亲吻数又叫牛顿数，是希尔伯特第十八问题（球体堆积）的局部形式，和通信技术中的"比特拥挤"问题是同一套底层逻辑。 闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 情人节到了… 那咱也来应应景，讲讲亲吻这件事—— AI的打开方式。 你或许知道，数学上有个正经问题叫做 亲吻数（Kissing Number Problem） ，卡了人类300多年，但就在最近，被 中国AI 狠狠推了一 把。 简单说，它研究的是：在n维空间中，一个球体周围，最多能有多少个和它大小相同的球体，刚好与它相切（kiss），不重叠的那种 。 它源自于1694年，牛顿和格雷戈里两位大佬的争吵： 在三维空间里，一个球周围到底能放12个，还是13个同款球？牛顿坚持12，格雷戈里不服，结果谁也没能当场辩过谁。 直到1953年，数学家用了 258年 时间才严格证明牛顿是对的。 就连2022年获得 菲尔兹奖 的玛丽娜·维亚佐夫斯卡， 正是凭借解决8维和24维空间的最密球体堆积问题，摘得桂冠。 但再往高维走，人类的直觉就崩了。在过去近50年里，亲吻数构造仅有7次实质性进展，而且每一次的方法都完全不同，在临近维度上难以迁 移与复用。 现在，僵局被打破了。 ...

闻乐 发自 凹非寺 量子位 | 公众号 QbitAI "OpenClaw们"让2026彻底卷成了智能体大战。 当初那个"智能体早期真神"，让25个智能体自己聊天、传八卦、谈恋爱的AI小镇Smallville团队也官宣创业了。 不仅当年在GitHub开源的时候爆火，现在一创业，热度依旧拉满。 公司名叫 Simile ，直接拿下了Index Ventures领投的1亿美元融资，连 卡帕西 、 李飞飞 也跟了。 当时AI小镇横空出世，这个"学术玩具"被视为 生成式智能体 领域的开创性成果，证明大模型能在虚拟世界里"活"起来。 现在创业是要把25个智能体升级为千级的大规模智能体平台，帮助人类进行决策的风险预测。 以防有朋友不知道AI小镇是干啥的，咱先来个前情回顾复习一下。 AI小镇 2023年，斯坦福团队在论文《Generative Agents》里，构建了一个叫Smallville的像素风虚拟空间。 他们把25个基于GPT的AI放进了小镇里，只给每个AI设定了一个简单的身份描述，比如外向的咖啡馆老板、乐于助人的药店店主等。 结果这25个智能体能在小镇里完全自主生活。 早上醒来刷牙、做早餐、去上班，下午闲聊八卦，晚上 ...

Core Viewpoint - The article discusses a groundbreaking discovery in particle physics where a long-held conclusion about gluon scattering amplitudes has been overturned, thanks to the contributions of GPT-5.2, which identified a key formula that was later proven by an OpenAI internal model [1][2][15]. Group 1: Discovery and Research Process - A previously believed zero scattering amplitude for a specific type of gluon scattering is shown to not be zero under certain kinematic conditions [2][14]. - The research team, led by Harvard's Andrew Strominger, initially struggled with complex calculations that grew exponentially with the number of parameters [4][19]. - The team turned to OpenAI to see if AI could assist, leading to GPT-5.2 proposing a crucial formula that simplified the problem [6][7]. Group 2: Technical Details of the Findings - Scattering amplitudes are central to particle physics, providing quantum probabilities for particle collisions, but their calculations are notoriously difficult [9]. - The article highlights the historical context, referencing the work of Parke and Taylor, who previously derived a complex expression for scattering amplitudes that was later simplified to a single line [11][13]. - GPT-5.2 identified a simplification when restricting to a specific region, leading to a significant reduction in the complexity of the expressions involved [26][28]. Group 3: Validation and Implications - The formula proposed by GPT-5.2 was proven by an OpenAI internal model after over 12 hours of computation, confirming its validity [29][30]. - The research team verified the proof manually, ensuring it met various consistency conditions, although these properties were not immediately apparent from the formula itself [32][33]. - This discovery marks the third instance of GPT-5.2 making original contributions to fundamental science, indicating the potential for AI to uncover previously unknown physical laws [34][40]. Group 4: Future Directions - The article notes that while the current formula represents a dramatic simplification, there is potential for even more concise expressions to be discovered [38][39]. - Future work is expected to explore the implications of these findings in broader contexts, including gravitational amplitudes and supersymmetry [37].

