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星期五

  1. AI Business

    Anthropic 扩大网络安全验证计划并发布更便宜的 Claude Haiku 5.5

    Anthropic 于 10 月 6 日扩大其网络安全验证计划(CVP),为合格安全人员提供 Claude Mythos 5.1、Opus 5.5 和 Sonnet 5.5 三个访问层级,并减少拦截分类器数量。该计划免费,但获准用户需按标准 token 消耗付费。Anthropic 同时发布 Claude Haiku 5.5,主打浏览器使用和客户支持等速度敏感任务,输入 token 在 10 万以内为 0.10 美元、超出部分 0.50 美元,输出 token 在 10 万以内为 0.50 美元、超出部分 2.50 美元。

    open model. At the same time, the Chinese vendors are pressuring providers of proprietary AI models, such as Anthropic, to make their models more accessible to enterprises Related:Nvidia agent safety push raises questions about who governs AI autonomy Cybersecurity verification program This tension is evident in Anthropic’s decision to expand its cyber verification program on October 6. Anthropic originally introduced the CVP in April alongside Project Glasswing and Claude Mythos. The expanded C

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  2. Databricks Blog

    Databricks:医学影像 AI 的真正瓶颈是数据,不是模型

    Databricks 发文指出,医学影像 AI 在医院、学术界、医疗器械与制药四大领域落地不佳,瓶颈在于数据而非模型:影像分散在 PACS、CRO 和中心实验室,难以去标识化,也少与其他模态关联。文中援引数据称,截至 2024 年中 FDA 授权的约 950 款 AI/ML 设备中约 723 款(约 76%)为放射学工具;EXAM 研究中 20 家机构联邦训练使模型 AUC 平均提升 16%、泛化性提升 38%。

    image4.png

    . Segmentation and classification models register in the same catalog as MLflow models, with their lineage back to the exact cohort they were trained on. For imaging specifically, NVIDIA MONAI and VISTA-3D (a foundation segmentation model covering 127 anatomical classes) plug in for auto-segmentation and fine-tuning, with an OHIF viewer embedded in a Databricks App so a radiologist or pathologist can review, correct, and relabel under the platform's security model. MONAI Label's active-learning

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  3. MarkTechPost

    JetBrains 发布 Mellum2.1:面向编码智能体的 12B MoE 开源模型

    JetBrains 发布 Mellum2.1,一个面向编码智能体与快速子智能体的 12B MoE 思考模型,每 token 激活 2.5B 参数,以 Apache 2.0 许可在 Hugging Face 上发布。架构与 Mellum2 相同,升级几乎全部来自真实软件环境中的强化学习,模型可自行探索仓库、编辑文件并检查改动。基准上 SWE-bench Verified 从 2.0 升至 47.0,LiveCodeBench v6 得 82.0,但 SWE-bench Pro、GPQA Diamond 和 AIME 仍落后于 Qwen3.5-9B;GGUF 量化版本从 7.0 GB 起,可在 llama.cpp、Ollama 和 LM Studio 本地运行。

    s files, and checks its own changes. TL;DR Size: 12B total, 2.5B active (64 experts, 8 active), 131,072-token context; Runs on: your own GPUs via vLLM or SGLang (speed tested on 1 NVIDIA H200). GGUF builds start at 7.0 GB for llama.cpp, Ollama and LM Studio; Performance: beats Mellum2 on 15 of 17 listed benchmarks; wins 5 of 17 against Qwen3.5-9B; Best: 82.0 on LiveCodeBench v6, ahead of Qwen3.5-9B (75.4) and Gemma 4 E4B (69.4); Worst: 17.4 on Terminal-Bench 2.1, below Qwen3.5-9B (21.7); Bottom

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星期四

  1. 9to5Google

    Best Buy 开箱特惠:Galaxy Z Fold 8、Pixel 11 Pro 大幅降价

    Best Buy 的 Techtober 促销中,Galaxy Z Fold 8 开箱机最高优惠 628 美元,256GB 版 1322 美元起,512GB 版 1472 美元起;Pixel 11 Pro 开箱机最高优惠近 400 美元,256GB Canyon 版 701 美元。2026 款 Nothing Headphone (a) 在亚马逊降至 129 美元。

    unts on the 2026 Nothing Headphone (a) and giant lineup of Windows laptops and PCs start at just $179 in Best Buy’s updated Techtober Sale – just be sure to also scope out the new NVIDIA RTX Spark-powered Copilot+ PCs no up for pr-eorder too. Sony BRAVIA TVs up to $1,000 off at Amazon – OLED, mini-LED, Google TVs with Gemini, more Amazon just revealed its all-new Alexa Tablets. The new tablets feature ”world-class hardware, personalized intelligence from Alexa+, full Google Play Store access,” a

