NVIDIA 与 EBU、Adobe 推进媒体智能体安全:主权云、开放模型与 GPU 加速视频搜索
NVIDIA 与欧洲广播联盟(EBU)扩大主权框架合作,引入主权云厂商、开放模型开发者和系统集成商,明确广播机构部署智能体时数据、基础设施、模型与安全的控制方式,NVIDIA Nemotron 开放模型可供定制。
NVIDIA 与欧洲广播联盟(EBU)扩大主权框架合作,引入主权云厂商、开放模型开发者和系统集成商,明确广播机构部署智能体时数据、基础设施、模型与安全的控制方式,NVIDIA Nemotron 开放模型可供定制。
后摩智能 10 月 14 日在北京举办生态合作伙伴大会,圆桌环节五位来自操作系统、应用、数据工程、整机集成和芯片领域的从业者讨论端侧 AI 如何成为一门生意。麒麟软件姚翎称涉密场景下本地安全没有商量余地,罗格数据刘学鹏认为企业要把 AI 数字员工招进内部而非放在云端。后摩智能陈仲铭表示正通过 M 系列做大算力和先进封装做大带宽,突破算力、带宽、功耗的「不可能三角」。
Simon Willison 发布 llm-tools-datasette 0.1.1,这是 llm-tools 系列中面向 Datasette 的工具插件更新。原文未披露该版本的具体功能变更、参数或可用性细节。
Simon Willison 更新了 llm-echo 调试插件至 0.5 版本,其模拟 token 用量统计现在会把工具调用、系统提示词和推理 token 计入。该插件提供一个不涉及 LLM 的 "model",只回显输入的提示词,示例中一次调用显示 2 个输入 token、24 个输出 token。
作者在 aiDotEngineer NYC 现场听到工程师对 agent harness 的强烈分歧:有人因模型不再需要而删减 harness 组件,有人则在构建能让智能体连续工作数天的系统。
NVIDIA RTX Spark 笔记本已上市,搭载 Blackwell RTX GPU 与 Grace CPU,最高 128GB 统一内存、最高 1 petaflop AI 算力,起售价 2399 美元。
NVIDIA 发布面向创作者、游戏玩家和 AI 智能体的 Windows PC 产品 RTX Spark,并在全球多地举办发布活动。
推荐理由:原文给出 RTX Spark 的本地 AI 实测完成时间对比,可据此判断笔记本端侧推理的可用性。
微软研究院发布零知识虚拟机 Magnetar,可直接证明用 Rust、Go 或 C 编写的程序执行过程,并输出可在约 12 毫秒内验证的简短证明。在 15 个基准程序上,它比同类最快的 zkVM 平均快 10 到 39 倍,在笔记本上每秒可证明 7.2 至 8.7 百万条 RISC-V 指令。
推荐理由:微软研究院梳理十余年零知识证明研究脉络,说明 Magnetar 如何在通用性、速度与密码学假设之间同时取得进展。
NVIDIA DLSS 4.5 控制选项已在 GeForce NOW 上线,让会员在云端调整支持游戏的画质与性能,无需最新硬件。DLSS Super Resolution、Dynamic Multi Frame Generation 和 Ray Reconstruction 均可在设置中调节,RTX 5080 云主机上的 Ultimate 会员最高可用 4X 动态多帧生成。
Modal 年化经常性收入突破 10 亿美元,并以 157.5 亿美元估值完成 7.5 亿美元 D 轮融资,由 Accel 领投,使用量同比增长超过 15 倍。其 2023 年推出的 Sandboxes 产品单独年化收入已达 3 亿美元,累计启动近 30 亿个沙箱,可扩展至百万级并发。
NVIDIA 在都柏林 AI in Science Summit 上加入欧盟委员会发起的 AI in Science Enablers Initiative,为欧洲科研社区提供加速工具、算力与培训支持。
685 output tokens/s per user on @Alibaba_Qwen Qwen3.8-Flash-Next. Running TokenSpeed on 4× NVIDIA GB300 with NVFP4. A look at the kernel and serving optimizations behind the results: 👉 https://lightseek.org/blog/tokenspeed-qwen3-8-flash-next.html ⭐ https://github.com/lightseekorg/tokenspeed
GitHub 用微调的 ModernBERT 分类器替换原有 LLM 流水线来识别通用密钥,用户接受率提升 11.5%,推送后扫描中位执行时间缩短 86%,服务成本降低超 98%。该方案先用正则高召回生成候选,再由分类器结合文件路径、变量名和上下文判断是否为真实凭据,并已把通用密钥检测扩展到推送保护阶段。
vLLM now supports NVIDIA Vera Rubin. The early results show more than 7.8x the throughput of GB200 on MiniMax M3 on AgentX. @inferact, @NVIDIAAI, @RedHat_AI, and the vLLM community have been bringing vLLM up on Rubin since it was announced. Here is where things stand. 🧵 1/5
Today, we announced new @Windows platform capabilities and @surface devices built to empower people and organizations for the era of hybrid intelligence. Here are some of the highlights: - It all starts with trust. Microsoft Execution Containers (MXC) is now generally available on Windows 11, keeping agents contained within boundaries the operating system enforces. - HydraFusion brings hybrid intelligence to life, allowing models to run locally while seamlessly accessing the cloud when more scale or capability is needed. We're working with @github to extend HydraFusion to Windows. - This fall, Search on the taskbar adds thousands of quick actions, making it easier to adjust settings and get things done as fast as you can type. - @MSFTCopilot is getting more powerful on Windows. With hybrid intelligence, it can tap into your PC's local capabilities and turn your requests into action, while keeping you in control. - Local agents are coming to Windows too. Muse is on its way as a native Windows app with MXC integration, and Hermes, OpenClaw, and Perplexity are already building local experiences on Windows. - Surface Laptop Ultra, built with NVIDIA RTX Spark, is the most powerful Surface we've ever built. It's available for pre-order today, along with the Surface RTX Spark Dev Box and new RTX Spark PCs from our partners. Call of Duty is coming to RTX Spark in 2027. Read more on the Windows Blog: https://blogs.windows.com/windowsexperience/2026/10/07/building-windows-for-hybrid-intelligence/
