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10月7日周三
  1. Lingxi Li52

    Elon Musk 宣布 SpaceX 的 Grok @Bot 之后会为每个任务选用最合适的后端模型,包括 Claude Opus 5.5、MidJourney、Suno 及其他领先 API,以最大化任务效果。Lingxi Li 转发并表示欢迎试用。

    引用Elon Musk@elonmusk

    Important note regarding Grok @Bot: Going forward, @SpaceX will use the best back end model for any given task, including Claude Opus 5.5, MidJourney, Suno and other leading APIs. Whatever is most likely to give you the best outcome.

  2. Arena.ai68

    Arena 宣布 Mistral Large 4 登陆 Code Arena: WebDev,以 1534 分排名第 45,比 Mistral Large 3(第130名)高 304 分,比 Mistral Medium 3.5 高 271 分。

    引用Mistral AI@MistralAI

    认识一下 Mistral Large 4,又名 Le Chonk。 • 1T 参数,原生多模态。49B 激活。 在综合基准测试中,它是来自美国或欧洲的最佳开放权重模型。 • 在关键工作负载上达到最先进水平,包括网络防御、制造业和金融,并且在视觉定位方面超越了闭源前沿模型。 • 端到端在欧洲打造,并可通过我们自己的 Mistral Cloud 基础设施从欧洲部署。 • 今天即可通过 API 向所有人开放。正与网络安全合作伙伴私下合作。 开放权重版本将于十月底发布。

    推荐理由:Arena 实测数据显示 Mistral Large 4 的编码得分、排名和价格对比,可帮读者评估其性价比位置。

  3. Rohan Paul47

    Smallest AI 的 Pulse 在 Voice Arena 的 Diarization + ASR 赛道以 24.4% DER(0 ms collar)排名第一,比第二名 ElevenLabs Scribe v2 的 40.7% 低 1.7 倍错误率。

    引用Voice Arena@voicearena_ai

    Pulse by @smallest_AI currently ranks #1 in the Diarization + ASR track by DER, as the newest entry on the Voice Arena Diarization Bench. The Diarization + ASR track ranks Speaker-Attributed ASR systems that return speaker labels together with the transcript. Seven systems are in it today. Pulse scores 24.4% DER at a strict 0 ms collar. The next system, ElevenLabs Scribe v2, scores 40.7%. That is 1.7x lower error than the next best in the track. Most of the gap is missed speech. For every other system in the track, missed speech is the largest part of the error, above 30% for each of them. Pulse misses 4.4% of reference speech, the lowest in the track. On the full board of 13 systems, dedicated diarization models and Speaker-Attributed ASR systems together, Pulse places 5th. It is the highest-ranked Speaker-Attributed ASR system on the board and sits ahead of two dedicated diarization models. The result holds across settings: In-person recordings : 24.7% DER In online calls : 22.4% DER Congratulations to @smallest_AI 👏 View full results, per track and per condition: http://voicearena.com/diarization-bench

  4. Josh Woodward62

    Nano Banana 2.1 发布,官方称在视觉设计、蒙版编辑、主体一致性和更自然的图像观感上超越前代。用户现可在 Gemini App 和 Google AI Studio 等入口使用;Google Labs VP Josh Woodward 表示蒙版编辑是此次更新中他最喜欢的功能,并预告后续还有更多更新。

    引用Nano Banana 2.1@NanoBanana

    Nano Banana 2.1 is here! This upgraded version outperforms our previous models across the board, with notable leaps in: - visual design - mask-based editing - subject consistency - more natural-looking imagery Try it now in @GeminiApp, @GoogleAIStudio, and more.

  5. Rohan Paul59

    Nvidia 逼近 6 万亿美元市值,年内涨约 28% 到 30%,同时交易市盈率低于标普 500。最新上涨来自 1500 亿美元回购授权,超过 Apple 2024 年的 1100 亿美元,公司还给出 2028 财年约 70% 的营收增长预测,高于分析师建模的约 44%;作者认为折价反映市场怀疑这个体量能否保持这种增速。

    引用Rohan Paul@rohanpaul_ai

    Bloomberg: SpaceX is in early talks to borrow $40B for Nvidia chips, with Apollo Global Management leading. The package would pair about $10B in bank loans with $30B of investment-grade debt and should close in 2027, according to the Financial Times. Musk has earlier said SpaceX will build exclusively on Nvidia hardware. Many of those chips get rented out, because SpaceX now runs a cloud business in which Anthropic could pay it up to $84.5B through 2029.

