llama.cpp WASM Gets 2x Speedup Thanks to Optimized SIMD

Simon Willison's blog post highlights a significant performance improvement in llama.cpp: a 2x speed increase for the WASM version achieved by optimizing SIMD instructions. Surprisingly, 99% of the code was generated by the AI-assisted programming tool DeepSeek R1. DeepSeek R1 spent 3-5 minutes 'thinking' about each prompt, ultimately helping the developer improve the llm_groq.py plugin and elegantly eliminate the model_map, streamlining the code. This showcases the immense potential of AI in code optimization and refactoring.