克雷西 发自 凹非寺 量子位 | 公众号 QbitAI 来来来，狠角色来给春节AI大模型大战升级了。 刚刚，蚂蚁集团正式发布了全球首个开源混合线性架构万亿参数模型 Ring-2.5-1T 。 这次它在 数学逻辑推理和长程自主执行能力 上都练就了一身本领。 目前它已适配Claude Code、OpenClaw这些主流智能体框架，模型权重和推理代码也已经在Hugging Face、ModelScope等平台同步开放 了。 混合架构让效率大幅提升 Ring-2.5-1T之所以能打破深度思考必然牺牲推理速度这一行业魔咒，主要是因为其底层采用了 混合线性注意力架构 。 这种架构基于Ring-flash-linear-2.0技术路线演进而来。具体来说，其采用了1:7的MLA（Multi-Head Latent Attention）配Lightning Linear Attention的混搭设计。 具体来说，它在IMO拿到了35分的金牌水平，CMO更是轰出105分远超国家集训队线；任务执行方面，则在搜索、编码这些复杂任务上都能 独当一面。 而且这次发布， 打破了业界长期以来关于深度思考必然要牺牲推理速度和显存的"不可能三角 ...

鹭羽 发自 凹非寺 量子位 | 公众号 QbitAI WHATTT！当红炸子鸡 OpenClaw 要走Manus老路了？！ OpenClaw之父Peter Steinberger亲口承认： 同时收到 小扎 和 奥特曼 递出的橄榄枝。 开出的条件更是一个比一个优厚—— Meta这边，技术宅小扎直接 Boss直聘 ，闭关一周亲自上手OpenClaw后：I Want YOU！ 再看OpenAI，奥特曼那边更是祭出雷神之锤：算力诱惑。 不止这两家，微软等公司也都纷纷下场，只为能够分一杯羹。 有趣的是，Peter还专门透露，在当初的改名风波中，他还特意 致电奥特曼 ，使用"Open"一词是否冒犯～ 毕竟OpenClaw——OpenAI、Clawdbot——Claude。 而早早被踢出局的Anthropic，不知可曾有悔？ （doge） 以上这些，都通通出自Peter的最新一期播客，主持人还是最会挖掘内幕消息的Lex Fridman。 他用 3小时 深度对谈，让Peter将有关OpenClaw的更多幕后故事，全交代了。 ……. 硅谷已经盯上了OpenClaw这块肥肉 OpenClaw有多火？且看GitHub最新star数 ...

Core Viewpoint - The article highlights the advancements in humanoid robots and drones, particularly focusing on the innovative capabilities of China Telecom's TeleAI in developing integrated intelligent systems that enhance operational efficiency in complex environments [6][7]. Group 1: Technology and Innovation - China Telecom's TeleAI has introduced a humanoid robot, TeleBot-M, and a versatile drone, TeleAqua-Bee, showcasing a significant leap in embodied intelligence [9][16]. - TeleBot-M features a lightweight design with a single-arm and a six-degree-of-freedom leg, enabling stable movement and interaction with drones [10]. - The robot is powered by a self-developed high-performance neural system, TeleBotOS, which ensures smooth operation and precise control even under heavy computational loads [12]. - TeleBot-M's learning capabilities are enhanced by a simulation platform that allows it to adapt to complex environments through reinforcement learning [14][15]. Group 2: Functional Capabilities - TeleAqua-Bee is a compact drone that can operate both in the air and underwater, with a flight time of 10 minutes and a diving capability of 30 minutes to a depth of 10 meters [20][21]. - The TeleAqua family includes various models designed for specific tasks, such as TeleAqua-H8, which can carry a 5 kg load and operate for extended periods [24]. Group 3: Connectivity and Communication - The AI Flow architecture developed by TeleAI ensures seamless data transmission between robots and drones, even in challenging environments with limited connectivity [29][30]. - The GVC technology compresses video data significantly, allowing for efficient transmission of semantic information rather than raw pixels, enhancing communication capabilities [31][32]. Group 4: Applications and Future Prospects - The integration of these technologies aims to facilitate operations in hazardous environments, such as disaster response and industrial inspections, where human presence is risky [40][41]. - The vision for the future includes a network of intelligent agents that can collaborate effectively, enhancing operational capabilities across various sectors [45].

CoMeT团队 投稿 量子位 | 公众号 QbitAI 当大模型试图处理一段包含100万token的超长文档时，会发生什么？答案是： 内存爆炸，计算崩溃 。 无论是分析整个代码库、处理万字研报，还是进行超长多轮对话，LLM的"长文本能力"都是其走向更高阶智能的关键。然而，Transformer架 构的固有瓶颈── 与上下文长度成平方关系的计算复杂度和线性增长的KV Cache ，使其在面对超长序列时力不从心，变成了一个既"算不 动"也"存不下"的"吞金巨兽"。 为了"续命"，现有方案要么选择上下文压缩，但这本质上是有损的，信息丢失不可避免；要么采用循环机制，但这类模型又常常"健忘"，难以 保留贯穿全文的关键信息，也记不清刚刚发生的细节。 △ CoMeT在32k上下文训练后，可在1M token中精准大海捞针，且推理速度和内存占用远优于全注意力模型 鱼与熊掌兼得："协同记忆"架构 CoMeT的巧妙之处在于，它没有试图用单一机制解决所有问题，而是设计了一套双轨并行的协同记忆系统，让模型既能"记得牢"，又能"看得 清"。 1. 全局记忆（Global Memory）：一个带"门禁"的记忆保险箱 为了解决长期遗忘问题 ...

