[bigmit37]

Same! I am looking to learn a low-level language and want to learn Rust due to all the things I have been hearing. However all the backend stuff (python)for deep learning is written in C++and nothing yet for Rust. I would love to avoid C++ as the language seems to have a lot of quirks and bugs that take time to get used (from what I hear) and these days I like efficient languages.

As far I know there aren’t any good computer vision libraries for Rust?

[cs702]

Clearly, we are not the only ones feeling this way. I suspect that if PyTorch or TensorFlow were to provide support for rust as a first-class citizen they would get a whole new community of users very quickly -- people looking to write production AI/DL/ML code in a fast, practical, memory-safe, widely used language.

The only other "fast, practical, memory-safe, widely used language" that looks like a real alternative to Rust is Swift. But unlike Swift, rust was designed from the ground up for for data parallelism and other forms of concurrency with "zero-cost abstractions" the allow "fearless concurrency" (e.g., take a look at https://github.com/nikomatsakis/rayon/ to get an idea of what's possible), and for predictable performance (e.g., compiled code doesn't suddenly slow-down to collect garbage or synchronize reference counts among CPUs). Concurrency appears to have been an afterthought in Swift's case, explicitly: https://gist.github.com/lattner/31ed37682ef1576b16bca1432ea9... . See also https://doc.rust-lang.org/book/ch16-00-concurrency.html and https://blog.spencerkohan.com/impressions-of-rust-as-a-swift...

Data parallelism and other forms of concurrency should become more and more important over time as models grow larger and larger, well beyond GPT-3's 175 billion parameters. This would favor rust.