Why do you believe it will be the future, and what do you see as the barriers to roll-out? I ask as someone who is curious about when/whether to start investing in Julia competence
https://julialang.org/blog/2012/02/why-we-created-julia
I've been playing around with it. As a Python/MATLAB guy, the syntax is very friendly. I can see it displacing Python in production code where you need speed and might avoid some of the heavy Python DS libraries. Overall it seems like a thoughtful combo of a lot of good numerical programming features.
But so far we have seen great development. Flux is a truly beautiful ml library. Being a compiled language remove a lot of headache when building production images. The syntax, the full utf support in variable name. Package management is great. Having that abstraction layer between CPU, GPU so you don't have to rewrite code. Dispatch based on signature, type management. I don't see it going away soon. It took me 13 years to make them transition out of SAS, good thing cloud computing come around and someone realised the clusterfuck of having to manage SAS licence in the cloud.
Right now the only way to do that without significant performance costs is to drop down into C or avoid the problem completely by using Julia.
Having worked with both R and Python on large datasets, I think both languages are really easy until they aren’t. Eventually you hit a performance wall.