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DeepMind has released AlphaGenome, a machine learning model that predicts the impact of genomic variants at base-pair resolution with a context window of one million base pairs. It matches or outperforms the strongest competing models on 25 of 26 variant effect benchmarks. Accompanied by the AlphaGenome Atlas, which has pre-computed the effects of roughly nine billion single-nucleotide variants — a scale 30 times that of the AlphaFold database — the model weights are permanently free for the scientific community.
DatologyAI launched the Datology Curation Studio, a customizable frontier data curation platform for teams training their own models, positioning data quality as the ultimate compute multiplier.
Steinert-Threlkeld and Szymanik argue that machine learning models can serve as 'cognitive thermometers' for measuring semantic complexity, showing that learning-based measures converge with and sometimes better explain semantic universals than traditional logical complexity approaches.
提出 Dirichlet-Sinkhorn Constant Averaging（DSCA）校准策略，通过在不同协变量分布的数据子集上独立校准候选表达式并取参数均值，为符号回归进化搜索提供额外选择压力，提升函数恢复精度与复杂度权衡。
NEMORA 是一种将 Fast Multipole Method 推广为可学习等变算子的新方法，用于在等变图神经网络中建模长程原子间相互作用，具备线性时间与内存复杂度，可处理数十万原子体系，并在长程基准测试上将力和能量误差降低一个至三个数量级。
A position paper arguing that AI development should move beyond treating a single ground truth as definitive, instead modeling the space of plausible human judgments while distinguishing meaningful ambiguity from annotation noise.
MIT News 发布三问专访，围绕 MIT 统计与数据科学中心主任 Sasha Rakhlin 的新文章，探讨 AI 对大学研究与研究生培养的冲击，以及院系应如何重新定义学术评价与训练方式。
The paper introduces ORACLE, an optimizer-relative constrained learning method that assesses constraint compatibility on the post-optimizer update rather than the objective or gradient, showing improvements over native optimizers in 94% of configurations across eight PDE benchmarks.
该论文提出一种车辆集成的数字孪生框架，通过驱动感知（drive-by sensing）实现桥梁结构健康监测，结合傅里叶神经算子代理模型、贝叶斯优化的传感器设计以及无监督损伤评估，并在澳大利亚和日本的多站点现场试验中完成验证。
本文提出一种可解释的机器学习分析，利用多中心纵向临床队列预测参与正念干预后患者在12周和24周的BDI-II抑郁评分，发现基线严重程度仍是最强预测因子，而短期结局更依赖临床与医院背景，长期结局则更依赖行为依从性和人口统计因素。
MIT professor Christina Delimitrou 使用机器学习优化大型数据中心的资源管理与服务器架构，以提升能效、减少电力浪费，从而缓解数据中心扩张对电网和环境造成的压力。
该论文系统研究了文本分类器在不同服务上下文（批量大小、数值精度、硬件等）下的非不变性，发现标签稳定并不意味着分数稳定，且在 bf16 下仅改变批量形状就能导致高达 56.7 个百分点的预测概率质量偏移，并为每种机制推导了标签稳定性的充分条件和缓解方法。
CuratorMAS proposes a multi-agent orchestration framework that automates dataset curation through five programmable stages—exploration, knowledge retrieval, evaluation, filtering, and skill evolution—reducing noise rates by up to 36.03 pp and improving downstream F1 scores by up to 8.88 pp.
一篇提出 AI 驱动、时序感知的芯片后布线功耗优化框架的论文，使用梯度提升模型集成对功耗修复编辑和修复动作进行排序，同时由确定性 EDA 分析把关约束。论文给出契约与预注册评估协议，但尚未报告训练模型的结果。
A quote from Ben Affleck describing his long interest in computers, digital film workflows, and how convolutional neural networks have been used for edge detection and green-screen compositing in visual effects, posted on Simon Willison's blog.
A part-time AutoResearch practitioner questions how much of autonomous research agent evaluation is genuine scientific inquiry versus optimization search within human-defined problem spaces, and asks what agents would need to demonstrate real research judgment beyond score improvement.
研究显示 AI 模型在科研实验的『品味』（taste）判断上已超越人类，能够选择更有价值的研究方向与实验设计。
An article exploring how machines and AI systems progressively learned to achieve greater precision, tracing the evolution of machine learning techniques and their growing accuracy over time.
A promotional post for the practical book "Reinforcement Learning: Industrial Applications of Intelligent Agents," which covers RL fundamentals, deep RL algorithms like Rainbow, PPO, TD3 and SAC, and their application to long-term sequential decision-making problems in industry.