Earlier quoted context omitted.
Lots of things are being rewritten. Remember we just released a new neural network library the other day, SimpleChains.jl, and showed that it gave about a 10x speed improvement on modern CPUs with multithreading enabled vs Jax Equinox (and 22x when AVX-512 is enabled) for smaller neural network and matrix-vector types of cases ( https://julialang.org/blog/2022/04/simple-chains/ ). Then there's Lux.jl fixing some majo…
The fact that things are being rewritten and the primary criteria being looked at is speed IS culturally a big part of the problem. If you don't prioritize provable correctness first, then I guarantee that the code is not correct. And as the complaint explains, incorrect code costs people months and leads them to not trust the result. Don't believe me? Re-read the blog post about how a major source of bugs is people…
There's been a decent number of posts based around "Julia has these problems". And I don't think that's because the world at large has a vendetta; I think it's because the world at large desperately wants to use Julia, but struggle with hard blocks that are currently preventing adoption.
FWIW I do think there's a growing acceptance in the Julia community that these concerns are real, which is good. (See the parallel discussion on the Julia Discourse.)