Use-AI.rs: Framework for Reinforcement Learning

What is the project about?

Modern AI can be useful in many practical contexts. However, external providers are often used who neither provide insight into the underlying AI algorithms nor allow sensitive data to be processed on their own hardware. Especially in areas such as robotics, where great advances can be made with the help of real-time reinforcement learning, there is a lack of libraries that offer the possibility to use local resources ideally for AI. Use-AI.rs is a high-performance, practical machine learning and reinforcement learning library in Rust that relies on parallelization. Its high efficiency and parallelization capabilities also make it possible to run complex models for local hosting.

Which audience does the project address?

Robotics, IoT, and business informatics require more and more AI. Unfortunately, existing options offer little possibility of running performance-oriented AI models on your own hardware. This means you are forced to rely on cloud providers. Use-AI.rs is therefore of interest to anyone who wants to use AI on their own hardware economically and, if necessary, locally.

What is to be achieved?

The project goal is to create a usable and robust framework that makes it easy to set up AI agents for your own use. Use-AI.rs consists of three components: a GPU layer, a core layer, and an API layer.