On: Julia adoption keeps climbing

[chalst]

Autodiff is a place where there is a gulf between Julia and Python, one that I think can't be bridged well: JuliaDiff is astonishingly flexible and performant.

https://www.juliadiff.org/

[oxinabox → chalst]

Urg that website is so incredibly out of date. Julia has amazing things for autodiff. But like not the things listed on that website.

Also python is still doing great with Jax and PyTorch.

[chalst → oxinabox]

I linked to the website (which was updated in May, but its contents could do with more work) because it has examples of how well the suite fits together.

I don't know much about Jax. I've seen competent benchmarks showing an order of magnitude benefit for using ReverseDiff from the AutoDiff suite over Autograd, which is what Pytorch uses for reverse-mode autodiff

[oxinabox → chalst]

It was update in May to fix that the CDN changed. The actual content hasn't been updated in 7 years.

It really should be updated to have basically the content of this thread https://discourse.julialang.org/t/state-of-automatic-differe...