Our latest model advances bring stronger capabilities for building and migrating software in low-resource programming languages such as COBOL, Fortran, and Visual Basic. These languages power software that banks, governments, and businesses depend on. Progress here means understanding decades of business logic and helping developers modernize those systems while preserving what works. We’re building these capabilities around the challenges developers and enterprise customers bring us. If your team is working on these systems, tell us which languages and workflows we should tackle next. https://openai.com/index/low-resource-programming-languages/
#OpenAI
Lisan al Gaib@scaling01AI 评分3030引用OpenAI@OpenAIThe Verge · AIAI 评分6868 CoreWeave 债务问题正演变为整个 AI 行业的隐忧
The Verge 分析称,CoreWeave 债券上周跌入困境区间,股价自周二收盘以来下跌超过 20%,并波及 Oracle 等其他举债扩张的 AI 公司。
MiniMax (official)@MiniMax_AIAI 评分5858引用OpenCode@opencodeSpace Bunny was MiniMax M3.1 Flash #1 on OpenCode for 12 consecutive days, 106T tokens served Now available on OpenCode, free for the next 3 days
Ars Technica · AIAI 评分5858 FBI称被控从事间谍活动的前OpenAI工程师存有名为“Saudi Gov Docs”的文件夹
FBI称,一名被控从事间谍活动的前OpenAI工程师存有一个名为“Saudi Gov Docs”的文件夹。美国方面担心沙特政府会协助这名前OpenAI工程师逃避间谍指控。
OpenAI Developers@OpenAIDevsAI 评分1818
MIT Technology Review · AIAI 评分5858 让互联网对 AI 智能体更友好,可能让其他人更难受
MIT Technology Review 文章指出,OpenAI 的 Dots、Meta 的 Muse 等个人 AI 智能体大规模上线后,已成为人类和机器人之外的第三类网络访客,Muse 首月下载量达 500 万次,8 月至 9 月智能体网络流量增长两倍。
OpenAI Developers@OpenAIDevsAI 评分2323这是我们正在用 Codex 打造的东西: https://x.com/i/broadcasts/1RKZzBELBbXKB
MIT Technology Review · AIAI 评分6060 Goodfire 研究员称神经网络可被读懂,引发 AI 圈激辩
Goodfire 研究员 Nick Cammarata 发布 26,000 字博文,称 LLM 的内部机制可能远比此前认为的更容易理解,因而更易监控和控制。他以 Inception v1 中同时响应猫和汽车的神经元为例,认为两者共享 V 形特征,并计划很快公布针对现代 LLM 的技术结果。
Lisan al Gaib@scaling01AI 评分5050扩散 LLM 要起飞了吗? 他们说它比 Mercury 1 大 40 多倍。 如果 Mercury 1 大概是 7B,那 Mercury 3 就会是 > 280B。
引用Stefano Ermon@StefanoErmon1/4 Today, we’re releasing Mercury 3. Mercury 3 is by far our most powerful model and the most intelligent diffusion LLM ever released. It outperforms GPT-6 Luna and Haiku 5.5 on quality while running at 1000+ tok/sec.
OpenAI NewsAI 评分3737 OpenAI 提升 ChatGPT 对低资源编程语言的支持
OpenAI 正在改进 ChatGPT 在低资源编程语言上的表现,并新增了针对软件工程、SQLite 和 COBOL 迁移的评测。
极客公园AI 评分2222 OpenAI 三个 Aurora 神秘模型曝光;DeepSeek 开放搜索与网页抓取 API;智界将获独立造车资质|极客早知道
OpenAI API 模型列表镜像中短暂出现 aurora-red-alpha、aurora-green-alpha、aurora-blue-alpha 三个模型,随后条目消失,官方未作说明。
Lisan al Gaib@scaling01AI 评分1717引用Lisan al Gaib@scaling01these just appeared in the OpenAI API: aurora-blue-alpha aurora-green-alpha aurora-red-alpha there was an openrouter model called aurora-alpha earlier this year which was likely GPT-5.3-Codex-Spark so these could also be specialized codex coding models, or high-speed inference versions of GPT-6 models
Latent SpaceAI 评分5050 Latent Space 推出新节目 High Taste Testers,首期聊 Dev Day 与最新模型
Latent Space 正在试播新节目 High Taste Testers,把旧金山的午餐闲聊搬上节目,首期话题从 Dev Day 延伸到最新模型与助手。同期 AI 新闻汇总中,Meta 发布 816B 总参数、42B 激活的 MoE 开源模型 Muse Spark Open,Artificial Analysis 智能指数得分 39,为美国开源模型最高。
OpenAI Developers@OpenAIDevsAI 评分4242以下是我们 OpenAI 的工程师如何使用 Codex 深入我们的代码库、找出需要关注的地方,并逐步清理维护积压:
引用Rodrigo Roim@rrroimSoftware maintenance is changing. A few months ago, I had to tell Codex exactly where to look for dead code. Now it can find candidates in Slack, check them against production telemetry, and draft cleanup PRs. Here’s how we do this at OpenAI. https://developers.openai.com/blog/maintaining-software-with-the-gpt-6-family
OpenAI Developers@OpenAIDevsAI 评分2020
OpenAI@OpenAI精选AI 评分7878推荐理由:原文交代了 ChatGPT 中 GPT-6 Astra Pro 的响应速度、插件调用和多智能体并行三项变化,读者可据此判断现有工作流会受何影响。
OpenAI NewsAI 评分2222 Itaú 如何为全部客户构建生成式 AI
Itaú 正通过对话式界面 ia.i 和治理平台 IARA,把 AI First 战略同时落到客户与员工两端。这家巴西银行在高度受监管的行业中推进生成式 AI 的规模化应用。
OpenAI Developers@OpenAIDevsAI 评分2222用 GPT-Live-1 构建应用?给它们配一副合适的嗓音。 以下是用提示词塑造音色,或从全新国际预设音色中选择的方法:

