跳到正文

#编码

今日 31 条
9月29日周二
  1. Yuchen Jin41

    我们 @databricks 目前在 NVIDIA 的 SOL-ExecBench kernel 排行榜上排名第一,覆盖全部 4 个赛道。 我们把 GPT-6 Astra 和 Opus 5 放进一个自我爬坡(self-hillclimbing)循环中,这些智能体击败了顶尖的 GPU kernel 工程师。 总 token 花费:约 $70K,远低于 kernel 工程师的薪酬。 一个体会:在编写 GPU kernel 方面,GPT-6 Astra 和 Opus 5 仍然比 OSS 模型强得多。

  2. 🚨 AI News | TestingCatalog46

    OpenAI 正在开发"Spaces"👀 最近新增了一则介绍"Spaces"的公告。 Spaces 可能是用户与智能体协作处理生成产物的环境(推测)。 部分 DevDay 场次提到了"一次耗时超过 1,000 小时的 Codex 运行"以及"多人 Codex"主题,可能与此密切相关(推测)。 * 公告字符串已被隐去

    引用🚨 AI News | TestingCatalog@testingcatalog

    OPENAI 🔥: Key insights from upcoming DevDay sessions. * This agenda is not public yet First, OpenAI will build Platform capabilities inside Codex, enabling users to develop plugins, agents, and apps right from a dedicated DevDay page, which is quite cool! Highlights from the agenda 👀 > Claw Labs "Join Peter Steinberger for a look at how agents can change the way open-source teams build." > 🔥 Codex Game Studio "What makes a game easy for humans but hard for AI? Build one and put Codex to the test." > 🔥 What Will You Build With Coding Agents That Don’t Quit? What engineering work deserves your time and tokens? Learn from a Codex run that spent more than 1,000 hours keeping builds and tests passing in a large shared codebase. See how this internal OpenAI agent had goals, subagents, and persistent plans that helped it investigate failures and coordinate fixes. > Codex Has Left The Laptop "As we move from delegating individual tasks to letting Codex tackle entire problems and goals on its own, it’s possible to harness the power of Codex wherever and however you work. " > From Single Player to Multiplayer with Codex "Follow a 2am outage from the first Slack messages to a reviewed fix and an update for the team." > What Comes After Loops?: Deep Dive Into Agentic Architecture "As models become more capable, agent architectures are changing. We'll trace the evolution from simple loops to collaborating agents, examine the design choices and model advancements behind that shift, and take a deep dive into what comes next."

  3. 🚨 AI News | TestingCatalog39

    OpenAI DevDay 未公开议程显示,将在 Codex 内构建 Platform 能力,支持用户通过专属 DevDay 页面开发插件、智能体和应用。议程涵盖 Codex Game Studio、可连续运行超 1,000 小时维护大型共享代码库构建与测试的内部编码智能体,以及从单人到多人协作、脱离笔记本使用和智能体架构演进等主题。

    引用🚨 AI News | TestingCatalog@testingcatalog

    @OpenAIDevs A good spot 🍿

  4. AWS Machine Learning Blog62

    xAI Grok 4.7 上线 Amazon Bedrock

    xAI 的 Grok 4.7 已在 Amazon Bedrock 可用,面向编码、长时间运行的 AI 智能体和知识工作,提供 500K token 上下文窗口及 low、medium、high、xhigh 四档推理强度。

    推荐理由:文章同时说明模型能力、跨区域推理配置和三种 API 接入方式,便于团队评估迁移与成本控制。

  5. ClaudeDevs72

    Anthropic 发布 Claude 5.5 系列第二款模型 Claude Sonnet 5.5。该模型相比 Sonnet 5 更聪明、更高效,运行速度提升超过 30%,大多数任务成本最高降低 30%,适合修复 bug 和快速迭代功能等边界清晰的日常任务,也能让 Claude Code 使用额度覆盖更多工作。

    引用Claude@claudeai

    Introducing Claude Sonnet 5.5, the second model in the Claude 5.5 family. It’s a clear upgrade over Sonnet 5, runs more than 30% faster, and costs up to 30% less for most work.

