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