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> Such capability can’t even be contemplated on the TPU side because you basically get a black box.

I'll just leave this here: https://jax.readthedocs.io/en/latest/pallas/index.html


Pallas is very new. Given how difficult these things are to debug and how half assed the XLA tooling generally is, I’d give it at least another year, if not two, before I touch it for anything prod related.


Baratza also sell replacement parts for their grinders on their web site, and provide clear instructions on how to install them. I am delighted to support a manufacturer that builds repairable products.


But the interpretation of the journalist is the issue here. Comparing a cost optimized part (TPU v5e) against a performance optimized part (H100) and deciding that this makes Google "behind" is just incorrect.


No, it is not. That's the sparse fp8 flop number, but you need to ignore sparsity and compare bf16 flops not fp8 flops for the comparison the ancestor post is making.


We ship Windows CPU only at the moment.

We don't support Windows GPU because we haven't had the engineer bandwidth to support it well.

We recommend WSL2 for GPU on Windows at the moment because that is a compromise: it allows CUDA support, without us having to support another release variant.

But we welcome community contributions!


Not true!

We release Windows CPU wheels (https://pypi.org/project/jaxlib/#files). So JAX on CPU works great on Windows.

We don't release Windows GPU wheels at the moment, but that's because we're a small team and none of us use Windows personally. We welcome contributions!

(I verified that the Windows CUDA GPU support built as recently as two weeks ago, but I don't have the ability to test that it works.)

We recommend WSL2 because that's just using our existing Linux CUDA release.


Oops so sorry. But this is recent isn't it? I thought it was actually due to XLA/Bazel not supporting it?


Yes, we made this more formally supported recently.

We felt that Windows CPU support was important so everyone can run JAX, even if it's not always the most-accelerated version of JAX. And we got some great PRs from the community that helped fix a few open issues.


Very nice! I just installed, I hope to eventually contribute down the line, especially in terms of custom operators. They weren't even document until recently, and there's still quite some work to add them.


If pypi didn't enforce size limits, I'd agree with you. We routinely have to delete older versions of our package to make space for newer versions.


I enjoyed playing Stellaris on my MacBook M1 pro on a transcontinental flight last night. 4x games work well for passing the time!


I wish Mac OS and Apple hardware supported 8k monitors. I have this monitor and love it, but I can't use it with a Macbook at higher than 4k.


My employer withheld California tax on restricted stock grants for me exactly as described here when I moved out of California years ago.

Other states even have forms for you to submit this calculation to them, see for example New York's IT203-F Schedule B. But you still have to apportion the income between states like this whether there's a form to do it on or not.


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