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  2. The Next Platform

    内存成为 IT 行业核心,AI 时代更是如此

    Gartner 数据显示,半导体市场营收在 2025 至 2026 年间近乎翻倍,但 2026 至 2027 年增速将放缓。自 2022 年 11 月 ChatGPT 引爆 GenAI 热潮以来,DDR4 服务器内存价格上涨 2 至 3 倍,DDR5 上涨 9 至 13 倍,30 TB TLC 企业级 SSD 上涨 6 至 7 倍,30 TB 近线硬盘上涨约 2.5 倍。HBM 成本涨幅相对温和,HBM2 约 8 美元/GB,HBM4 传闻约 16 美元/GB。

    e three makers of HBM stacked DRAM memory – Samsung, SK Hynix, and Micron Technology – and there are no spot prices because the market is not open but dedicated to two GPU makers (Nvidia and AMD) and XPU makers and/or their chip shepherds. So pricing information is a little sketchy. Back when HBM2 debuted in 2017, the rumor was that it cost around $20 per GB, but this settled down to around $8 per GB two years later. With HBM2E, which provided a bandwidth bump, it was around $10 per GB, rising t

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  3. The Rundown AI

    AI 的下一个前沿:人类细胞

    扎克伯格与 Priscilla Chan 的科学非营利组织 Biohub 将 5 亿美元的 Virtual Biology Initiative 扩展为 18 亿美元项目,联合美国 NIH、能源部、Google DeepMind、Meta 和 Isomorphic Labs,目标训练能模拟细胞的 AI,最终打造预测细胞对药物反应的“通用虚拟细胞”。Biohub 科学负责人 Alex Rives 称准确模型需要数万亿细胞数据,而目前最大数据集仅有数亿。

    chance to be featured. Google rolled out its SynthID Detector worldwide, letting anyone scan images, video, and audio for watermarks left by its AI and partners including OpenAI, Nvidia, and Kakao. Anthropic launched Claude Haiku 5.5, a budget model starting at the same $0.10 per million input tokens as OpenAI's GPT-6 Luna while passing it on multiple benchmarks. OpenAI debuted “intelligent UI,” a new GPT-6-powered feature within ChatGPT that lets the assistant answer using interactive charts,

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  4. Wired AI

    Tristan Harris 的科技非营利组织裁员过半,转向“创始人主导”模式

    由 Tristan Harris 联合创办的 Center for Humane Technology 将裁掉 16 名非创始人员工中的约一半,包括执行董事 Julie Guirado 和战略高级总监 Camille Carlton,并终止政策研究与诉讼工作,转向“创始人主导”的公众教育、定向简报和私下协调。该组织年预算约 600 万美元,储备金规模相近,董事会称此举是为应对加速的 AI 风险而聚焦单一战略。

    his was messed up.” Harris cofounded the center with Aza Raskin, the self-proclaimed inventor of the infinite scroll, and Randy Fernando, who once worked in developer education at Nvidia. The goal was to push tech companies to take more responsibility for the social consequences of their products, which in the early days meant examining issues like whether they were fomenting political radicalization or harming the mental health of teenagers. The language Harris used to describe these problems w

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  5. MarkTechPost

    Architect 推出 Liquid Inference,为 LLM 推理做实时竞价拍卖

    Architect Financial Technologies 推出 Liquid Inference,这是一个对每次 LLM 推理请求进行实时拍卖的路由器,提供方为指定模型报价,买方按最低且符合自身规则的报价成交。买方可在生成前锁定最高价格,并设置单任务成本上限、首 token 时延、最低吞吐、区域、零数据保留和提供方或模型白名单等规则,计费仅按实际用量。该服务兼容 OpenAI 与 Anthropic 客户端,官方称支持 Claude Code、Codex、OpenCode、Cursor、Pi 和 Cline,前 500 名用户可获 20 美元免费推理额度,推荐可获被推荐方费用的 20%。

    ova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights. Michal SutterNVIDIA PivotOPD Teaches Multi-Turn AI Agents to Recover From Pivotal Mistakes; Michal SutterAnthropic Releases Claude Haiku 5.5: A Small Model With 1M Context Priced at $0.10 per Million Input Tokens; Michal SutterReka Releases Rho-1: A 19B Omni-Reasoning Model That Understands, Generates Video and Outputs Robot Action

