[nickvincent]

I'm quite hopeful that language models for code might actually lead to more people getting comfortable with multiple languages and especially some kind of hopping back and forth. I think the prospect of starting off your script in Python (which is a "comfort food" for many, including myself), using LLM to translate over to Julia, probably do some minor debugging, and then taking off from a starting point instead of a blank file could be a nice workflow for people who want to dip their toes in.

[CoreyFieldens]

If you can use LLM's to translate your code from one language to another, why would you translate Python to Julia? Even the most ardent Julia supporters will admit that Julia code will be slower than optimized C and C++ code. Why not just use an LLM to rewrite your Python into those languages?

[adgjlsfhk1]

> Julia code will be slower than optimized C and C++ code

This isn't true. Optimized Julia will pretty much always tie optimized C/C++. This shouldn't be surprising. They use the same compiler and run on the same hardware and both let you use inline assembly where needed. Octavian often beats MKL at matmul, and the Julia math library is written in Julia and doesn't lose performance from doing so.

Rewriting to Julia instead of C/C++ has the benefit that the code is still readable and improvable by scientists who wrote the code in the first place.

[nickvincent]

Yeah, that's what I'm basically thinking: for scientists who already like Python because it's readable and mostly matches the mental model of what they care about, being able to catalyze the switch to a different, faster language that still reads nicely could really drive adoption. But it's a stretch for sure!

[dunefox]

Not going to happen because the majority of Python users don't know Julia exists and see no reason to switch to anything else.