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Exploring PyTorch and Open-Source Communities with Soumith Chintala, VP/Fellow of Meta, Co-Creator of PyTorch

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Manage episode 371232505 series 2777250
Content provided by Lukas Biewald. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Lukas Biewald or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

On this episode, we’re joined by Soumith Chintala, VP/Fellow of Meta and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch.

We discuss:

- The history of PyTorch’s development and TensorFlow’s impact on development decisions.

- How a symbolic execution model affects the implementation speed of an ML compiler.

- The strengths of different programming languages in various development stages.

- The importance of customer engagement as a measure of success instead of hard metrics.

- Why community-guided innovation offers an effective development roadmap.

- How PyTorch’s open-source nature cultivates an efficient development ecosystem.

- The role of community building in consolidating assets for more creative innovation.

- How to protect community values in an open-source development environment.

- The value of an intrinsic organizational motivation structure.

- The ongoing debate between open-source and closed-source products, especially as it relates to AI and machine learning.

Resources:

- Soumith Chintala

https://www.linkedin.com/in/soumith/

- Meta | LinkedIn

https://www.linkedin.com/company/meta/

- Meta | Website

https://about.meta.com/

- Pytorch

https://pytorch.org/

Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.

#OCR #DeepLearning #AI #Modeling #ML

  continue reading

107 episodes

Artwork
iconShare
 
Manage episode 371232505 series 2777250
Content provided by Lukas Biewald. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Lukas Biewald or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

On this episode, we’re joined by Soumith Chintala, VP/Fellow of Meta and Co-Creator of PyTorch. Soumith and his colleagues’ open-source framework impacted both the development process and the end-user experience of what would become PyTorch.

We discuss:

- The history of PyTorch’s development and TensorFlow’s impact on development decisions.

- How a symbolic execution model affects the implementation speed of an ML compiler.

- The strengths of different programming languages in various development stages.

- The importance of customer engagement as a measure of success instead of hard metrics.

- Why community-guided innovation offers an effective development roadmap.

- How PyTorch’s open-source nature cultivates an efficient development ecosystem.

- The role of community building in consolidating assets for more creative innovation.

- How to protect community values in an open-source development environment.

- The value of an intrinsic organizational motivation structure.

- The ongoing debate between open-source and closed-source products, especially as it relates to AI and machine learning.

Resources:

- Soumith Chintala

https://www.linkedin.com/in/soumith/

- Meta | LinkedIn

https://www.linkedin.com/company/meta/

- Meta | Website

https://about.meta.com/

- Pytorch

https://pytorch.org/

Thanks for listening to the Gradient Dissent podcast, brought to you by Weights & Biases. If you enjoyed this episode, please leave a review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation.

#OCR #DeepLearning #AI #Modeling #ML

  continue reading

107 episodes

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