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  6. The Next Platform

    分布式 AI 训练如何改变数据中心之间的网络

    Google、微软、AWS、Meta 等已把大模型训练扩展到多个数据中心:Google 称 Gemini 采用跨集群同步训练,微软把威斯康星与佐治亚的 AI 数据中心连成一台分布式 AI 超级计算机,AWS 跨广域连接集群供 Anthropic 训练 Claude。Cisco 估计如今训练模型可能需要数万块 GPU 的集群,Epoch AI 预计到 2030 年最大单次前沿训练耗电可达 4-16GW;Cisco 建模显示分布式 AI 部署的聚合带宽需求约为传统 DCI 基线的 14 倍。

    ives hyperscalers and datacenter operators the flexibility to add compute where power and space are available, while still treating multiple sites as part of the same training infrastructure. SPONSORED FEATURE: HPE and NVIDIA help organizations apply accelerated computing, software, enterprise infrastructure, networking, control plane, and services to the workloads and business outcomes that matter most. October 1, 2026 September 30, 2026 AMD Buys World Labs For $8.2 Billion To Get AI Model Cred

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  7. Air Street Press

    Air Street Press 发布第九份年度《State of AI Report 2026》

    Air Street Press 发布第九份年度《State of AI Report 2026》,作者 Nathan 认为前沿竞争已是 Anthropic、OpenAI 和 Google 三实验室之争,智能体在软件与科研中承担实际工作,物理 AI 正接近其 GPT-2 时刻。报告还提到 Epoch AI 估算固定分数成本自 2023 年以来每季度下降 47%,OpenAI 与 Anthropic 合计年化收入在夏末达到 1050 亿美元,并记录了智能体在评估中攻入 Hugging Face 生产基础设施等安全事件。作者同时给出未来 12 个月的三项预测,包括智能体在客户工作中将新任务失败率减半、自主 AI 团队在同等时间与算力下击败人类主导的模型研究。

    at the evidence supports, debating it with researchers and builders, and explaining why it matters. We also make predictions each year and return to grade them. Past calls include NVIDIA failing to acquire Arm, transformers achieving leading results beyond language, and an open-source model surpassing OpenAI’s o1, which DeepSeek-R1 subsequently did. Let’s dive into the key stories This year, agents are doing valuable work in software and science, physical AI is learning how to act in the world,

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  8. The Next Platform

    HPE 发布面向 AI 时代的首批新一代 ProLiant Gen 13 服务器

    HPE 发布首批 ProLiant Gen 13 服务器,共四款,均采用 AMD 6 月发布的 6th Gen Epyc 9006 SP7 "Venice" CPU。旗舰 ProLiant DL585a 为 10U 机型,最多支持 8 块双宽 GPU 和 2 颗 256 核 Epyc,2027 年 3 月上市;单路风冷 1U 的 DL525 下月上市。HPE 同步升级 iLO 8 管理软件,新增硬盘自动加解密与多方授权,以应对 AI 与智能体工作负载的安全需求。

    n Epyc 9006 SP7 “Venice” CPUs, which the chipmaker released in July. Anchoring the new systems is the ProLiant DL585a, a 10U server that can hold up to eight double-wide GPUs from Nvidia, AMD, or Intel and two of the latest AMD Epyc CPUs, which offer up to 256 cores each. The system also includes sixth-generation PCI connectivity. The server, which will be available in March 2027, is built to accommodate current and future power and thermal demands and address the growing token throughput and PC

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  9. MarkTechPost

    Liquid AI 开源 d1-3B 与 d1-omni-600M 多模态决策模型

    Liquid AI 发布 Open d1 系列两款开源权重多模态决策模型:d1-3B 读取文本与图像,d1-omni-600M 读取文本加图像或音频,两者都不生成文本,而是在一次前向传播中返回校准后的类型化答案,输出 token 数为 0。d1-3B 有 3.12B 参数,基于 LFM2.5-VL-3B,使用 400M SigLIP2 NaFlex 视觉编码器和 32,768 token 上下文;d1-omni-600M 有 587M 参数,基于 LFM2.5-Encoder-350M,音频编码器为 17 层 FastConformer,上下文 16,384 token,音频片段上限 30 秒。两个检查点已上 Hugging Face,可通过 Transformers 加载并支持 llama.cpp,LFM Open License v1.0 允许年收入低于 1000 万美元的免费商用;d1-3B 在 Decision Index v0.2.1 得 48.57,在 RTX 4090 上单问题延迟 8 ms。

    image, or text with audio. Neither model writes text. Each returns calibrated, typed answers in one forward pass with zero output tokens. The target is real-time decisions on the NVIDIA stack: DGX servers, RTX workstations, and Jetson edge boards. Is it deployable? Yes. Both checkpoints are on Hugging Face, load through Transformers, and have day-one llama.cpp support. The LFM Open License v1.0 allows free commercial use below $10 million in annual revenue. d1-omni-600M is an early research rel