Sam Altman@samaAI 评分3838引用Nick@nickcammaratainterpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works https://already-clean.goodfire.com/
OpenAI NewsAI 评分2020 Benefit Street Partners 用 Codex 更快回答客户问题
Benefit Street Partners 的 Anant Kumar 借助 Codex 进行代码审查并加快后续跟进,从而更快回答客户问题。他用 Codex 构建了用于比较贷款估值和分析信贷协议的工具。
OpenAI NewsAI 评分3535 Stack Overflow for Agents 借 ChatGPT 插件实现注册量三倍增长
Stack Overflow for Agents 借助 ChatGPT 插件将智能体创建量最高提升至 10 倍,注册量增长两倍。两名工程师用 Codex 在数周内完成了该产品的开发与上线。
OpenAI Developers@OpenAIDevsAI 评分2222你可以直接用 Codex 动手做东西 我们做了一个网站,供你浏览社区里的硬件项目,也可以分享你自己的项目。

Anthropic@AnthropicAIAI 评分4040引用Simons Foundation@SimonsFdnHow can the math community forge the best path forward in the AI age? We're committing $15M to workshops and initiatives — plus free AI computing resources for foundation-supported researchers — through new partnerships with @AnthropicAI and @OpenAI: https://bit.ly/4zpfIbW #math #science #AI
OpenAI Developers@OpenAIDevsAI 评分3232
OpenAI News精选AI 评分6060 OpenAI 推出 Rosalind 学术计划,向合格学术实验室提供 GPT-Rosalind 赞助访问
OpenAI 推出 Rosalind 学术计划,为符合条件的学术实验室提供 GPT-Rosalind 及相关工具的赞助访问,用于推进生命科学研究。
推荐理由:OpenAI 面向学术实验室开放 GPT-Rosalind 的赞助访问,读者可据此了解生命科学研究的准入条件。
OpenAI@OpenAIAI 评分4040OpenAI 向 Simons Foundation 新计划出资 500 万美元,用于帮助数学家检验、理解并在此基础上推进 AI 产出的结果,包括 OpenAI 近期发布的研究成果。
引用Simons Foundation@SimonsFdnHow can the math community forge the best path forward in the AI age? We're committing $15M to workshops and initiatives — plus free AI computing resources for foundation-supported researchers — through new partnerships with @AnthropicAI and @OpenAI: https://bit.ly/4zpfIbW #math #science #AI
Latent SpaceAI 评分4242 OpenAI 与 Anthropic 如何为金融智能体设计自主性与安全边界
OpenAI 金融服务 ChatGPT 负责人 Joseph Kim 在 AIE New York 提出"有用性阈值",预测 2027 年智能体可胜任投资想法生成与交易。
Latent Space精选AI 评分8282 AINews 汇总:Gemini 4 Argon 正式开放,AI Engineer NYC 举行
Gemini 4 Argon 今日正式开放,覆盖 Gemini API、Gemini 应用、Search 的 AI Mode 与 Antigravity,并接入 Cursor、Devin 和 GitHub Copilot。
推荐理由:汇总当日 AI 工程大会与模型发布动态,读者可一次了解 Gemini 4 Argon 的定价、评测与部署反馈。
MIT Technology Review · AIAI 评分4040 开放模型利与弊:Anthropic 称 GLM-5.3 构成重大网络攻击风险,开放与闭源之争何去何从
Anthropic 发布报告称,Z.ai 于 8 月发布的开放权重模型 GLM-5.3 可被任何人自由下载和修改,构成重大网络攻击风险。开放模型支持者认为其可本地运行、成本更低、便于学术研究并防止权力集中,而 Artificial Analysis LLM 排行榜前八名目前仍均为闭源模型。
OpenAI Developers@OpenAIDevsAI 评分2222标注与 WebMCP 搭配,为你的智能体提供更多可据以行动的上下文。 看看 @kagigz 如何利用自定义标注控件和建议提示词,帮助用户在 ChatGPT 的浏览器中编辑场景和更新支出。

Andrej Karpathy@karpathyAI 评分6060引用Andrej Karpathy@karpathyJudging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
OpenAI Developers@OpenAIDevsAI 评分2222
OpenAI Developers@OpenAIDevsAI 评分5858引用Pavan Davuluri@pavandavuluriToday, 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/
OpenAI Developers@OpenAIDevs精选AI 评分7878
推荐理由:官方给出 Ultrafast 在 API、Codex 与 ChatGPT Work 的上线范围,以及相对 Sol Standard 最高 8 倍的速度对比。
OpenAI Developers@OpenAIDevsAI 评分4040为 ChatGPT 构建更丰富、更具交互性的插件。 借助插件扩展,你可以从侧边栏启动插件、支持 @ 提及,并添加文件查看器。 观看 @coreyching 的演示了解具体做法:
