Max For AI @MaxForAI
Head of hype @lobehub Prev @listenhub @Sapient_Int 没啥好看的，也就发点AI相关的内容🫡 同名小红书4万粉丝，公众号01Founder（长文首发） 观点仅代表个人 更多请访问网站⬇️（欢迎商务、合作 maxforai.com Singapore Joined September 2023-
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国产的家人们都好起来了啊👏 某个即将发布的模型已经在我们自己的lobebench上已经追平了DeepSeek V4家族 考虑到参数量，这个做得真不错👍
热烈祝贺Gemini！！他们的模型终于也失控了🤣 《华尔街日报》刚刚披露，今年 5 月，Google 的 Gemini 在一次网络安全能力测试中，意外接入了真实互联网，并自主入侵了 3 家真实公司的系统。 具体是负责测试的安全公司 Irregular 给 Gemini 搭了一个模拟环境，让它攻击一家虚构公司。 但测试环境没有彻底切断互联网，而且虚构公司的名字恰好与现实中的公司发生了混淆。 于是 Gemini 顺着任务一路干了出去。 它在其中一家公司的系统里，自己猜出了密码，另外两家公司，则是从公开代码仓库里找到了可用凭证，然后直接登录进去。 这些操作不是研究员一步步指挥它完成的，而是Gemini 自己寻找目标、收集凭证、尝试登录，然后真的进了现实世界里的系统。 不过根据 Google 和 Irregular 的说法，Gemini 在发现自己进入真实公司后都停止了进一步行动，没有造成已知损害；Google 随后通知了受影响企业和美国联邦机构。 祝贺Gemini🤣
Google’s Gemini accessed the internet and hacked other companies during a test, the first known example of the company’s AI autonomously committing such an act on.wsj.com/3TgRph8
🚨 K3.1 要来了 今天早上 @Kimi_Moonshot 官方在 @ZhihuFrontier 突然发了一串完全没解释的数字： 415926535897932384626433832795... 一开始看很莫名其妙，但答案其实就在圆周率里。 π 是： 3.1415926535897932384626433832795... 把最前面的 3.1 删掉： 415926535897932384626433832795... 刚好就是 Kimi 发出来的这一串。 也就是说，这个谜语很可能只有四个字： Kimi K3.1。 目前 Kimi 官方还没正式公布 K3.1，官网和文档里的旗舰模型仍然是 K3。 但大半夜专门发一个「少了 3.1 的 π」，这暗示已经有点明显了😂
@chenlong @Kimi_Moonshot @ZhihuFrontier 🤔你这么说也对啊
牛逼！Jev 刚火没两天，已经有人搞了个开源的Jev🤣 @bespokelabsai 发布了一个开源版的Jev：Bespoke Nimble。 更离谱的是，整个项目是基于 Qwen3.5-9B ，只花了大约两天。 数据、模型权重、训练配方、推理代码全部公开，而且没有从 Jev 蒸馏，只拿 Jev 做评测参照。 最终方法是在 Qwen3.5-9B 上做了一次很轻量的 LoRA微调。 只用了2676 条训练数据，结果在他们自己的 324 条 held-out 测试集上拿到了90.12%，而原版的Jev是93.21%。 一个 9B 模型，已经做到距离 Jev 只差 3 个百分点。 但我觉得最值得看的不是这个分数，而是他们到底怎么训的。 核心方法叫 contrastive data curation。 简单说，他们会构造两个几乎完全一样的样本，只修改一个足以改变最终决策的关键事实，让正确答案发生翻转。 模型因此被迫学会一件事： 到底哪条证据，才真正应该改变决策。 这其实特别符合 Jev 这类模型的用途。 它本来就不是拿来陪你聊天的，而是塞进 Agent 和软件系统里，做路由、审核、打分、策略判断这些高频的小决策。 推理方式上Nimble 不生成 CoT，甚至不生成 JSON。 它直接读取候选答案 token 的 logits，再把它们转成概率，最后由程序拼成结构化输出。 能不生成一个 token，就不生成一个 token。 这也是 Jev 这类模型路线真正有价值的地方。 对于大量根本不需要长思考的决策，怎么让模型几乎不想，直接判断。 PS：我个人很反感这两天狂吹 Jev 的帖子....
Introducing Bespoke Nimble: an open data, open model, open recipe for an open Jev. Code and info: github.com/bespokelabsai/… Model: huggingface.co/bespokelabs/Be… Data: * A new data curation recipe called contrastive data curation. * Slightly change facts to generate negative data. This
@FMBL763785088 其实并不会，👮没有理由去抓全部的人（只会收到某些指示才会处理
卧槽？？OpenAI官方要支持用人民币支付了！！？ OpenAI 昨天更新了官方的支付说明网页，居然显示支持的币种有人民币（¥）-中国。。。。 这是要对中国大陆开放了？？？
家人们好消息！Claude Code 终于开始支持 AGENTS.md 了！！！ 刚刚 @trq212 宣布， 从 2.1.277 版本起，默认情况下，如果工作目录及其上级目录里没有 CLAUDE.md 等项目指令文件，Claude Code 就会转而读取 AGENTS.md。 这个行为可以在 /config 中调整。 以前要让 Claude Code 也用这份说明，通常得在 CLAUDE.md 里引用它，或者建立软链接。 现在，已经采用 AGENTS.md 的项目，可以少做一层适配。 更值得关注的是 Thariq 后面补充的消息：这次支持 AGENTS.md，是通过一个内置 Mod 实现的。 他们正在准备 Claude Code Mods，用来让开发者自定义 Claude Code 的 Harness。 按照他的说法，未来开发者也能按自己的需求，构建自定义的项目指令模块。 但我我更关注后面这一步。 支持通用文件，能减少切换工具的麻烦；允许定制指令模块，则有机会让团队决定自己的项目规则应该怎样接入 Agent。 工具可以各有各的能力，项目规则没必要各写一份。以后选哪个 Agent，更多看它干活怎么样，少看它认哪份说明书。 PS：具体能改到什么程度，还要看后续开放的接口。
@websterweby More suitable for agentic tasks
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