Whatever happened to Julia? Wasn't it supposed to incorporate all these incredible abstractions at the language level and run quickly on GPUs and everything in-between? Is it just lack of adoption or is has it something else?
Though you can already use very clean Pytorch style libraries like Flux and Knet or the Tensorflow bindings to leverage the benefits of Julia for high performance numerical processing on the adjacent tasks such as data preprocessing.
https://arxiv.org/abs/1907.07587
https://news.ycombinator.com/item?id=20477873
From the abstract:
> We describe Zygote, a Differentiable Programming system that is able to take gradients of general program structures. We implement this system in the Julia programming language. Our system supports almost all language constructs (control flow, recursion, mutation, etc.) and compiles high-performance code without requiring any user intervention or refactoring to stage computations.
Just linking to this for those who haven't seen it.
You can take a look at https://discourse.julialang.org/t/where-does-julia-provide-t... for some of my questions.
Essentially, the biggest advantage imo is that Julia offers a single cohesive language, where compilers can do anything at the language level. I don't think this will allow for a single killer application - almost anything Julia can do ca n be simulated by some combination of Python/C++.
However, what might be true is that using a single language allows for much faster development and iteration than a combination of Python/C++. I think the way that'll manifest is in more and more high quality libraries coming out for Julia that are higher quality than the Python ones.
Maybe wait 5 years, and we'll see what happens :)