According to Andrej Karpathy (@karpathy), nanoGPT has evolved from a simple educational repository into a benchmark for recursive self-improvement in AI model training. Initially created to help users understand the basics of training GPT models, nanoGPT now serves as a baseline and target for performance enhancements, including direct C/CUDA implementations. This progression highlights nanoGPT’s practical utility for AI developers seeking efficient, lightweight frameworks for rapid experimentation and optimization in natural language processing. The project’s transformation demonstrates clear business opportunities for organizations aiming to build custom, high-performance AI solutions with minimal overhead (source: @karpathy, June 30, 2025).