微软研究院开源 Agent Lightning v1.0,这是一个约 3500 行代码的轻量 Agentic RL 框架,提出 Harnessed Agentic RL 范式,让部署时使用的 agent harness 直接参与强化学习,无需在训练框架内重写 agent。
推荐理由:微软研究院开源约 3500 行的 Agent RL 框架,用真实 harness 参与训练,并给出 6000 样本提升 14.6 个点的完整流程。
DeepSeek Harness for desktop is now available on macOS and Windows. https://x.com/i/article/2104777189275439104
微软研究院实习生构建的机器学习流水线可为美国本土66,935座变电站生成30-60分钟前的空间天气风险预报,评估期内检出近80%的重大空间天气事件。系统结合AE与Dst指数预报、纬度、地质电导率及电网数据,Dst预测在2020-2026年活动高峰时段有62.2%的小时优于Burton方程。
来自 @inteldevs 的 Day-0 OpenVINO 支持!🥳 Qwen-Image-2.1 已可在 Intel 硬件上优化运行。一个开放权重 checkpoint,同时支持生成与编辑。👇
We're excited to offer Day0 OpenVINO support for Qwen-Image-2.1 Read more about what you can accomplish here: https://ms.spr.ly/6019a5nm5
感谢 @sgl_project 的 day-0 支持!🙌 SGLang-Diffusion 现已支持 Qwen-Image-2.1:文生图、多图编辑和透明 RGBA 输出。快来试试!🎨
Day-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24GB with CPU offload - 1024×1024 generation in 18.7s and image editing in 21.7s with 22.7 GiB peak GPU memory during requests. - On an RTX PRO 6000 96GB: 8.0s generation and 9.6s editing. 🎨 Text-to-image, multi-image editing, and transparent RGBA output—all with one checkpoint. ⚡ Native inference with TP/SP, LoRA, and OpenAI-compatible APIs. 40 denoising steps, one image per request, warmed HTTP latency including PNG output. No quantization. Cookbook and GPU-specific commands below 👇
Qwen-Image-2.1 from @Alibaba_Qwen has day-0 support in vLLM-Omni. 🎉 Generate, edit, and create transparent images with one model: a 7.1B DiT paired with Qwen3-VL-8B. Setup and supported combinations 👇 https://recipes.vllm.ai/Qwen/Qwen-Image-2.1
快速遇上开源。🚀 Qwen3.8-27B 现已在 @cerebras 上运行,推理速度飞快。立即体验!
Qwen3.8-27B is now live at Cerebras speed. The dense, open-weight model from @Alibaba_Qwen scores 34 on the Artificial Analysis Intelligence Index—making it comparable to models such as GPT-5.6 Luna, DeepseekV4 Pro, and Claude Sonnet 4.6.
Berkeley Sky Lab 团队为 K-Search 增加 MLX 后端和结构化 CUDA-to-MLX 翻译层,让进化式内核搜索以现有 CUDA 内核为知识库生成 Apple Silicon 内核。
UC Berkeley 团队提出,推理成本已从 GPT-4 级约 $30/百万 token 降至不足 $1,部分厂商低于 $0.10,基准测试中推理价格每年下降 9x 至 900x、中位数约 50x。作者据此提出三类数据系统挑战:为智能体设计的数据系统、支撑智能体群体运行的数据系统、以及由智能体合成的数据系统。
伯克利 AI 研究团队综述并行推理进展,重点分析自适应并行推理——让模型自行决定何时分解并并行化子任务、开多少并发线程以及如何协调。现有方法如 self-consistency、Best-of-N、Tree of Thoughts、MCTS、ParaThinker、GroupThink 和 Hogwild! Inference 的并行结构多由外部设定,而非模型自主选择。
DeepSeek-V4-Pro 折扣已延长至 2026 年 5 月 31 日 15:59 UTC!
🔥DeepSeek-V4-Pro API is 75% OFF until May 5th, 2026, 15:59 (UTC Time)! Don't miss out on this massive discount. 🛠️Integration Updates: 🔹Claude Code: Set model to deepseek-v4-pro[1m] to unlock 1M context! 🔹OpenCode: Update to v1.14.24+ 🔹OpenClaw: Update to v2026.4.24+ Check the latest official API docs for full details: https://api-docs.deepseek.com/quick_start/pricing
Andrej Karpathy 回顾约一年前搭建 menugen 的经历,认为最难的不是代码本身,而是服务、支付、认证、数据库、安全、域名等一整套 DevOps 组装。
When @karpathy built MenuGen (https://karpathy.bearblog.dev/vibe-coding-menugen/), he said: "Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services, docs, API keys, configurations, dev/prod deployments, team and security features, rate limits, pricing tiers." We've all run into this issue when building with agents: you have to scurry off to establish accounts, clicking things in the browser as though it's the antediluvian days of 2023, in order to unblock its superintelligent progress. So we decided to build Stripe Projects to help agents instantly provision services from the CLI. For example, simply run: $ stripe projects add posthog/analytics And it'll create a PostHog account, get an API key, and (as needed) set up billing. Projects is launching today as a developer preview. You can register for access (we'll make it available to everyone soon) at http://projects.dev. We're also rolling out support for many new providers over the coming weeks. (Get in touch if you'd like to make your service available.) https://projects.dev