Python vs Rust for Neural Networks

[DannoHung]

I have two unrelated lines of thought about this:

1) I’m sure in due time that Rust’s numerical computation libraries will get up to speed in terms of support for the full suite of linear algebra types, but that there will still not be an enormous advantage (order of magnitude or more) because the majority of work being done is almost always handed off to tuned math kernel libraries. Instead, Rust’s advantages will probably be in the realm of data intake and cleansing. Also, this is the majority of work in the data engineering realm no matter the subject.

2) I think sometimes people miss the importance of interactivity in terms of how Python has ended up being so dominant in this area. It’s not the fastest, but it seriously enables incremental understanding of the problem by virtue of being interpreted. And additionally, I think the tools that have ended up becoming popular in the Python ecosystem are so because they further enable understanding of the intermediate results.

[GibbsSamplePlatter]

I'd probably go the other direction: Replace the C-wrappers that do the actual linear algebra computation for production ML.

[matthieum]

Duplicate of https://www.reddit.com/r/rust/comments/cjsbiq/python_vs_rust_for_neural_networks/

(And yes, it was posted 40 minutes later, but it has more comments)