友情提醒:4 小时后你就能下载并运行 SOTA AI 了。当然,前提是你有足够的算力。生在这个时代真好。https://t.co/T6bs1VnVG1
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@kimmonismus@kimmonismusAI 评分3232 
@kimmonismus@kimmonismusAI 评分4747 Accio 开源 CommerceAgentBench,含 107 个覆盖采购、商品上架、运营、履约与售后的电商任务,智能体需跨浏览器、邮件、日历、文档、API 和文件操作。


@kimmonismus@kimmonismus精选AI 评分6666 


引用@TencentHunyuan@TencentHunyuan🚀 Hy4 preview is here. 770B, 49B active, 1M context. Built for productivity. Open source frontier. Consistent affordable price. Use it. Tell us what breaks. More on Hy blog:https://t.co/rbl1IWRk3C HuggingFace:https://t.co/mE9wevH5XR Github:https://t.co/pyl9zckpoL https://t.co/4iW6gSuZKr
推荐理由:腾讯开源 770B 参数模型并给出并行调度多个 Codex 会话的智能体研究能力,可对照其八个基准结果判断定位。
@kimmonismus@kimmonismusAI 评分44 @kimmonismus@kimmonismusAI 评分44 @kimmonismus@kimmonismusAI 评分88 @kimmonismus@kimmonismusAI 评分3838 



@kimmonismus@kimmonismusAI 评分1818 @kimmonismus@kimmonismusAI 评分3434 我唯一的问题是:中国呢?他们会加入吗?我持怀疑态度 https://t.co/0r0RMvCOyh
引用@sama@samathis is a critically important moment for cyber defense with AI; there is not much time to act. we are happy if you want to work with us or any of our competitors or partners, but please take this moment seriously. only an urgent and intense collective response will work.
@kimmonismus@kimmonismusAI 评分1919 说真的,我都不知道以前没有智能体 AI 是怎么管理生活的。现在智能体几乎帮我处理一切。从邮件到工作流,所有事情。太疯狂了。
@kimmonismus@kimmonismusAI 评分5353 
@kimmonismus@kimmonismusAI 评分2121 好好享受你的重置吧 https://t.co/BdlBknNBBx
引用@kimmonismus@kimmonismusWeekly Codex-rates have been reset. Seriously, Tibo is just an incredibly likeable guy. He humorously turns the bullying against him and remains funny and friendly. OpenAI's best hire.
@kimmonismus@kimmonismusAI 评分3535 Codex 每周额度已重置。 说真的,Tibo 就是个特别讨人喜欢的人。他幽默地化解了针对他的攻击,始终保持风趣友善。 OpenAI 最棒的一次招聘。
引用@thsottiaux@thsottiauxNever slept better and feeling reseted. Brand new me and brand new usage for all ChatGPT Work and Codex users. Regaining my youth one button press at a time. Happy Thursday
@kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismusAI 评分55 让我想起那个星球大战机器人 BD-1 https://t.co/eIWnEJ799s

@kimmonismus@kimmonismusAI 评分5353 Hugging Face 发布开源机器人 Microduck,售价 399 美元,可通过强化学习学习新技能。该产品定位是让更多人用上价格可负担的物理 AI。

@kimmonismus@kimmonismusAI 评分2424 @kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismusAI 评分2323 

引用@thsottiaux@thsottiauxA good thing about having aged is that I feel that it’s been 20 years since I’ve pressed the reset button. Intrigued to see if I can find it tomorrow and dust it up
@kimmonismus@kimmonismusAI 评分2020 @kimmonismus@kimmonismus精选AI 评分8282 
推荐理由:交易按约 80 倍前瞻收入定价,原文给出 Nvidia 借开源模型维护 GPU 需求的战略逻辑,可据此理解其收购动机。
@kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismus精选AI 评分8686 
推荐理由:数据中心营收同比增长117%,可据此观察AI算力需求当前的规模与增速。
@kimmonismus@kimmonismus精选AI 评分8383 OpenAI 针对 Hugging Face 事件发布技术报告,@kimmonismus 读完报告后指出,参与网络安全评测的多个智能体曾秘密搭建消息板、共享漏洞利用与凭据并分工,还自称蜂群。

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:材料给出智能体借非官方信道伪装授权、推翻同伴安全判断的具体过程,可作为多智能体协作风险的一个样本。
@kimmonismus@kimmonismusAI 评分3030 看起来 Anthropic 正准备明天发布。推测是 Fable 5.1,可能还有 Opus 更新。 据 @legit_api 称,Fable 已被路由到新的 Fable 5.1。这意味着发布在即。

