The article describes Julia as "a general-purpose programming language aimed at science, engineering, and related arenas of technical computing".
I think this is about right. If you are going to solve differential equations or run some numerical weather codes or solve an integer program or simulate an electrical circuit, it would be a good idea to consider Julia rather than reaching for Fortran, C++, or MATLAB. It is a much nicer language and still very fast.
My experience is that people who want to use Julia for data science and especially for deep learning, usually find that you can get the job done, but often it's easier to use PyTorch or Jax and just accept the limitations of Python.
I think this is about right. If you are going to solve differential equations or run some numerical weather codes or solve an integer program or simulate an electrical circuit, it would be a good idea to consider Julia rather than reaching for Fortran, C++, or MATLAB. It is a much nicer language and still very fast.
My experience is that people who want to use Julia for data science and especially for deep learning, usually find that you can get the job done, but often it's easier to use PyTorch or Jax and just accept the limitations of Python.