编辑部 发自 凹非寺 量子位 | 公众号 QbitAI AI热潮还在汹涌，但如果你还不知道如何参与……那为什么不来 量子位 呢？ 加入我们，你可以获得： 以下是岗位详情： 所有岗位不同能力层级职位均在开放，欢迎结合个人履历和经验申请。 AI产业方向 岗位职责： AI产业方向 ：关注基建层创新，包含芯片、AI Infra、云计算； AI财经方向 ：关注AI领域创投和财报，跟踪产业链资本动向； AI产品方向 ：关注AI在应用和硬件终端方向的进展。 社招：覆盖编辑、主笔、主编各个层级，按能力匹配岗位； 校招：应届毕业生，接受实习且可转正。 我们是一家以 追踪AI新进展 为核心的内容平台，经过8年积累，目前拥有顶流影响力，广泛且备受认可的产业资源，以及时代风口的最佳观 测和学习生态位。 目前，我们有 三大方向 岗位招聘，希望你是 （或者能成为） 这三个方向的内容专家： 岗位均为全职，工作地点：北京中关村。 岗位面向： 岗位职责： 任职要求： AI产品方向 岗位职责： 站在AI浪潮之巅 ：第一时间接触和了解AI领域最新技术和产品，构建完整的AI认知体系。 玩转AI新工具 ：将各种AI新技术、新工具应用于工作，提升工作效 ...

梦瑶 发自 凹非寺 量子位 | 公众号 QbitAI 太热闹了！整个一个现象级show time～ 前脚字节刚上线 Seedance 2.0 ，后脚直接全网现象级刷屏！！！ 这边 马斯克 怒赞，那边 美国导演 直呼好莱坞要完蛋了。 甚至急得不少老外狂催更：啥时候能开放全球使用？咋注册中国账号？在线等！挺急的！ 如此之火爆，如此之amzing，那咱高低也得上手搓一把试试。 看我搓的这个全网超火的「猫咪大战哥斯拉」同款视频，小猫一跃，直接一个重拳出击～ 再来看这个AI版《F1狂飙飞车》，转速表飙升、刹车尖啸，太有好莱坞内味儿了嗷： 再来试试Chinese kungfu大战钢铁侠，俩人一来一回近身过招，音效刺激感拉满，太带派了！ 脑洞大开的网友们更会整活儿，快看下面这位网友做的一镜到底，镜头从街头一路滑进地铁站、钻进车厢，超有梦核感： 还有这位网友，只是上传了一张漫画截图，Seedance 2.0直接给他整出了一整段剧情视频，别太amazing啊我说！！ 老实说，Seedance 2.0确实对镜头语言理解更到位也更可控了，参考能力直接next level，很适合咱日常做多镜头和精细化控制使用～ 老规矩不废话，咱直接 ...

Core Viewpoint - The article discusses the launch of "Teamily AI," a groundbreaking AI-native instant messaging application that integrates AI agents into social interactions, allowing them to participate in group discussions and decision-making processes, thus transforming the role of AI from a personal assistant to a collaborative entity within social networks [1][5][8]. Group 1: AI Integration in Social Interactions - Teamily AI allows users to invite AI agents into their social circles, enabling real-time responses to group needs and facilitating collaborative tasks [1][6]. - The platform supports various content forms, including images, videos, and long texts, allowing AI agents to engage in diverse discussions and tasks [6][10]. - AI agents can understand and respond to casual prompts in group chats, making interactions feel natural and seamless [15][19]. Group 2: AI in Work Environments - In professional settings, Teamily AI can assist in brainstorming sessions, project planning, and data analysis, significantly reducing communication overhead and improving collaboration efficiency [22][24]. - The AI agent can quickly analyze lengthy reports and provide structured insights, enhancing decision-making processes within teams [23][30]. - The platform's ability to manage multiple roles and tasks allows for a more organized workflow, addressing the complexities of team dynamics [42][44]. Group 3: Technical Framework and User Experience - Teamily AI eliminates the need for local deployment, allowing users to create personalized AI agents easily without technical barriers [31][33]. - The platform emphasizes privacy and user control, enabling individuals to manage permissions and data access for their AI agents [36][38]. - The underlying technology consists of a three-layer architecture that facilitates context management, user intent understanding, and task coordination among AI agents and human members [44]. Group 4: Future Implications - The integration of AI agents into social and work environments signifies a shift in human collaboration, where AI becomes an active participant rather than a passive tool [55][56]. - The potential for each individual to have a dedicated AI agent team suggests a future where AI is deeply embedded in daily social and professional interactions [55].