  6. Greg Brockman55

    OpenAI 发布一系列由内部前沿模型产出的新数学结果,仓库地址 https://github.com/openai/math。发布前咨询了高等研究院数学与人工智能独立顾问小组,并参考其建议和公开推荐来决定发布方式。Greg Brockman 转发此事,称其朝加速科学发现和改善每个人生活质量的方向迈进。

    引用OpenAI@OpenAI

    We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. https://github.com/openai/math

  7. Rohan Paul67

    OpenAI 发布 722 篇 AI 生成的数学证明论文,覆盖 372 个数学结果族。其中矩阵乘法证明将 2 个 n×n 矩阵乘法的已证明成本从 AlphaEvolve 今年 8 月创下的约 n^2.371177 降至约 n^2.25,并附 Lean 形式化,但这是理论界,尚未给工程师提供可用于真实 GPU 负载的更快例程;这些结果来自内部模型处理约 4K 研究问题后的分组过滤,每个平均使用约相当于 3 小时 ChatGPT Pro 思考的算力。

    引用Rohan Paul@rohanpaul_ai

    OpenAI published the full papers behind its open-problems claim: 722 manuscripts covering 372 math results. OpenAI built this catalogue by giving its internal model roughly 4K research problems during testing, then grouping and filtering the output into 372 significant result families. Almost all of those results came from the same standard setup, and each used on average the computing equivalent of 3 hours of ChatGPT Pro thinking.

  8. Rohan Paul65

    OpenAI 在 GitHub 公开发布内部前沿模型产出的数学论文与证明材料,共 722 篇手稿,整理为 372 个结果族。测试时模型被喂入约 4K 个研究问题,每项结果平均使用相当于 3 小时 ChatGPT Pro 思考的算力;部分结果尚无 Lean 形式化,可能存在问题,仓库将持续更新。

    引用OpenAI@OpenAI

    We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. https://github.com/openai/math

  9. dominik kundel58

    OpenAI 推出 Decisions API 公共测试版,向所有开发者开放,可让应用近实时选择合适的模型、工具或动作,决策速度比通过 Responses API 调用 GPT-6 Luna 快最多 10 倍。Dominik Kundel 转发官方公告并附上更长的演示视频 https://www.youtube.com/watch?v=FB6oCmrIj-Y。

    引用OpenAI Developers@OpenAIDevs

    让你的应用通过 Decisions API 近乎实时地选择正确的模型、工具或操作,现已面向所有开发者开放公开测试版。 Decisions API 通过 Responses API 做出决策的速度比 GPT-6 Luna 快达 10 倍。

  10. Rohan Paul58

    Anthropic 扩展 Cyber Verification Program,将 Project Glasswing 并入,经审核的安全专业人员可通过三个访问层级使用 Claude Mythos 5.1、Opus 5.5 和 Sonnet 5.5。

    引用Anthropic@AnthropicAI

    We’re expanding our Cyber Verification Program to give security professionals broader access to our most capable models. Through this program, verified security professionals can access Claude Mythos 5.1, Opus 5.5, and Sonnet 5.5 with safeguards designed for defensive work. We’re also opening up new tiers to allow for authorized offensive work, like penetration testing and red-teaming. https://www.anthropic.com/news/cyber-verification-program

  11. Rohan Paul62

    AutomationBench Verified 发布,对 Zapier AutomationBench 全部 600 个公开任务的评分器逐一审计,Agent 标记 323 个可疑项,人工确认 206 个真实 bug 并全部修复。

    引用shaped@shaped

    AutomationBench Verified is out. We went through all 600 public tasks in @Zapier's AutomationBench and checked every verifier. • Agents flagged 323 verifiers as suspicious, human review confirmed 206 real bugs, all 206 are fixed. • We replayed 1,235 Kimi K3 runs on the old and fixed verifiers and 344 of them (27.9%) got a different grade • Where verifiers were too strict, pass rate went from 18.8% to 43.8% • Where they were too lenient, it dropped from 60.2% to 49.7% Audit and dataset links below.