PyTorch vs. TensorFlow in 2022
As a researcher in RL & ML in a big industry lab, I would say most of my colleagues are moving to JAX [<a href="https://github.com/google/jax" rel="nofollow">https://github.com/google/jax</a>], which this article kind of ignores.  JAX is XLA-accelerated NumPy, it's cool beyond just machine learning, but only provides low-level linear algebra abstractions.  However you can put something like Haiku [<a href="https://github.com/deepmind/dm-haiku" rel="nofollow">https://github.com/deepmind/dm-haiku</a>] or Flax [<a href="https://github.com/google/flax" rel="nofollow">https://github.com/google/flax</a>] on top of it and get what the cool kids are using :)