs/pull/18">https://github.com/pytorch/rfcs/pull/18</a></li></ul>

Expect tests

The PyTorch Developer Podcast is a place for the PyTorch dev team to do bite sized (10-20 min) topics about all sorts of internal development topics in PyTorch.