Using Local LLMs to Discover High-Performance Algorithms

A developer used local AI models on a MacBook Pro to automatically generate and optimize matrix multiplication algorithms for Rust. Using Microsoft Autogen, five AI agents collaborated where one proposed algorithms, another verified math, a third wrote code, and a fourth tested performance, with results stored in a vector database. After four iterations, the system produced an algorithm using ARM NEON instructions and parallel processing that achieved a 50% speed improvement over standard implementations, demonstrating that consumer hardware can discover meaningful algorithmic optimizations.