Tootfinder

We've updated the What Uses More app to reflect last week's finding by Luccioni and Gamazaychikov that "reasoning" mode increases energy and water usage by 30x. The study casts doubt on the improved efficiency AI companies are claiming for newer models
https://www.

Automating Structural Engineering Workflows with Large Language Model Agents
Haoran Liang, Yufa Zhou, Mohammad Talebi Kalaleh, Qipei Mei
https://arxiv.org/abs/2510.11004 https:/…

Automating Structural Engineering Workflows with Large Language Model Agents
We introduce $\textbf{MASSE}$, the first Multi-Agent System for Structural Engineering, effectively integrating large language model (LLM)-based agents with real-world engineering workflows. Structural engineering is a fundamental yet traditionally stagnant domain, with core workflows remaining largely unchanged for decades despite its substantial economic impact and global market size. Recent advancements in LLMs have significantly enhanced their ability to perform complex reasoning, long-hori…

Cold-atom fountain for atom-surface interaction measurements mediated by a near-resonant evanescent light field
Taro Mashimo, Masashi Abe, Athanasios Laliotis, Satoshi Tojo
https://arxiv.org/abs/2511.08115

Much of what I post on here is about Vancouver transit. But today I got to read about (some of) the history of Seattle. I recommend it. And venture to suggest that you might find Transit Sleuth's upcoming material worthy of your attention too.
https://transitsleuth.com/2025/12/06/s

(Some) of Seattle’s Origin Story: From Chief Sealth’s Grace to the Interurban’s Legacy
Seattle’s founding is marked by the arrival of white settlers in 1851, led by Arthur Denny, who exploited the Duwamish people’s land. Despite the settlers’ entitlement, Chief Sealth aided the…

Is #AI really just dumb statistics? "Olympiad-level physics problem-solving presents a significant challenge for both humans and artificial intelligence (AI), as it requires a sophisticated integration of precise calculation, abstract reasoning, and a fundamental grasp of physical principles," says the (abstract of the) paper https://arxiv.org/abs/2511.10515: "The Chinese Physics Olympiad (CPhO), renowned for its complexity and depth, serves as an ideal and rigorous testbed for these advanced capabilities. In this paper, we introduce LOCA-R (LOgical Chain Augmentation for Reasoning), an improved version of the LOCA framework adapted for complex reasoning, and apply it to the CPhO 2025 theory examination. LOCA-R achieves a near-perfect score of 313 out of 320 points, solidly surpassing the highest-scoring human competitor and significantly outperforming all baseline methods." Oops ...?

Reinforced Preference Optimization for Recommendation
Junfei Tan, Yuxin Chen, An Zhang, Junguang Jiang, Bin Liu, Ziru Xu, Han Zhu, Jian Xu, Bo Zheng, Xiang Wang
https://arxiv.org/abs/2510.12211

Reinforced Preference Optimization for Recommendation
Recent breakthroughs in large language models (LLMs) have fundamentally shifted recommender systems from discriminative to generative paradigms, where user behavior modeling is achieved by generating target items conditioned on historical interactions. Yet current generative recommenders still suffer from two core limitations: the lack of high-quality negative modeling and the reliance on implicit rewards. Reinforcement learning with verifiable rewards (RLVR) offers a natural solution by enabli…