Core Insights - Linus Torvalds expresses a generally positive attitude towards vibe coding as a way to introduce newcomers to programming, but emphasizes it is not suitable for production-level code due to maintenance concerns [2][5][31] - The introduction of Rust into the Linux kernel is seen as a significant change, with Torvalds noting that it is becoming a real part of the kernel rather than just an experimental feature, although the process is slower than expected [3][15][21] - AI's impact on the software development landscape is complex, with Torvalds suggesting that while AI tools can enhance productivity, they will not replace the need for skilled programmers [34][36] Group 1: AI and Software Development - Torvalds acknowledges the disruptive influence of AI, particularly the influx of AI-generated bug reports that complicate kernel maintenance, although the impact is less severe compared to other projects [4][23][26] - He has not personally used AI coding tools but recognizes their potential for improving productivity in certain contexts, while cautioning against over-reliance on them for serious projects [5][27][34] - The expectation is that AI will eventually become a standard tool in software development, similar to compilers, enhancing efficiency without eliminating the need for human programmers [34][36] Group 2: Linux Kernel Development - Torvalds has shifted from primarily rejecting new ideas to occasionally endorsing them, indicating a change in his role as a maintainer to encourage innovation within the kernel community [10][13][15] - The Linux kernel development process has remained stable, but recent years have seen significant debates and changes, including the removal of certain components to reduce friction within the community [15][17][21] - The relationship between Nvidia and the Linux community has improved, with Nvidia becoming a more cooperative player in the Linux kernel space due to the importance of Linux in AI cloud applications [4][21][22]

整理 | 傅宇琪、褚杏娟 一个 Bug 审稿人信息全泄露，ICLR、NeurIPS、ACL 都遭殃；某车企录音曝光，周六没去加班被逼离职？腾讯员工工作满 15 年即可退休，一次性拿到 21 个月工资；稚晖君"，当选上市公司董事长；百度新设两个大模型研发部，直接向 CEO 汇报；苹果罕见裁员，英特尔有望为 M 系列芯片代工 ；华为云大调 整：张平安升任董事长，周跃峰接棒 CEO，新设 5 大产品线；国际 IT 巨头惠普宣布：全球裁员约 10%；曝特斯拉曾拆解多款中国电动汽车，并在部分车型 上借鉴了相关做法…… 行业热点 一个 Bug 审稿人信息全泄露，ICLR、NeurIPS、ACL 都遭殃 2025 年 11 月，OpenReview 平台出现的一个系统级漏洞引发了学术圈的震动，该漏洞导致 ICLR、NeurIPS、ACL 等多个计算机顶会的双盲评审机制 失效，审稿人、作者及领域主席的姓名、邮箱、单位等个人信息被泄露，且只要在特定 API 链接中输入相关字段，就能获取这些本应隐匿的信息，甚至 过往年份各大顶会的审稿人名单也被人爬取，平台俨然变成了 "人肉" 工具。 ICLR 2026 率先发布声明，称于 11 ...

Core Insights - The era of relying solely on scaling resources to achieve breakthroughs in AI capabilities may be over, as stated by Ilya Sutskever, former chief scientist of OpenAI [2] - Current AI technologies can still produce significant economic and social impacts, even without further breakthroughs [5] - The consensus among experts is that achieving Artificial General Intelligence (AGI) may require more breakthroughs, particularly in continuous learning and sample efficiency, likely within the next 20 years [5] Group 1 - Ilya Sutskever emphasized that the belief in "bigger is better" for AI development is diminishing, indicating a shift back to a research-driven era [16][42] - The current models exhibit a "jaggedness" in performance, excelling in benchmarks but struggling with real-world tasks, highlighting a gap in generalization capabilities [16][20] - The focus on scaling has led to a situation where the number of companies exceeds the number of novel ideas, suggesting a need for innovative thinking in AI research [60] Group 2 - The discussion on the importance of emotional intelligence in humans was compared to the value function in AI, suggesting that emotions play a crucial role in decision-making processes [31][39] - Sutskever pointed out that the evolution of human capabilities in areas like vision and motor skills provides a strong prior knowledge that current AI lacks [49] - The potential for rapid economic growth through the deployment of advanced AI systems was highlighted, with the caveat that regulatory mechanisms could influence this growth [82]

作者 | Robert Krzaczyński 译者 | 田橙 苹果正式发布全新开源工具 Embedding Atlas，支持对大规模嵌入向量（Embeddings）进行交互式可视化与探索。该平台专为研究人员、数据科学家及 开发者量身打造，提供了一种快速且直观的方式来分析从文本嵌入到多模态表示等复杂的高维数据，且无需任何后端基础设施或上传外部数据。 Embedding Atlas 的应用不止于科研可视化，它更是一款通用的工具包，用于跨领域探索模型表征。开发者利用它可以审视模型如何对语义进行编码， 对比不同训练批次的嵌入空间，或者为检索、相似度搜索及可解释性研究等下游应用构建交互式演示。 该项目已引起 AI 社区的广泛关注。例如，研发工程师 Haikal Ardikatama 问道： 该系统完全在浏览器端运行，这意味着包括嵌入生成和投影在内的所有计算任务均在本地完成。这一设计既保障了数据隐私与可复现性，也能让用户流 畅地交互探索数百万个数据点。借助简洁的 WebGPU 驱动界面，用户可以实时缩放、筛选和搜索嵌入向量，仅需极简的设置即可轻松识别数据中的模 式、聚类及异常点。 Embedding Atlas 开箱即 ...

