Ruv-FANN

About

Ruv-FANN is a pioneering neural intelligence framework designed to make AI ephemeral, accessible, composable, and surgically precise. It includes a complete, memory-safe Rust rewrite of the Fast Artificial Neural Network (FANN) library, advanced Neuro-Divergent forecasting models that outperform traditional frameworks, and a revolutionary ruv-swarm system for distributed, multi-agent intelligence. This framework empowers developers to instantiate intelligence on demand, deploy it efficiently via WebAssembly on any CPU-native platform, and orchestrate complex problem-solving with unprecedented speed and resource efficiency.

Key Features

• 290 GitHub stars
• CPU-native WebAssembly deployment for running intelligence anywhere from browser to RISC-V
• Significant performance gains: 2.8-4.4x faster and 29% less memory usage than traditional frameworks
• Pure Rust rewrite of FANN with zero unsafe code and blazing performance
• 27+ state-of-the-art neural architectures including LSTM, N-BEATS, and Transformers
• Ephemeral swarm intelligence system achieving 84.8% SWE-Bench solve rate

Use Cases

• Developing high-performance, memory-safe neural networks for core AI tasks
• Implementing advanced forecasting models for time-series analysis and prediction
• Orchestrating distributed, multi-agent AI systems for complex problem-solving and task automation