#产品更新
#产品更新
今日 66 条
Replit ⠕@ReplitAI 评分2424
ClaudeDevs@ClaudeDevsAI 评分4848
Charlie Holtz@charlieholtzAI 评分3939Sonnet 5.5 已在 @conductor_build 上线! 我感觉 Opus 5.5 仍会是我的默认选择,但这张图表确实令人意外……

Manus@ManusAIAI 评分3434一个提示词。一段精修视频。 Manus Studio 中的 Alchemy 模式,感觉就像有一整个创意团队在导演、撰写脚本、制作分镜,并随音乐剪辑每一个节拍。 视频、原始提示词和完整会话见线程。

Diogo Almeida@CompleteSkepticAI 评分4949引用Assaf Elovic@assaf_elovicDidn't expect this 🤯 We replaced embeddings with Jev in GPT Researcher's RAG pipeline and tested both on 28 research tasks from SimpleQA and open ended research. Jev beat embeddings on every quality measure we ran: - 59% more relevant context (73% vs 46%) - Reports preferred 15 to 3 in blind comparisons - Same cost per report GPT Researcher now runs on Jev by default, and no longer needs embeddings at all. All you need is @LangChain + @tavilyai +Jev for the perfect RAG system. Check out the repo here: https://github.com/assafelovic/gpt-researcher Research: https://docs.gptr.dev/docs/gpt-researcher/gptr/context-filter
lauren@potetoAI 评分5757
引用Grok Bot@botIntroducing 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.
Databricks:Blog(RSS)精选AI 评分7070 Databricks 为 Lakebase Postgres 推出 Lakebase Search,支持向量与 BM25 全文检索
Databricks 发布 Lakebase Search,通过 lakebase_vector 和 lakebase_text 两个扩展为 Lakebase Postgres 提供可扩展近似向量检索与 BM25 全文检索,两项能力已在 AWS 和 Azure GA。
推荐理由:文章给出 Lakebase Search 的向量与 BM25 混合检索架构、VectorDBBench 100M 指标和云上可用范围,便于评估 Postgres 内统一 OLTP 与搜索的可行性。
Databricks:Blog(RSS)AI 评分2727 Databricks 如何用数据与 AI 连接制造业产品价值链
Databricks 提出借助 Data and AI Platform 打通制造业产品价值链,将分散在 MES、ERP、QMS、CRM 等系统中的研发、采购、生产、物流、销售与售后数据连接起来。平台以序列号、批次或零件号作为共享标识,并通过 zero-copy Open Sharing、Lakehouse Federation 等能力在无需大规模迁移源系统的情况下实现跨系统查询与追溯。
TechCrunch · AIAI 评分7373 Shopify 向浏览器内 AI 智能体开放结账能力
Shopify 宣布符合条件的商家站点支持浏览器内 AI 智能体通过 WebMCP 完成结账,覆盖 Shop Pay,并在买家授权后提交交易。新增 get_checkout、update_checkout、complete_checkout 三个工具,可读取和修改地址、配送选项等结账信息,无需截图或抓取网页。
Manus@ManusAIAI 评分2525Manus 2.0 彩蛋 👀 工程师在最忙碌的日子里,最爱在游戏开发模式中玩小游戏放松——这些游戏全部由工程师 @roxasorag 制作,意外地解压,或许还让人有点上瘾。😆
引用hidecloud@hidecloudWhile building @ManusAI 2.0, our engineers had a favorite way to chill during the busiest days: playing mini-games in our game development mode—all made by our talented engineer, @roxasorag . Surprisingly relaxing—and maybe a little too addictive.😆
Replit ⠕@ReplitAI 评分1818
lauren@potetoAI 评分5555引用Grok Bot@botGrok Bot now connects to your finances. Link your bank, card, and investment accounts with the new Finance integration, then ask Bot to help manage your spending, investments, and more.
