[havercosine]

This is spot on. I love Julia, whatever little I have dabbled into it. History of deep learning would have been slightly different if Julia had taken off as the implementation language. Might have encouraged more hackability and understandability. Wrapping our heads around Pytorch source or Jax source is tough.

But this introspection gave me a reality check. In my own work, as much as I love Julia, I fallback to quickly using Python libs. In industry, most of the people's focus is on using someone's already written code. The byproduct is inheriting Python and C/C++ interface mess around dependency management. People needing to write their own algorithms are majority academics and researchers where Julia has flourished.

The incentives of corporate work are setup to build on top of Python's ecosystem which means (sadly) Julia will stay in its niche.