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A comment on JAX – NumPy on the CPU, GPU, and TPU, with great automatic differentiation. Parent comment

Re:JAX – NumPy on the CPU, GPU, and TPU, with great automati... by __rito__ on Friday September 29, 2023 @03:18AM (#37700321)
> "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.

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Re:JAX – NumPy on the CPU, GPU, and TPU, with great automati... by matrss on Friday September 29, 2023 @04:50AM (#37701000)
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.

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Re:JAX – NumPy on the CPU, GPU, and TPU, with great automati... by mattjjatgoogle on Friday September 29, 2023 @12:00PM (#37706167)
You're right! Maybe we should revise that... I made https://github.com/google/jax/pull/17851, comments welcome!
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Re:JAX – NumPy on the CPU, GPU, and TPU, with great automati... by londons_explore on Friday September 29, 2023 @07:39AM (#37702249)
So was tensorflow... And yet it's pretty much dead.
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