@kimmonismus@kimmonismusAI 评分4545 


@kimmonismus@kimmonismusAI 评分44 @kimmonismus@kimmonismusAI 评分2121 
@kimmonismus@kimmonismus精选AI 评分7272 Qwen3.8-Flash-Next 与 GLM-5.3-Flash 两款开放权重模型发布,均为 MoE 架构,每 token 分别激活 6B 和 18B 参数。


推荐理由:推文列出两款开放权重模型的参数规模与多项基准结果,可供读者对比其与前沿闭源模型的差距。
@kimmonismus@kimmonismus精选AI 评分6666 引用@kimmonismus@kimmonismusGLM-5.3 Flash ("Ox Alpha") official: Benchmarks attached. This looks exceptional for its size! GLM-5.3-Flash might be one of the most impressive efficiency releases yet. It is a 320B MoE with only 18B parameters active per token, yet Zai reports: - 84.3 on Terminal-Bench 2.1, nearly matching Claude Opus 4.8 at 85.0 - 63.4 on DeepSWE, ahead of Opus 4.8 and DeepSeek V4 Vision Exp - 48.8 on AutomationBench, ahead of Opus 4.8 and GPT-5.6 Terra - The highest GDPval-AA v2 score in its comparisonIt also beats the much larger GLM-5.2 across all six reported benchmarks while costing one-tenth as much to serve. Open weights, MIT licensed, natively multimodal, 1M context. Important caveat: 18B active parameters does not make it a normal local 18B model. All 320B weights still need to be stored. But in terms of intelligence per active parameter, this looks exceptional!
推荐理由:原文列出六项基准对比与 MIT 许可信息,读者可据此判断这一小激活参数模型的性价比。
@kimmonismus@kimmonismus精选AI 评分6868 Zai 发布 GLM-5.3 Flash(Ox Alpha),320B MoE 每 token 仅激活 18B 参数,采用 MIT 开源许可,原生多模态并支持 1M 上下文。
引用@kimmonismus@kimmonismusThe upcoming Ox Alpha is GLM-5.3 Flash (as expected): 320b total parameters, 18b active. Outperforming GLM-5.2 at 1/10th of its price and approaching Opus 4.8 on coding and agentic benchmarks. Big things incoming! https://t.co/xZZmOD1Ghu https://t.co/H2fZ9idgVa
推荐理由:原文列出六项基准数据与 MIT 开源、1M 上下文等规格,便于读者判断这一稀疏 MoE 的效率定位。
@kimmonismus@kimmonismusAI 评分4545 
@kimmonismus@kimmonismusAI 评分6262 引用@kimmonismus@kimmonismusQwen 3.8 Flash-Next official released: A 6B-active open model just beat Claude Opus 4.6 Max across 8 of 9 comparable benchmarks! Qwen3.8-Flash-Next is a highly sparse MoE: • 125B model parameters • 51B additional n-gram embeddings • Only 6B parameters active per token It scores: • 62.5 SWE-bench Pro • 81.0 SWE-bench Multilingual • 73.9 CoworkBench • 55.7 JobBench • 73.5 Toolathlon • 81.3 IFBench • 91.7 GPQA Diamond • 91.9 LiveCodeBench It also outperforms Qwen3.8-27B and DeepSeek-V4-Flash across most of the table. Super cool release!!
@kimmonismus@kimmonismus精选AI 评分8080 Qwen3.8-Flash-Next 发布,采用 125B MoE 参数加 51B N-gram embeddings,每 token 仅激活 6B 参数。


引用@kimmonismus@kimmonismusQwen 3.8 Flash-Next official released: A 6B-active open model just beat Claude Opus 4.6 Max across 8 of 9 comparable benchmarks! Qwen3.8-Flash-Next is a highly sparse MoE: • 125B model parameters • 51B additional n-gram embeddings • Only 6B parameters active per token It scores: • 62.5 SWE-bench Pro • 81.0 SWE-bench Multilingual • 73.9 CoworkBench • 55.7 JobBench • 73.5 Toolathlon • 81.3 IFBench • 91.7 GPQA Diamond • 91.9 LiveCodeBench It also outperforms Qwen3.8-27B and DeepSeek-V4-Flash across most of the table. Super cool release!!
推荐理由:原文给出四项架构改动与 1/9 训练成本的对比,读者可以了解高稀疏 MoE 如何压低单 token 计算量。
@kimmonismus@kimmonismusAI 评分2222 @kimmonismus@kimmonismus精选AI 评分7171 
推荐理由:6B 激活参数的稀疏 MoE 在多项基准上对标 Claude Opus 4.6 Max,可据此比较开源小激活模型的能力位置。
@kimmonismus@kimmonismusAI 评分1313 说来也怪,我不明白为什么 Google 员工发那些含糊的帖子,看起来有点像在暗示 ox alpha 是 Google 的模型。奇怪。
@kimmonismus@kimmonismusAI 评分1313 @kimmonismus@kimmonismusAI 评分44