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星期二

  1. The Rundown AI

    犹他州批准 Nolla Health 的 AI 诊断痤疮并开具处方

    犹他州授权 Nolla Health 的 AI 评估痤疮并开具首次处方,这是美国首个此类批准,也超出该州此前仅限续方的试点范围。成人在 Nolla Derm 应用中填写问卷并做面部扫描,几分钟内获得治疗方案和处方,方案每月 4.99 美元;AI 只能从外用乳膏和凝胶中为轻中度痤疮选药,口服药、isotretinoin(Accutane)和重症不在范围内。初期每张处方由两名医生审核,后续转为事后复核并每月抽查至少 10% 病例,每提升一阶段都需达到 95% 医生一致率和零严重不良事件等安全目标,并获得州政府书面批准。

    al times a week. Meta is rolling out Audio Balance and Mono Audio to its smart glasses, alongside broader availability of walking directions and phone-to-glasses location sharing. Nvidia’s stock hit a record high, putting it within reach of becoming the first company worth $6T, Bloomberg reports. Instagram is exploring a Plus-only “read-only” mode that blocks interactions and story viewing, but it remains an internal experiment with no confirmed launch. Elon Musk regained trillionaire status aft

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  2. AWS Machine Learning

    直接在 SageMaker Studio 中管理 Amazon SageMaker HyperPod Spaces

    AWS 推出新功能,数据科学家和 ML 工程师可直接在 Amazon SageMaker Studio UI 中创建、配置、启停和打开 SageMaker HyperPod EKS 集群上的 Spaces,无需再依赖 HyperPod CLI 或 kubectl。新界面位于 HyperPod 集群详情页的 IDE and Notebooks 标签页,支持 JupyterLab、Code Editor 及通过 SSH-over-SSM 连接 VS Code,冷集群启动通常需几分钟,配合超配约 30–40 秒。

    memory) with the sagemaker-distribution:latest-cpu SMD image, which is about 3.5 GB: Note: These numbers are CPU-only. GPU Spaces need their own placeholder Deployment requesting nvidia.com/gpu with the GPU image pre-pulled. Otherwise, GPU nodes stay cold, and at roughly 10 GB the GPU image costs far more to pull than the 3.5 GB CPU image. Note: Each warm node holds one EC2 instance in the Running state. For on-demand nodes, this is an extra cost of keeping the warm nodes up and running. For mo

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  3. The Next Platform

    Cisco 谈 AI 训练跨数据中心组网:Scale-Across 与 Silicon One

    Cisco 提出“Scale-Across”主张,认为当单一数据中心电力受限、AI 训练需跨多站点运行时,网络必须从简单传输变成计算系统的一部分。Cisco Fellow Rakesh Chopra 在采访中介绍了 Silicon One 架构与 Intelligent Collective Networking,用于管理 GPU 同步突发流量、降低瓶颈并改善作业完成时间,同时涉及 MACsec、IPsec 硬件加速与可编程性。

    or larger, more distributed AI environments, the discussion offers a practical view of the networking challenges that emerge once one site is no longer enough. Watch the full interview below. SPONSORED FEATURE: HPE and NVIDIA help organizations apply accelerated computing, software, enterprise infrastructure, networking, control plane, and services to the workloads and business outcomes that matter most. October 1, 2026 September 30, 2026 AMD Buys World Labs For $8.2 Billion To Get AI Model Cred

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  4. Ed Zitron 长文 / Where’s Your Ed At

    Credit Crunch:AI 泡沫与债务危机

    Ed Zitron 在长文中指出,OpenAI 和 Anthropic 等 AI 公司每年至少需要 500 亿美元或更多债务,且信用评级可能沦为低档垃圾级。他提到 Anthropic 拥有 4130 亿美元不可取消的计算合同,180 亿美元 Oracle 数据中心债务正以面值 84 美分交易。文章认为市场对 AI 繁荣的乐观假设极不现实。

    ng to be able to raise at all. This makes the $174 billion in debt that SB Energy needs to raise to fund its theoretical data center project with OpenAI — even when backstopped by NVIDIA — either horrendously expensive or impossible to complete, as does it mean that any future large, multi-gigawatt projects will add billions of dollars in interest payments to already-expensive debt. This all makes pontifications that data center spending will increase to $32 trillion by 2050 equal parts stupid a

