Yes, but not everyone loves to have dual stack development, I surely didn't, back in the Tcl days, eventually we ask ourselves for how long.

That's not how it works in Python.

The C/C++ is shipped in the form of well-established libraries like Numpy and PyTorch. Very few end users ever interact with the C/C++ parts, except for specialists with special requirements, and library contributors themselves.

It is definitely how it works in Python.

As if there is nothing else to chose from regarding Python performance issues and libraries used by folks.

Not everything is fashionable AI.

The comment thread was specifically about AI, so my comments were specifically meant for that context. I wasn't clear enough, sorry for the confusion.

Can you name specific "un-fashionable" AI projects that are dependent on Python code for things that have any significant performance impact, which are seeing significant benefits from Python JIT implementations?

I guess you will have to ask Microsoft, Facebook, NVidia and Intel why they are bothering then.

Can you name projects at those companies which meet the description?

He cannot

Microsoft, Facebook, NVidia and Intel apparently can.