A Stanford-led paper titled "Intelligence per Watt" (arXiv 2511.07885) reports that AI inference efficiency improved 5.3 times from 2023 to 2025, with model improvements contributing a 3.1 times gain …
A study by researchers including Jon Saad-Falcon, submitted to arXiv, proposes intelligence per watt (IPW) as a unified metric for local AI efficiency, finding that local language models with up to 20…
Local AI models can now answer 89% of everyday chat and reasoning queries as well as frontier cloud models, according to a November 2025 study by Stanford University and Together AI. The best local mo…
At a YC Paper Club event in Mountain View, five researchers presented on performance optimization in AI, covering multi-GPU kernels, intelligence per watt, AI-written systems code, heterogeneous infer…