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
