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9月29日周二
  1. Ollama:Blog69

    Ollama 支持基于 Jev API 的决策模型,新增 nimble 等三款模型

    Ollama 0.35 通过新 /v1/systemone 端点支持基于 TypeSafe Jev API 的决策模型,可在本地一次请求回答多个命名问题,适合工单分诊、模型路由和内容审核等快速决策任务。

    推荐理由:官方宣布本地运行决策模型,给出延迟数据和 API 用法,可帮助读者评估本地快速决策场景的可行性。

  2. Lingxi Li51

    Team Bots 发布,定位为随团队协作不断学习的共享 AI 队友。用户可为 Team Bot 配置其角色所需的技能、插件和凭据,并在 Slack 或 Grok Bot 中使用;作者 Lingxi Li 表示自己的 @bot 已成为全团队可用的队友。

    引用Grok Bot@bot

    Introducing Team Bots, shared AI teammates that learn as your team works with them. Give your Team Bot the skills, plugins, and credentials it needs for its role, then work with it in Slack or Grok Bot.

  3. xAI:News66

    xAI 发布 Team Bots:可与团队共享并持续学习的 Grok Bot

    xAI 发布 Team Bots,即可与团队共享的 Grok Bot,通过 Context、Plugins、Credentials 和 Memories 四要素围绕共享角色或工作流构建,每人对话保持私密,并可在 Slack 中协作。

    推荐理由:官方说明了 Team Bots 的四项组成机制和四类团队用法,读者可以据此判断共享型 Grok Bot 如何接入现有工作流。

  4. Hacker News:AI 热帖49

    MicroLLM Lab:在浏览器中试用 7 款微型 LLM

    MicroLLM Lab 上线,可在浏览器内直接试用 7 款微型 LLM,并支持用 JavaScript 编写基准测试。测试以正则或精确 token 做客观校验,不评判写作质量,135M 模型允许失败,这本身就是测量结果。运行会记录 tokens/s 持续解码速度与客观测试通过率,数据只留在本机,图表按每个模型的最新测试套件展示。

  5. lauren55

    Lauren Tan 宣布 Grok @bot 支持多人协作,可创建一个 Team Bot 并为其配置插件、技能和凭据,然后一键添加到 Slack 中使用。她表示自己很喜欢与自己的 Team Bot 聊天并调度 cloud agents,并称后续会有更多更新。

    引用Grok Bot@bot

    Introducing Team Bots, shared AI teammates that learn as your team works with them. Give your Team Bot the skills, plugins, and credentials it needs for its role, then work with it in Slack or Grok Bot.

  6. Sierra:Blog45

    Sierra 将 Ghostwriter 从工具升级为 Slack 和 Teams 里的 AI 队友

    Sierra 把 Ghostwriter 从需要提示的工具改造成常驻 Slack 和 Teams 的主动型 AI 队友,用户可通过 @ 提及获取客服解决率趋势、销售漏斗转化图表或发起实验。新版本会结合团队对话与海量客户交互主动提出洞察和业务建议,并协助把想法转成实验、监测结果直至统计显著。该版本将于下周开始更广泛地推送。

  7. Rohan Paul63

    Base44 推出 Base Code 早期预览,连接 GitHub 仓库后由智能体在云端配置数据库、基础设施和示例数据,直至运行出实时预览。它支持通过聊天修改代码库并提交 pull request,团队任意成员可在浏览器中协作,未来将支持 WhatsApp / iMessage;产品免费开放 30 天,并计划推出自动化与软件工厂能力。

