I don't. It doesn't have the incumbency of R, the use in other areas of programming of Python, or a company actively marketing it like MATLAB. It's not 5x or 10x or whatever good enough than the alternatives to assert itself in the playing field.
If it means you get your work done using it, be all means use it. But I think it will stay around clojure levels of use in data science, statistics, and machine learning.
But who knows. Weird things seem to become popular despite all the negative points.
It can precompile very fast code before runtime.
Python will require an interpreter and or hefty runtime.
https://discourse.julialang.org/t/julia-motivation-why-weren...
Precompiling in Julia is extremely not-straight-forward. You would think you just use --compile and it would work; but it doesn't at all.
Also, at ~850kb, Python's runtime is not that hefty. It's intended to be embedded and while it's quite a bit larger than lua's 200kb, but smaller than libjulia's 16mb.
Julia's runtime includes its compiler and full huge standard lib, but of which are eventually going to be split off, IIUC.
The former because of static compilation potential and the latter into modules that can be included piecemeal.