I've been using R since beta and Julia is the first thing that I've seen since then in numerical computing that reminds me of that time. Julia still has a lot

I've been using R since beta and Julia is the first thing that I've seen since then in numerical computing that reminds me of that time. Julia still has a lot of empty library space compared to R or Python, and isn't perfect, but my guess is it will catch up. R did when it was being compared to SAS, fortran, C/C++, lisp, and so forth. I'll be honest and say that I wish something else more general-purpose (to the point of say, having a bootstrapped compiler) would be in its spot but I can't really complain right now. Maybe something else will catch up. I think for me personally is that R and python is a bit in denial about its performance limitations when it comes to hard problems. You pretty much have to drop down into C/C++ to address them, and for certain things, julia really does do many times better time-wise, without the weeds of C/C++. I think there's some people (myself probably included) that are tired of being forced to choose between the C/C++ and R/python worlds. I think there is a bit of overhyping and/or cult-like nature of julia but I also think some of it is trying to convince people that you don't have to choose between expressiveness and performance.