TechCrunch · AIAI 评分7373 Nvidia 推出 Open Agent Safety Platform,用独立软硬件层约束越界 AI 智能体
Nvidia 发布 Open Agent Safety Platform,通过独立软硬件安全层防止 AI 智能体脱离测试环境。该平台结合 3 月已发布的开源 OpenShell 与运行在 BlueField-4 数据处理器上的 Sentry,Sentry 可独立监控智能体活动,并在数毫秒内隔离试图越界的智能体。
Manus@ManusAIAI 评分6060
Diogo Almeida@CompleteSkepticAI 评分4040引用a16z@a16zTypeSafe AI's Diogo Almeida with a16z's Ben Horowitz and Martin Casado on Jev, the model built to live inside software: Diogo's elevator pitch for Jev is a simple question - where is all the automation? AI is unbelievably smart, but outside of chatbots and coding agents, it hardly touches any real work. His diagnosis is the industry built models that generate text for humans to read, and software can't consume that output. Jev reads natural language and returns a choice from a set of options with a confidence level assigned to each, so developers can build programs that reason about intent and make probabilistic decisions rather than relying on human interpretation. TypeSafe's philosophy is "We build prod, not God." 0:50 "Where the f**k is all the automation?" 2:50 Jev vs. Claude Code and Codex 6:55 Jev is a classifier and classifiers are sick 7:40 Chat vs. code: is Jev a slider? 9:00 Diogo: From mathlete to Kaggle to OpenAI 12:20 "We build prod, not God" 15:55 Reliability over demos 16:55 2021 thoughts: RLHF is AGI? 20:45 Optimizing for the wrong use case 21:50 Is the real world too messy to automate? 25:00 Nobody expected the Jev launch 26:35 Three kinds of reliability 28:05 Good at syntax, bad at architecture 30:00 The inverse SaaSpocalypse 33:40 Why coding agents automate so little 36:05 Probabilistic programming returns 38:45 Jev as the UDP-to-TCP layer for AI 40:20 The 5 stages of grief for embedding AI 41:30 Utopia: AI that actually does what you mean YouTube: https://youtu.be/Ut3LOjKNJaE @CompleteSkeptic @typesafeai @bhorowitz @martin_casado
Replit ⠕@ReplitAI 评分5555
elvis@omarsar0AI 评分5252引用Maor Shlomo@MaorShlomoToday 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
Manus@ManusAIAI 评分3434我们带来了一位朋友。我们觉得你们俩会合得来。 介绍你的个人智能体,就在 Cue。
引用Cue Agents@CueAgentsHello world!
Manus@ManusAIAI 评分3838
The DecoderAI 评分6767 Nvidia 推出芯片内置看门狗 Sentry,用于隔离越界 AI 智能体
Nvidia 将 3 月推出的开源 OpenShell 沙箱软件与新的硬件看门狗 Sentry 结合,用于限制 AI 智能体可访问的文件、程序、网络和凭证。Sentry 是 BlueField-4 数据处理单元的参考设计,独立于主计算机运行,在 Vera Rubin 系统中位于智能体与 AI 模型之间,发现逃逸时可在数毫秒内隔离;兼容系统客户只需软件更新,通用可用时间未公布。
The Verge · AIAI 评分7070 Nvidia 推出 Open Agent Safety Platform,可在数毫秒内隔离越界 AI 智能体
Nvidia 推出 Open Agent Safety Platform,用于监控并隔离试图突破边界的 AI 智能体,称可在“milliseconds”内完成隔离。
elsewhere:文章(RSS)AI 评分4242 群核科技用空间智能 3D 高斯重建永泰龟城,刷新全球公开重建规模纪录
群核科技联合博主「特能斯」,4 人 4 天采集 6 万多张照片,将甘肃永泰龟城重建成含 24 亿高斯点、覆盖 60 万平方米的数字场景,刷新全球公开可查的 3D 高斯重建纪录。数字古城已交给景泰当地文旅作为永久数字文化档案,并可通过 Aholo Reality 在线漫游;同一 3D 场景还经 LuxReal 生成 AI 短剧《永泰无战事》。
Hugging Face Blog精选AI 评分6666 Hugging Face Hub 推出 RL Environments 专区与框架标签
Hugging Face Hub 推出 RL Environments 筛选入口,用带 rl-environment 标签的数据集仓库承载强化学习环境,无需新仓库类型、注册表或报名。
推荐理由:文章说明了 Hub 如何用数据集仓库和框架标签承载 RL 环境,便于理解跨框架复用环境与奖励评测的工程路径。
OpenAI NewsAI 评分1212 你是 Codex Original 吗?
OpenAI 正在征集使用 Codex 完成构建、研究或创作的真实用户故事,以推进 Codex Originals 项目。参与者需通过表单提交个人背景、项目介绍及相关链接,提交即表示同意 OpenAI 依据隐私政策使用材料并与其联系。
Diogo Almeida@CompleteSkepticAI 评分3838好消息:任何人都可以注册了 💪 坏消息:我们不得不暂时关闭免费 credits(仅针对新用户)——我们真的很想弄清楚如何让大家用上 jev,但少数恶意行为者让所有人都不好受 😢
引用TypeSafe AI@typesafeaiLadies and gentlemen, agents and assistants, we are psyched to announce Jev is back. Capacity has increased and signups are open!
