The Billion Dollar AI Advantage Is Disappearing

This post introduces a new technique for optimizing LLM inference that achieves a 200% improvement in inference speed and a 50% reduction in memory usage. This is accomplished through a novel combination of speculative decoding and a highly optimized kernel for attention mechanisms, allowing for more efficient computation and reduced hardware requirements. The authors demonstrate this on Anthropic's Sonnet 5.5 model, showing significant performance gains that make large models more economically viable.