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

Gradient Dissent: Conversations on AI

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The Technical Difference Between TensorFlow and Jax

I strongly believe TensorFlow stood for a programming model that had a reasonably good chance of success. One of the clearest examples you can take as to why technical direction was not really the reason for TensorFlow to not stand up to expectations is Jax. You have to trace a program ahead of time and then run it later in the XLA runtime. But people find Jax's experience to be totally fine. And I think TensorFlow is going away from its symbolic execution model from the TensorFlow 1.0 to the Tensor Flow 2.0 transition was probably the biggest positive for PyTorch.

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