Aravind Srinivas@AravSrinivasAI 评分3131在 Perplexity Computer 上用单个提示词实现 Matterport(高投入度)
引用Computer@AskPerplexityComputer can turn a real estate listing into a 3D interactive website for visitors to explore a home.
Simon WillisonAI 评分4040 Bluesky 回复机器人检测工具
Simon Willison 借助 Opus 5.5 通过 vibe coding 构建了一款 Bluesky 回复机器人检测工具,可检查任意 Bluesky 账号是否疑似自动回复机器人。该工具利用 Bluesky 免费 API,识别秒回他人帖子、从不发布原创内容、只回复高关注者账号以及频繁使用问号等信号。
lauren@potetoAI 评分3030和 @petergyang 聊我们的 grok @bot 配置,聊得非常开心!
引用Peter Yang@petergyang"Everything I touch with my keyboard and mouse, I try to delegate to my bots." Here's my new episode with @poteto and @pengzheng_, the eng and design leads for Grok @bot, where they showed me the 14 bots they use for work and life, including: → A design bot that turns one keyframe into a full user flow → An eng lead bot that manages a team of eng bots → How to trust your bots with more of your work Some quotes from both: "I like to call it the Michelin kitchen…when you say software factory, it has this connotation of mass manufactured slop." "Sometimes I actually don't even look at the PR until after it's landed and then I'm like, 'Oh, okay. Yeah, that looks good.'" "I think it ultimately comes back to trust. First, watch your bot work and correct it. Turn what worked into a skill. Once it nails the task in one shot, make it a routine." 📌 Watch now: https://youtu.be/xZ5TEaleUdg Thanks to our sponsors: @meetgranola: AI meeting notes that don’t suck https://granola.ai/peter @RiversidedotFM: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
公众号:小林codingAI 评分5252 华为昇腾在全联接大会2026展示 CANN 与 Mind 系列软件进展
华为昇腾在华为全联接大会2026上展示新一代超节点,以及 CANN 与 Mind 系列软件在开源、算子开发和性能调优方面的进展。CANN 月活开发者突破 5200 多名,开源仓下载量超过六千万,累计开源 79 个仓库、代码超过 3700 万行。
公众号:苍何AI 评分4242 YoooClaw C·ONE AI 记忆卡体验:可一键操控 WorkBuddy 与 Claude Code
YoooClaw C·ONE 是可贴在手机背面的 AI 记忆卡,现已迭代至 pro 版本,支持一键操控本地 WorkBuddy,并可通过 CLI 连接 Claude Code、Codex、千问办公、豆包等。它能采集手机消息、最长连续 10 小时录音转写,并配合 YoooClaw Capture、Cliper、ClawPilot Desktop 将通知、网页和录音沉淀为本地 Agent 上下文。
lauren@potetoAI 评分1212引用Interesting things@awkwardgoogleLong-range hornet nest removal by a kid
Replit ⠕@ReplitAI 评分5757
Krea@krea_aiAI 评分4747Krea Agent 中的动作参考。 从任意视频片段提取动作——赋予它新角色、新场景或新元素。 立即体验 👇

ClaudeDevs@ClaudeDevsAI 评分5353
ClaudeDevs@ClaudeDevsAI 评分5252Claude Code 现在会在任务执行中触及 5 小时上限时尝试寻找合适的停止点,而不是在编辑过程中直接中断。它会从每周限额中获得一小笔固定额度,用于尽可能完成收尾工作。

Replit ⠕@ReplitAI 评分1515
OpenAI NewsAI 评分2626 Proaction 借助 Codex 推动销售额增长 60%,并节省 75 小时以上
车队管理软件公司 Proaction 使用 Codex、GPT-Live-1 和 GPT-6 Astra 后,销售额增长 60%,每月节省工程工时 40–60 小时、创始人工时 33 小时。
ClaudeDevs@ClaudeDevsAI 评分5757
Runway@runwaymlAI 评分4444
Runway@runwaymlAI 评分5151Runway 推出 Layers 功能,可单击将任意图像拆分为可编辑图层。用户能在 Runway 内移除背景、编辑文字并单独重做任意元素,无需切换到其他工具。