    引用Maor Shlomo@MaorShlomo

    Today we’re introducing Base Code. It’s an early preview of how we think software will be built in the future. It’s a product that encapsulates everything we’ve learnt from: - How our users are building software. - How we’re building internally, scaling to hundreds of millions of dollars in revenue while keeping our engineering team very small and focused. Here are some of the principles behind it, which align with how we at @Base44 think about the future of software engineering: Cloud: - Software will move past local desktop environments (where current tools are widely used) and move to the cloud. - Moving everything to the cloud is not easy. Setting up dev environments with databases, infra components, services, mock data, etc. is easier said than done. - Base Code first scans your code repo and sets up everything - every infra component (databases, Redis, etc.) - in the cloud. It runs nonstop until your preview environment is ready. - From an enterprise standpoint, it’s also the logical thing to do: a centralized, governed dev environment instead of handing out keys and secrets to all team members. - Once Base Code does that, EVERY team member can work in this environment. No more syncing local environments. Internally, this (cloud) is one of the main things that enabled us to move so fast. Collaboration: - Once everything is in the cloud, everybody can write software from anywhere (any browser, your phone, WhatsApp / iMessage coming soon). - You can easily see what everyone is working on, where they’re at, and how they’re prompting - and jump to their environment in one click. - We’ve built many great collaboration features from the ground up. Loops, automations, software factories: - A full, working cloud environment allows for many advanced capabilities we will unveil soon-think agents running in the browser and testing on every device and in any browser. - It also allows the use of automations to build software factories-e.g., agents reading support tickets, identifying bugs to fix or features to develop, implementing the changes, verifying them in the cloud, and potentially pushing them. And lastly, there’s a real advantage in being model agnostic. -------------- As always, we’re releasing it very early. It’s far from perfect-but we’re looking for early feedback so we can build it together with our great community and make this vision a reality. *We’re giving it away for free for 30 days*. Give Base Code a try. Connect any GitHub repo, get your live preview, and share it with your team. I’d love to hear what works and what doesn’t: http://app.base44.com/base-code

9月28日周一
  1. 公众号:腾讯元宝50

    腾讯元宝桌宠尝鲜版上线:Windows 与 macOS 升级 v2.87 即可开启

    腾讯元宝推出桌宠抢鲜版,Windows 与 macOS 用户将元宝 PC 端升级至 v2.87 及以上,点击左下角头像进入「我的桌宠」即可开启。该桌宠可实时盯长任务进度、以专属动画提醒完成,支持拖拽文件图片直接导入应用、快速抓取长文案网页重点,还会提醒久坐起身和喝水,拖到屏幕边缘自动吸边。目前正在灰度放量中。

  2. Tianyi Cui51

    Tianyi Cui 提名三个使用广泛、更新及时的 DSH 插件导航站:https://dshfind.com/、https://dshmarket.com/ 和 https://awesome-dsh-plugin.com/,其中 dshmarket 还可直接作为 DSH 插件安装到设置页中。

    引用Tianyi Cui@tianyi

    从 DeepSeek 官方 API 处统计的数据来看,约有 60% 的 DeepSeek Harness 用户使用了至少一个第三方插件。第三方插件是 DeepSeek Harness 用户体验中最具特色且不可缺少的一部分。DeepSeek Harness 团队将持续支持第三方插件生态的繁荣发展,并推动插件 API 趋于稳定,在将来减少和尽量避免破坏性更新。 接下来的几天我个人将每天推荐一个优质的 DSH 第三方插件,欢迎 DSH 插件作者在本 thread 下自荐。我会结合插件质量及后台实际统计到的插件使用量择优推荐。 DeepSeek Harness 团队祝大家中秋快乐阖家幸福! (注:在用户使用官方 API 及模型时,DSH 会向官方 API 上报实际使用的插件包名和版本。此类上报不额外消耗 tokens。)

  3. IT之家·人工智能41

    腾讯元宝电脑端上线“桌宠”尝鲜版:文件、图片拖过去就能导入到应用

    腾讯元宝桌宠尝鲜版正式上线并处于灰度放量中,Windows 与 macOS 用户将元宝 PC 端升级至 v2.87 及以上,点击左下角头像进入「我的桌宠」即可开启。桌宠可实时传达长任务进度并配专属动画提醒,支持文件、图片拖拽导入应用,还提供复制翻译、网页辅助阅读以及起身活动、喝水提醒。