wafngar

Image support is much better in iterm2, you can open them, save them - then you can easily download any file. And fonts also look much nicer.

You are proud of tax evasion? Would be fun to restrict market access for Swiss companies …

Very common in ML research these days - claim novelty / cite prior work in an obfuscated way and so on.

But they have built a fully “independent” pipeline. Deepseek and others probably trained in gpt4, o1 or whatever data.

Why not use torch.compile()?

They train with ERA5 and observations.

Brussels is quite small. Probably less than Washington.

Depends. PyTorch on the other hand has a large user base and well defined and tested api. So should be doable; and is already progressing and rapid speed..

Probably unfair as a reaction to the unfair statements in the blog…

PyTorch is developed by multiple companies / stake holders while jax is google only with internal tooling they don’t share with the world. This alone is a major reason not to use jax. Also I think it is more the other way around: with torch.compile the main advantage of jax is disappearing.

For AI you have to support PyTorch. That works well now on the big AMD GPUs. Consumer gpu capabilities do not matter here.