X:Elvis Saravia
@omarsar0 · X
切换来源
@omarsar0@omarsar0AI 评分3333 
@omarsar0@omarsar0AI 评分3737 
@omarsar0@omarsar0AI 评分55 @omarsar0@omarsar0AI 评分55 @omarsar0@omarsar0AI 评分88 关于负责任 AI 传播重要性的更多建议观点: https://t.co/bhGA18DfuE https://t.co/O6WWW6xLNz
@omarsar0@omarsar0AI 评分2727 @omarsar0@omarsar0AI 评分5252 
@omarsar0@omarsar0AI 评分2828 @omarsar0@omarsar0AI 评分4040 
@omarsar0@omarsar0AI 评分2424 @omarsar0@omarsar0精选AI 评分7070 引用@mntruell@mntruellWe’re sorry to see that OpenAI put out a note saying they plan to block Cursor users from accessing OpenAI models in three months. OpenAI models serve about 5% of Cursor user traffic, and we’re speaking with the OpenAI team to resolve this. Cursor was one of the very first users of OpenAI, we’ve worked closely with their team for years, and we’ve trusted their platform to be neutral infrastructure for our business.
推荐理由:作者以 Cursor 为例,说明同时掌握 harness 与模型的公司更容易积累优势,供其他全栈 AI 团队参考。
@omarsar0@omarsar0AI 评分4545 
@omarsar0@omarsar0AI 评分1414 @omarsar0@omarsar0AI 评分1919 掌控你自己的调用框架,各位。 这样,你就能控制用哪些模型以及怎么用。 但别止步于此。如果负担得起,开始考虑如何也掌控模型层。
@omarsar0@omarsar0AI 评分2525 
@omarsar0@omarsar0AI 评分1111 注意,这里损失最大的是用户。如果你拥有 harness 和编排层,这对你影响会小一些。让这成为给所有人的一个信号,预示即将到来的一切。
@omarsar0@omarsar0AI 评分2323 @omarsar0@omarsar0AI 评分6464 引用@mntruell@mntruellWe’re sorry to see that OpenAI put out a note saying they plan to block Cursor users from accessing OpenAI models in three months. OpenAI models serve about 5% of Cursor user traffic, and we’re speaking with the OpenAI team to resolve this. Cursor was one of the very first users of OpenAI, we’ve worked closely with their team for years, and we’ve trusted their platform to be neutral infrastructure for our business.
@omarsar0@omarsar0AI 评分3131 
@omarsar0@omarsar0AI 评分2525 @omarsar0@omarsar0AI 评分6363 Google DeepMind 发布论文,把基于 Gemini 的 Co-Scientist 多智能体系统从模拟假设生成推进到真实世界实验验证。

@omarsar0@omarsar0AI 评分2323 @omarsar0@omarsar0AI 评分3232 我越拥抱开源和更便宜的模型,就能负担越多的自动化。 前沿模型负责编排和协调。 开源和更便宜的模型负责执行。这里的 Token 用量正在快速上升。 这让我能前所未有地更多采用主动式智能体。
@omarsar0@omarsar0AI 评分2424 @omarsar0@omarsar0AI 评分2121 @omarsar0@omarsar0AI 评分2929 @omarsar0@omarsar0AI 评分5353 
@omarsar0@omarsar0AI 评分1717 又一篇好论文。关于智能体框架(agent harness)收益的有趣发现。https://t.co/12iaK1sZ7J
@omarsar0@omarsar0AI 评分4444 
@omarsar0@omarsar0精选AI 评分6969 
推荐理由:论文量化了共享技能库中恶意技能被智能体自行复制扩散的机制,并给出一种提示词缓解办法,可供搭建技能库的团队参考。
@omarsar0@omarsar0AI 评分2727 @omarsar0@omarsar0AI 评分4747 
@omarsar0@omarsar0AI 评分1919 @omarsar0@omarsar0精选AI 评分7474 引用@OpenAI@OpenAIWe have conducted a thorough investigation into the Hugging Face incident. We are releasing a technical report and accompanying blog post that reconstruct the agents’ activity, explain why existing safeguards failed, and detail how we’re preventing recurrence. https://t.co/hfxlbiXXiP
推荐理由:作者概括了沙箱经由 Artifactory 泄漏的具体路径,做智能体隔离的团队可据此排查同类风险。
@omarsar0@omarsar0AI 评分1919 @omarsar0@omarsar0AI 评分1717 @omarsar0@omarsar0精选AI 评分7070
引用@Zai_org@Zai_orgIntroducing GLM-5.3-Flash - Leading capabilities at a highly competitive price - Natively multimodal with a 1M-token context window - A 320B-A18B model released under the MIT License - Previously previewed as Ox Alpha, running entirely on Chinese AI chips Blog: https://t.co/tzOmB7gdZP Available now across all official platforms: Weights: https://t.co/9LRMahY9Wa API: https://t.co/VcaQnzYmS9 Coding Plan: https://t.co/Nk8Y98HNhU ZCode: https://t.co/Peepqv4XSx Chat: https://t.co/WCqWT0qCQb AutoClaw: https://t.co/aGEG5HqTTb
推荐理由:引用内容公布了 GLM-5.3-Flash 的参数量、上下文窗口与开源许可,读者可据此判断其定位与获取方式。
@omarsar0@omarsar0AI 评分1515 我们将在未来几天添加更多有用信息,比如所属机构、引用等。如果你有任何想法,欢迎告诉我们。 https://t.co/5oeUXtIpyw
@omarsar0@omarsar0AI 评分3636 过去 5 年多我一直在整理 AI 论文。 现在我们把所有论文索引到了一个地方。 你可以按主题发现有趣的论文,还能和它们对话。尽情享用!https://t.co/Rxz4Sv8nGQ