Where I am people are really pushing out of the MATLAB/Python world into Julia. It's tailor made for scientific computing in a way that none of the others are.

Where I am people are really pushing out of the MATLAB/Python world into Julia. It's tailor made for scientific computing in a way that none of the others are. Clearly we're talking decades, but I am already realizing pay-offs from the switch to Julia (from Python) in my domain. Rackauckas pointed out an amazing example recently [1]: https://discourse.julialang.org/t/differentialequations-jl-and-measurements-jl/6350 https://discourse.julialang.org/t/differentialequations-jl-a... You have a library that implements calculating with numbers with uncertainties. You have the differential equations library. They don't know about each other but you can use the former in the latter to solve differential equations with uncertainties with a whole bunch of advanced solving algorithms. This sort of power, having an ecosystem like Python that combines in a performant way, will be huge. [1] http://www.stochasticlifestyle.com/why-numba-and-cython-are-not-substitutes-for-julia/ http://www.stochasticlifestyle.com/why-numba-and-cython-are-...