8 ms·

Gosh, it seems every day I see a new shiny thing made with Rust that was developed remarkably quickly, runs quite smoothly, and appears to be magically bug-free

by cs702 6y ago

Gosh, it seems every day I see a new shiny thing made with Rust that was developed remarkably quickly, runs quite smoothly, and appears to be magically bug-free. I'm sooo tempted to dive into Rust head-in. Have only dabbled a bit with it so far. The main thing holding me back at this point is that Rust seems to lack a decent ecosystem for data science and AI/DL/ML (in particular, a set of crates that has proven useful and stable in real-world AI/DL/ML applications).

shpongled 6y ago
What kind of libraries are you looking for? I know there is ongoing work on things similar to numpy/pandas, but that kinda stuff is more complicated in statically typed languages. That being said, you should definitely give Rust a try. I find it to be an absolute joy to use
- cs702 6y ago
  Yes, it would be great to know there are mature facilities for manipulating dataframes and arrays, along with mature linear/tensor algebra facilities, ideally with support for offloading computation to GPUs and TPUs. The equivalent of something like scikit-learn, even if it fall short of its breadth and depth. Also, facilities for automatic differentiation, or alternatively, stable and well-supported integration with frameworks like TensorFlow and/or PyTorch (tch looks like a possible option). PS. The link shared by dabreegster has a fairly detailed list of missing facilities: https://news.ycombinator.com/item?id=23615175 https://news.ycombinator.com/item?id=23615175
dabreegster 6y ago
http://www.arewelearningyet.com http://www.arewelearningyet.com is a good overview. And if there's something missing, trying to create it yourself could be a way to learn the language, even if the result doesn't actually do everything you need.
- cs702 6y ago
  Thank you for sharing that link. The tagline on that page summarizes my views quite well: "...but the ecosystem isn't very complete yet." It's nice to see that others are thinking the same. I'll take a look.
  - rckoepke 6y ago
    I truly wonder, what is it about this community that leads to such quality software? Your reaction to arewelearningyet is similar to how I feel about: https://areweguiyet.com/ https://areweguiyet.com/ However, at least for GUI I know that Raph Levien is really pushing a focus on GUI at the moment. https://raphlinus.github.io/rust/druid/2019/10/31/rust-2020.html https://raphlinus.github.io/rust/druid/2019/10/31/rust-2020.... I wish I could contribute more. You really summed up how I feel about Rust: "It seems every day I see a new shiny thing made with Rust that was developed remarkably quickly, runs quite smoothly, and appears to be magically bug-free." Even the maligned actix web framework in Rust is still leading performance benchmarks: https://www.techempower.com/benchmarks/#section=data-r19&hw=ph&test=db https://www.techempower.com/benchmarks/#section=data-r19&hw=...
qchris 6y ago
If you're interested, there's an unofficial working group that's been organized to start doing development in machine learning for Rust at https://github.com/rust-ml https://github.com/rust-ml . We actually have a meeting scheduled for later today--you can find details on the Zulip chat, even if you just want to pop in to see what people are up to. As others have mentioned, everything's pretty early-stage, but there's a lot of experimentation going on around scientific computing, GPU acceleration, etc. that you might find interesting, and we're definitely open towards community participation at all levels, even if you're a relative newcomer to the language.
WhatIsDukkha 6y ago
Julia is quite strong in these areas and there is this as a strategy - https://github.com/Taaitaaiger/jlrs https://github.com/Taaitaaiger/jlrs
bigmit37 6y ago
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 6y ago
  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/ 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/31ed37682ef1576b16bca1432ea9f782 https://gist.github.com/lattner/31ed37682ef1576b16bca1432ea9... . See also https://doc.rust-lang.org/book/ch16-00-concurrency.html https://doc.rust-lang.org/book/ch16-00-concurrency.html and https://blog.spencerkohan.com/impressions-of-rust-as-a-swift-developer-2/ 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.

by cs702 6y ago

shpongled 6y ago

What kind of libraries are you looking for? I know there is ongoing work on things similar to numpy/pandas, but that kinda stuff is more complicated in statically typed languages. That being said, you should definitely give Rust a try. I find it to be an absolute joy to use

cs702 6y ago
Yes, it would be great to know there are mature facilities for manipulating dataframes and arrays, along with mature linear/tensor algebra facilities, ideally with support for offloading computation to GPUs and TPUs. The equivalent of something like scikit-learn, even if it fall short of its breadth and depth. Also, facilities for automatic differentiation, or alternatively, stable and well-supported integration with frameworks like TensorFlow and/or PyTorch (tch looks like a possible option). PS. The link shared by dabreegster has a fairly detailed list of missing facilities: https://news.ycombinator.com/item?id=23615175 https://news.ycombinator.com/item?id=23615175

dabreegster 6y ago

http://www.arewelearningyet.com http://www.arewelearningyet.com is a good overview. And if there's something missing, trying to create it yourself could be a way to learn the language, even if the result doesn't actually do everything you need.

cs702 6y ago
Thank you for sharing that link. The tagline on that page summarizes my views quite well: "...but the ecosystem isn't very complete yet." It's nice to see that others are thinking the same. I'll take a look.
- rckoepke 6y ago
  I truly wonder, what is it about this community that leads to such quality software? Your reaction to arewelearningyet is similar to how I feel about: https://areweguiyet.com/ https://areweguiyet.com/ However, at least for GUI I know that Raph Levien is really pushing a focus on GUI at the moment. https://raphlinus.github.io/rust/druid/2019/10/31/rust-2020.html https://raphlinus.github.io/rust/druid/2019/10/31/rust-2020.... I wish I could contribute more. You really summed up how I feel about Rust: "It seems every day I see a new shiny thing made with Rust that was developed remarkably quickly, runs quite smoothly, and appears to be magically bug-free." Even the maligned actix web framework in Rust is still leading performance benchmarks: https://www.techempower.com/benchmarks/#section=data-r19&hw=ph&test=db https://www.techempower.com/benchmarks/#section=data-r19&hw=...

qchris 6y ago

If you're interested, there's an unofficial working group that's been organized to start doing development in machine learning for Rust at https://github.com/rust-ml https://github.com/rust-ml . We actually have a meeting scheduled for later today--you can find details on the Zulip chat, even if you just want to pop in to see what people are up to. As others have mentioned, everything's pretty early-stage, but there's a lot of experimentation going on around scientific computing, GPU acceleration, etc. that you might find interesting, and we're definitely open towards community participation at all levels, even if you're a relative newcomer to the language.

WhatIsDukkha 6y ago

Julia is quite strong in these areas and there is this as a strategy - https://github.com/Taaitaaiger/jlrs https://github.com/Taaitaaiger/jlrs

bigmit37 6y ago

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 6y ago
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/ 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/31ed37682ef1576b16bca1432ea9f782 https://gist.github.com/lattner/31ed37682ef1576b16bca1432ea9... . See also https://doc.rust-lang.org/book/ch16-00-concurrency.html https://doc.rust-lang.org/book/ch16-00-concurrency.html and https://blog.spencerkohan.com/impressions-of-rust-as-a-swift-developer-2/ 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.