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9月5日周六
  1. Rohan Paul74

    Anthropic 宣布 Claude 完成费马大定理的首个完整机器验证证明,Claude 在 11 天内以多个智能体将基于 Wiles 的证明转化为 Lean 代码。

    引用Anthropic@AnthropicAI

    Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer proof assistants like Lean can verify—can help. Last month, Claude completed the first formalized proof of Fermat’s Last Theorem, one of the most famous theorems of all time. This was a project experts thought would take many years. It is the largest Lean proof ever written. Fermat’s Last Theorem was first proven in 1995 by Sir Andrew Wiles, more than 350 years after it was conjectured. Our proof, which totals over 13 million lines of code, provides machine verification. More importantly, it proves over 29,000 other theorems that the proof requires, across many areas of math which had never before been formalized. We see this as a major step in the long process of firming up the core of mathematical knowledge, building on work from three centuries of mathematicians and hundreds of contributors to Lean and Mathlib. We are optimistic that AI-assisted verification of mathematical proofs will help reduce the burden of refereeing mathematics in an era where more proofs are being produced than ever before. You can read about the process on our Science Blog: https://www.anthropic.com/research/formalizing-fermats-last-theorem And see the complete proof on GitHub: https://github.com/anthropics/fermats-last-theorem

  2. Rohan Paul57

    Visko 公布 Orbis 1.0 的评测结果:在自动化基准中于 DOVER 美学与技术和 VideoAlign 视觉与运动质量得分最高,并在 VideoPhy-2、Physics-IQ、VBench-2.0 Physics 三个物理合理性协议领先;在随机化人类 Arena 研究中总偏好和时间稳定性均排第一。

    引用Visko Platform@viskoai

    Our evaluation results for Orbis 1.0: Across automated benchmarks, Orbis scores highest on DOVER aesthetic and technical quality, and on VideoAlign visual and motion quality. It also leads three physical-plausibility protocols: VideoPhy-2, Physics-IQ, and VBench-2.0 Physics. In a randomized human Arena study of state-of-the-art real-time interactive video systems, Orbis ranked first in overall preference and first in temporal stability, the prerequisite for long-form generation. Full report: https://www.visko.ai/blog/papers/files/Visko_Orbis_1_0__A_Live_Model_for_Real_TimeInteractive_Long_Video_Generation.pdf

9月4日周五
  1. Rohan Paul46

    Apodex 发布 TRACES,一个针对答案未必已知的困难科学问题的 AI 基准,配套技术报告由首席科学家 @profshengwang 牵头。报告由 10 名 STEM 博士历时两个月、调研 561 个行业后整理出 423 个高价值真实问题,覆盖生物医学、临床转化和前沿模型工程。

    引用Apodex@Apodex_AI

    We invite you to read the full TRACES technical report Inside: the definitions, evaluation rubric, and registry of problems spanning biomedicine, clinical translation, and frontier-model engineering. Led by Apodex Lead Scientist @profshengwang, the report brings together the technical framework underpinning this effort. Behind it: 10 STEM PhDs, two months of research, and 561 industries surveyed to identify 423 problems worth solving—real, high-stakes questions that can take human experts years to work through. Bring a problem. Bring a solver. Both doors are open. *Submit a Problem: https://traces.apodex.com/submit-your-problem *Submit a Solver: https://traces.apodex.com/submit-your-solver

  2. Google Research:Blog64

    Google 联合 HHMI Janelia 发布完整雄性果蝇大脑连接组图谱

    Google 与 HHMI Janelia、MRC 分子生物学实验室及剑桥大学等合作,在 Cell 发表雄性果蝇大脑和中枢神经系统的完整连接组,包含超 166,000 个神经元和 1.25 亿个突触连接,是迄今按神经元数量计最大的大脑图谱。

    推荐理由:原文交代了连接组规模、验证流程和开放获取方式,并说明与雌性图谱配合能支持哪些比较研究。

9月3日周四
  1. ARC Prize:官方博客79

    ARC Prize 发布 OpenAI GPT-6 Astra 在 ARC-AGI-3 上的评测结果

    ARC Prize 报告 OpenAI 的 GPT-6 Astra 在 ARC-AGI-3 Semi-Private 上,Standard harness 得分 62.7%(成本 $26K),Provider Adapter harness 得分 99.9%(成本 $19K),均为 SOTA。

    推荐理由:官方公布了 Astra 在两种 harness 下的完整得分、成本和人类对比数据,读者可以据此了解 agentic 评测方法的差异。

  2. Cohere Labs:官方研究博客65

    Cohere Labs 发布 ATE 数据集:69.6 万 MCP 工具中仅 2.6% 能完整执行职业任务

    Cohere Labs 聚合七个公开目录,构建含 696,291 个工具、123,069 个 MCP 服务器的 Agentic Task Ecosystem 数据集并对外开放。

    推荐理由:研究用近 70 万个 MCP 工具构建供给侧数据集,给出自动化落在职业哪个环节的证据,可与曝光度研究互补阅读。

9月2日周三
  1. IT之家·人工智能46

    新加坡科技设计大学研究发现老年群体更看重 AI 陪伴聊天机器人的真实感而非拟人化

    新加坡科技设计大学研究人员让 140 名 60 至 89 岁老年人与其社交聊天机器人 Ami Chat 互动,研究发表于《老龄化创新》期刊。结果显示,社会关系相关三个指标(拟人化、真实性、AI 社交互动强度)在使用意愿差异中额外解释了 27%;感觉更真实、互动更具回应性时使用意愿更高,但认为机器人更像真人的参与者意愿反而更低;自评健康状况较差者使用意愿更强。