Artificial Intelligence algorithms (generative, creative, language models) are currently a major topic, trending not just with tech media but also in mainstream news.


I would note that while the media usually do tend to inflate news stories, AI is currently marked as a “disruptive” technology, with the potential to revolutionize certain industries, meaning it will definitely shift the economic balance in favor of those companies that have access to different AI tools.


Considering how Artificial Intelligence is probably the most valuable technology today, it seems logical that it would be built using the most reliable software available, which is where we must mention RUST coding language.


For those not introduced to it, RUST is a fresh and relatively new multi-paradigm programming language designed for performance and safety, namely it is much safer than C++ which is its main advantage.


Besides utilizing a number of features that help to prevent bugs and errors via safe memory management, Rust also uses a powerful ownership system which helps to prevent data races and other types of memory errors.


While RUST is a powerful and efficient language, it lacks many features that are necessary for building AI models, such as support for deep learning frameworks and libraries.


This is where I must mention a project that deserves its time in the spotlight, the Awesome-Rust-MachineLearning - a repository that collects various RUST frameworks, libraries, software and resources for AI. These libraries cover different aspects of machine learning, such as linear algebra, supervised learning, neural networks, and deep learning1.


It may be interesting to mention other notable RUST projects such as teepee.rs, nickel.rs, and piston.rs … and you may have noticed they all use .RS domain as a community branding. Other AI projects with RUST coding language include:


AI assisted learning: A project that uses ChatGPT, Copilot and Advent of Code to learn RUST1.

OpenAI Codex: A system that generates working code from natural language commands using a large neural network2.

Iced: A cross-platform GUI library with a focus on simplicity and type safety3.


Hope this information was helpful for any avid AI enthusiast, and I hope it will bring more developers interested in AI and data safety to the RUST community.