AI 研究レーダー — 第 40 週

NMI

論文Nature Machine Intelligence·2026/10/01

Large language models discover complementary heuristics for combinatorial optimization

Nature Machine Intelligence, Published online: 01 October 2026; doi:10.1038/s42256-026-01307-8 Huatian Gong and colleagues developed LACE, a large language model-based framework that designs optimization algorithms. It builds a verified problem contract, then evolves a portfolio of complementary heuristics that together solve problems that no single method can handle.

NMI

論文Nature Machine Intelligence·2026/09/30

Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pretraining

Nature Machine Intelligence, Published online: 30 September 2026; doi:10.1038/s42256-026-01309-6 Alonso-Monsalve et al. demonstrate that self-supervised pretraining helps deep learning models to interpret complex neutrino detector events, improving classification, reconstruction and data efficiency while enabling transfer across different neutrino detector technologies.

NMI

論文Nature Machine Intelligence·2026/09/28

Regional climate risk assessment from climate models using probabilistic machine learning

Nature Machine Intelligence, Published online: 28 September 2026; doi:10.1038/s42256-026-01308-7 A generative AI framework called GenFocal is introduced for climate downscaling, producing realistic fine-scale weather from coarse projections and improving regional risk estimates of compound extremes such as heatwaves and tropical cyclones.

AI

研究OpenAI Research·2026/09/30

Helping small businesses put AI to work

OpenAI is partnering with America’s SBDC to expand hands-on AI training and local support for small businesses, alongside a new report on how small teams are using AI.