It matters to package developers. If you can develop packages in Julia rather than in C++ you can move much faster. Also in Julia users of a package can much mo

It matters to package developers. If you can develop packages in Julia rather than in C++ you can move much faster. Also in Julia users of a package can much more easily contribute. A Python programmer cannot easily jump in an fix or add things to a package mostly written in C++. Also writing packages in C++ creates a fair amount of friction. Combining packages becomes easier. The ML world in Julia allows a lot more code sharing while in Python PyTorch and TensorFlow are large monoliths. E.g. different ML packages in Julia can use the same library of activation functions. Each ML library is not a completely different island of functionality.