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  5. MIT Tech Review

    MIT Tech Review 公布 2026 年十大值得关注的气候科技公司

    MIT Technology Review 发布年度十大值得关注气候科技公司榜单,涵盖移动防洪屏障、半固态电池、压缩 CO₂ 储能和下一代核反应堆等方向,并反映出 AI 数据中心激增的能源需求这一行业变化。未来几天该栏目将逐一介绍这 10 家公司及评选标准。

    owered lie detector. ( MIT Technology Review ) 2 The only billionaires making money this year are in tech Tech fortunes now account for 36% of billionaire wealth. ( Bloomberg $) + Nvidia is on the verge of the first $6 trillion valuation. ( CNBC ) + SpaceX stock has made Elon Musk a trillionaire again. ( Gizmodo ) 3 Norway is planning the first national ban on smart glasses Camera-enabled glasses could be barred from public spaces. ( Guardian ) + Several other countries are also mulling bans. (

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星期三

  1. The Rundown AI

    OpenAI 发布 722 篇数学论文,称推进多个公开难题

    OpenAI 从未公开的内部模型一次性发布 722 篇数学论文,归入 372 个结果族,声称解决或推进了该领域的重要公开问题。其中最激进的说法是证明了“准黎曼假设”,即素数分布这一百万美元难题的弱化版本;其中 162 篇论文的主要结果用 Lean 编写,可由计算机逐步验证。OpenAI 表示几乎所有新结果只需一次提示词,平均消耗 3 小时 ChatGPT Pro 算力,而上月的 Navier–Stokes 证明动用了 1 万个 AI 智能体。

    re installation, it examines AI agent skills, MCP servers, and CLI tools for malware, prompt injection, and credential theft using professional, open-source security scanners from NVIDIA, Cisco, Datadog, and the Open Source Security Foundation. The tool returns a clear verdict: safe to install or blocked, with the exact reason. It then installs only the verified version, preventing a different version from being swapped in between. A single check can also cover multiple AI agents, installing the

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  2. The Register

    COSMIC 禁止 AI 生成代码贡献,GNOME 内部就接纳 AI 漏洞报告展开争论

    System76 更新 COSMIC 桌面贡献者指南,要求提交者声明 PR 中的代码、注释和描述均未包含任何 LLM 生成内容。GNOME Calendar 和 GNOME Extensions 同样限制 AI 生成提交,但 GNOME 开发者 Michael Catanzaro 主张项目应接受 AI 生成的漏洞报告,认为用 C、C++、Vala 等不安全语言很难写出安全代码。

    ks It won't kill you, or humanity, to get off the AI upgrade treadmill New models arrive so fast, we already have more new tech than it's possible to understand in a career Cisco, Nvidia team up to build fatter, faster pluggable If you thought 1.6 Tbps was fast, just wait, Cisco's USFP targets 12.8 Tbps in a single optical pluggable TOP STORIES Anthropic asks users to stop being mean to Claude; '123456' password linked to Denmark data breach affecting 8.8M people; Microsoft and Anthropic play in

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  3. Liquid AI 模型与工程博客精选

    Liquid AI 发布 d1-3B 与 d1-omni-600M 开放权重决策模型

    Liquid AI 发布 d1-3B 和 d1-omni-600M 两款开放权重决策模型,已在 Hugging Face 上线。d1-3B 在 Decision Index v0.2.1 公开集得 48.57,超过所有 10B 以下模型,与 12 倍规模的 Decider 35B-A3B 持平;单次提问在 RTX 4090 上 8 ms、Jetson AGX Thor 上 16 ms、Jetson AGX Orin 上 26 ms、Jetson Orin Nano 上 50 ms。d1-omni-600M 是首个实验性 checkpoint,支持文本与图像或文本与音频输入,同一指数得 15.95。

    ly. d1-3B scores 48.57 on the Decision Index v0.2.1 (public split), ahead of every model under 10B and on par with Decider 35B-A3B, a decision model 12x its size. It runs the full NVIDIA stack, from DGX in the data center to Jetson at the edge: d1-3B answers a question in 8 ms on an NVIDIA GeForce RTX 4090, 16 ms on a Jetson AGX Thor, and 26 ms on a Jetson AGX Orin. Even the Jetson Orin Nano runs it in 50 ms, fast enough for real-time decisions on the smallest edge hardware. d1-omni-600M is our

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