    推荐理由:材料给出 Sonnet 5.5 相对 Sonnet 5 的速度、成本变化和适用任务,可帮助判断 Claude Code 日常使用的升级价值。

  6. TechCrunch · AI78

    Anthropic 发布 Sonnet 5.5,主打更快速度与更低使用成本

    Anthropic 发布中端模型 Sonnet 5.5,称其比 Sonnet 5 快 30%,token 消耗速度显著降低,适合编码和制作办公文档等日常任务。Anthropic 的基准显示,Sonnet 5.5 在智能体编码上表现优于 Opus 5.5,并具备与 Opus 5 相当的网络能力,因此将适用与 Fable 和 Opus 相同的网络安全防护。

    推荐理由:文章整理了 Sonnet 5.5 相对 Sonnet 5 的速度、成本和智能体编码表现,并说明其网络能力防护安排。

  7. elvis52

    Base44 推出 Base Code 早期预览版,定位为面向智能体时代的软件开发工具。它会扫描 GitHub 仓库并在云端配置数据库、Redis 等基础设施,生成可持续运行的预览环境,团队成员无需同步本地环境即可协作。产品还规划浏览器与手机入口、WhatsApp 和 iMessage 支持,以及让 AI 智能体读取支持工单、修复缺陷、开发功能并在云端验证的自动化流程;当前提供 30 天免费试用,入口为 http://app.base44.com/base-code。

    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. François Chollet41

    François Chollet 表示自己如今不再直接读写代码,而是通过指令 LRM 完成开发,核心原因是手写代码的 ROI 已不再划算。LRM 不仅能写代码,还能快速完成代码库测试、组件审计、可视化生成与红队测试等任务,形成比传统流程更高产的新工作流。这一转变并非因为 LRM 代码质量完美或指令总能被准确执行,而是其速度带来的流程优势。

  2. 公众号:小林coding12

    小林coding推出AI大模型《就业保薪班》,主打Agent开发转型与保薪承诺

    小林coding推出AI大模型《就业保薪班》,面向Agent开发、大模型岗位转型,课程涵盖Transformer架构、LoRA、QLoRA、Agent、Claude Code等内容。班级承诺在校应届生最低年薪30万、在职人员薪资涨幅40%-50%,未达标可全额退款,并称往期学员平均薪资38w+、90%拿到AI岗位offer。

  3. OpenAI News12

    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。

  4. Claude Platform:开发者版本说明(RSS)80

    Anthropic 发布 Claude Sonnet 5.5 并说明 API 迁移变化

    Anthropic 于 9 月 28 日发布 Claude Sonnet 5.5(claude-sonnet-5-5),已在 Claude API、Amazon Bedrock、Claude Platform on AWS、Google Cloud 和 Microsoft Foundry 提供。

    推荐理由:官方同时列出多平台可用性和从 Claude Sonnet 5 迁移时的五类兼容性变化,便于开发者提前调整请求与工具调用。

9月27日周日
9月26日周六
  1. 公众号:小林coding52

    用户领取 Anthropic Claude Code 云端额度后反馈账号被封

    多名用户在领取 Anthropic 面向 Pro 用户的 100 美元、Max 用户的 250 美元 Claude Code 云端编程额度后反馈账号被封。领取福利需要绑定 GitHub 并授权 Claude 访问代码仓库,有人猜测地区识别触发风控,但原文说明这仍只是猜测。作者还提到两个月前 Claude「Max 零元购」后曾出现大规模封号,并在文末链接其阿里云端 Claude Code 搭建教程。

9月25日周五
  1. François Chollet35

    我认为软件工程的“难度”本质上是恒定的,无论你切换到什么抽象层级,因为人类认知会适应新工具,直到能充分利用自身。 工具只是可供性,不是让工作消失的魔法棒。 过去,出色的软件工程极具挑战性。现在依然极具挑战性,尽管工作流程已大不相同。

    引用Simon Willison@simonw

    The more time I spend working with coding agents, the more convinced I am that they make software engineering even harder We can do amazing things with them, but unlocking their full potential requires extraordinary discipline and knowledge