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> "It took me a while to realize it, but Jax is actually a huge opportunity for a lot of scientific computing."

In all conferences like NeurIPS, in Google ML Community days, etc., whenever there is a JAX workshop/tutorial/talk, it is always touted as a numerical computation library. And it was developed as such. Sure the focus is in ML, but everyone involved in it always have said that this is a general purpose scientific computing library.

Flax, Haiku, etc. are Deep Learning libraries.



Meanwhile, the first sentence in their readme is this:

> JAX is Autograd and XLA, brought together for high-performance machine learning research.

That does not really convey the generality of it that well.


You're right! Maybe we should revise that... I made https://github.com/google/jax/pull/17851, comments welcome!


So was tensorflow... And yet it's pretty much dead.




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