PyTorch is now one of the most popular machine learning frameworks out there but that was not a foregone conclusion when it was released in 2016. Our host Pascal is joined by Suraj, a developer advocate here at Meta, to dissect the history of PyTorch and look at the factors that contributed to its success. That includes understanding your target audience, maintaining backwards compatibility, fostering a helpful community and so much more.

 You don't need to be an expert in PyTorch to enjoy the discussion as Suraj explains all the basics.

Got feedback? Send it to us on Twitter (https://twitter.com/metatechpod), Instagram (https://instagram.com/metatechpod) and don’t forget to follow our host @passy (https://twitter.com/passy and https://mastodon.social/@passy). Fancy working with us? Check out https://www.metacareers.com/.

Links:

• Meta Open Source Blog: Creating Safe Spaces for Underrepresented Individuals in Open Source Communities - https://developers.facebook.com/blog/post/2023/05/31/creating-safe-spaces/ 

• PyTorch Developer Podcast - https://pytorch-dev-podcast.simplecast.com/

• PyTorch - https://pytorch.org/ 

• PyTorch on GitHub - https://github.com/pytorch/pytorch

• Announcing the PyTorch Foundation: A new era for the cutting-edge AI framework - https://ai.facebook.com/blog/pytorch-foundation/

Timestamps:

• • Intro 0:05

  • Suraj Intro 1:52

  • What is PyTorch? 4:39

  • History of PyTorch 5:33

  • Choosing a Target Audience 7:27

  • Python and Performance 11:20

  • Design Decisions 19:04

  • OSS Governance and Community 21:11

  • PyTorch 2.0 25:47

  • How to get started 28:32

  • Outro 30:14

  • Bloopers 32:16