数学界31年未解难题KLS猜想获证：高维几何与随机算法理论取得根本性突破
微软研究院研究员张鑫志与合作者于2026年10月4日完成Kannan–Lovász–Simonovits（KLS）猜想的严格证明，终结了自1995年提出以来长期悬而未决的核心问题。该成果确立了高维对数凹分布中‘平面切割瓶颈’的维度无关常数界，为随机采样、凸优化与理论计算机科学提供了无条件理论基础。
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谷歌云与英伟达宣布NVIDIA Vera Rubin基础设施正式商用：A5X实例上线，聚焦大规模强化学习与智能体推理
谷歌云与英伟达宣布基于Vera Rubin架构的A5X实例将于下月起正式商用，首期覆盖美国，后续扩展至欧洲；该平台整合NVL72 GPU、ConnectX-9 SuperNICs、Virgo网络及第四代液冷技术，专为大规模强化学习、生成式智能体推理等高密度计算场景设计。
Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.
Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.
译文排队中，当前为原文 · enNVIDIA发布Kumo Forecast：融合预训练时序表征、历史模式检索与可解释性的多变量预测模型
NVIDIA推出开源时序预测模型Kumo Forecast（原NV-Tesseract Forecasting），基于MOMENT-1-large Transformer架构，支持直接预测与Domain-Aware Representation and Retrieval（DARR）双路径推理，并内置无需修改模型结构的可解释性框架。
Using thousands of AI agents to uncover new leads in biological data
See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.
译文排队中，当前为原文 · enPatch the Planet: global response coordination as agents uncover critical vulnerabilities
Patch the Planet connects security researchers, maintainers, and incident responders to help address critical vulnerabilities across open source.
译文排队中，当前为原文 · en“我们一直看错了”：Goodfire研究员提出神经网络可解释性新视角，引发AI界震动
Goodfire研究员Nick Cammarata发布26000字长文，主张大语言模型（LLMs）的内部机制可能远比学界预想的更结构化、更可理解；其核心论点基于对Inception v1等模型中‘多义神经元’的重新诠释——如‘猫/车共用神经元’实为响应V形视觉模式，而非无序超置。该观点尚未在现代LLM上完成系统验证，遭斯坦福大学Chris Potts、Alignment Research Center Jacob Hilton等学者质疑其普适性与技术深度。
谷歌研究推进AI代理扎根真实湿实验室：构建自主生物发现的三大技术基石
谷歌研究院发布三项关键技术进展——VERID数字孪生框架、闭环适配体发现系统、靶向表位切除蛋白设计流程，推动AI代理在真实湿实验室中实现可追溯、可验证、自迭代的分子发现闭环。
[AINews] 智能体证伪多义性；显著提升可解释性与对齐性
尼克·卡马拉塔突然抛出了一些重磅言论！
[AINews] 智能体证伪多义性；显著提升可解释性与对齐性
尼克·卡马拉塔突然抛出了一些重磅言论！
Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline
Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline
译文排队中，当前为原文 · enPutting Earth AI to work: Geospatial agents for our planet's biggest challenges
Earth AI
译文排队中，当前为原文 · enSimulating student learning for better AI tutoring
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
译文排队中，当前为原文 · enAgent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
译文排队中，当前为原文 · enWhat AI gets wrong and what failure teaches us
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
译文排队中，当前为原文 · enUnlocking Earth AI’s planetary geospatial foundation models for global public health
Earth AI
译文排队中，当前为原文 · en如何跳跃 Trading 用 ChatGPT 缩放四进制研究
Jump Trading使用OpenAI扩展定量研究. 参见持续时间较长的AI工作流程如何将多个数据源与人文审查相结合.
我们对待欧盟文本来源规则的方法
OpenAI如何接近欧盟规则下的文字水标记. 了解水印的应用地点,检测工作如何,以及为什么访问始于研究人员.
Introducing Quine: An AI research system designed for the complexity of biology
Biology doesn't operate in silos, and neither should the AI representation of it. Quine is an early-stage research effort to create a multimodal world model of biology. By connecting insights across biological scales and modalities, Quine helps scientists computationally search a space far larger than intuition allows and prioritize hypotheses before they reach the lab. Experimental results provide important feedback, helping researchers sharpen future research directions. The post Introducing Quine: An AI research system designed for the complexity of biology appeared first on Microsoft Research.
译文排队中，当前为原文 · enOne year in: How Microsoft Research Asia – Singapore is advancing research, partnership and talent for real-world impact
Since launching a year ago, the Microsoft Research Asia — Singapore lab has established a strong foundation, deepened collaboration across government, academia, and industry, and explored how frontier AI research can create real-world value. The post One year in: How Microsoft Research Asia – Singapore is advancing research, partnership and talent for real-world impact appeared first on Microsoft Research.
译文排队中，当前为原文 · en