1. Researchers from UC Santa Cruz have discovered a method to run large language models (LLMs) at a mere 13 watts without compromising performance. 2. The key to this efficiency is the elimination of matrix multiplication in LLM processing, which, when optimized, significantly boosts performance-per-watt. 3. The broader applicability of this approach to AI in general is yet to be determined.