Core Viewpoint - The "2025 China Technology Power Annual List" is set to recognize outstanding contributions in the AI sector, with a strong lineup of participating companies and a focus on AI innovations and applications [4][5]. Group 1: Event Details - The final registration date for the "2025 China Technology Power Annual List" is November 30, with only one day remaining for submissions [3]. - This year marks the fifth consecutive year of the list's evaluation, receiving submissions from over 100 companies, including industry giants like Alibaba, Tencent, and ByteDance, as well as innovative representatives [4]. - The theme for this year's list is "Insight into AI Transformation, Witnessing an Intelligent Future," covering eight major areas related to AI advancements [4]. Group 2: Award Categories - The awards will include eight categories: - 2025 AI Infrastructure Excellence Award TOP20 - 2025 AI Engineering and Deployment Excellence Award TOP20 - "Artificial Intelligence +" Best Industry Solution TOP20 - AI Agent Most Productive Product/Application/Platform TOP15 - Data & AI Most Valuable Product/Platform TOP10 - AI Coding Most Productive Product TOP5 - Embodied Intelligence Star Product TOP10 - AI Open Source Star Project TOP10 [5]. Group 3: Evaluation Process - The evaluation results will be announced on December 19 during the AICon·Beijing event, which will also feature a grand award ceremony [8]. - The evaluation criteria for various awards will involve scoring from an expert panel and the InfoQ editorial team, with user ratings contributing to some categories [9][11]. - Specific dimensions for evaluation will be outlined in the registration forms, focusing on factors such as internal implementation effectiveness, resource investment, replicability, data security, and community engagement in open-source projects [12][14].

Core Viewpoint - Infinite Reality, a tech startup, has raised significant concerns regarding its financial status and business model despite claiming a valuation of $155 billion after a $30 billion investment from an anonymous investor [2][11][12]. Company Background - Infinite Reality was founded in 2020, initially focusing on enterprise-level metaverse solutions, including virtual meeting platforms and digital asset trading systems [3]. - The company is led by CEO John Acunto, who has extensive experience in the tech and creative sectors, having collaborated with major companies like IBM, Apple, and Amazon [3][4]. - The company aims to create realistic 3D virtual spaces for brands and creators, allowing them to control content distribution and user engagement [6]. Financial Activities - In May 2025, Infinite Reality announced a name change to Napster Corporation to align its technology platform with the iconic music brand [6]. - The company has rapidly expanded through acquisitions, including a $350 million investment and the purchase of Landvault, raising its valuation to approximately $51 billion [8]. - A significant acquisition was made in early 2025 when Infinite Reality bought AI company Touchcast for about $500 million to enhance its AI capabilities [8]. Valuation Concerns - Infinite Reality's reported valuation of $155 billion is based on projected revenues of $75 million for 2024, resulting in a valuation-to-revenue ratio of 200 times, which is significantly higher than other AI startups like Anthropic and OpenAI [9][11]. - The company's revenue primarily stems from acquisitions made since 2022, raising questions about the core business's actual value [11]. Investor Relations and Controversies - The $30 billion investment from an anonymous source has raised skepticism, with experts suggesting it could be one of the year's biggest venture capital risks [13]. - Acunto's educational background has come under scrutiny, with claims of degrees from prestigious universities being unverified [14]. - Recent communications indicated that the previously announced $3.36 billion investment may never materialize, shocking investors and leading to a cancellation of stock buyback plans [19][21]. Market Dynamics - The startup's rapid rise contrasts with a decline in venture capital interest in metaverse companies, attributed to Meta's struggles in the space [16]. - Notable industry figures have expressed confusion over Infinite Reality's high valuation, indicating a lack of recognition and collaboration within the sector [17][18]. Regulatory Scrutiny - The SEC and DOJ are investigating the circumstances surrounding the company's financing and potential misconduct, with the SEC's inquiry expanding beyond initial concerns [22][23].

传统推荐架构正成为技术与业务演进的瓶颈。从最早的规则引擎到线性模型，再到深度学习进入推荐、行为序列建模，每一次技术跃迁都伴随着可 用算力的数量级提升。以 FM 到基于行为序列的精排模型为例，单个推荐 item 的计算量大约提升了 5 个数量级，同时带来显著效果增益。然而， 近两年 LLM 突飞猛进，推荐领域却更多停留在精排等局部环节的微调上，整体创新进入瓶颈。如果我们仍将迭代重心局限于排序模块、围绕单点 模型做细节优化，要获得数量级的提升将愈发困难。 能否直接借用 LLM 的技术栈与算力方案，重构一套端到端的推荐系统？ 直接采用 LLM 架构来做推荐的想法，看似美好，但深入思考并不简单，根本原因在于 LLM 与推荐的在线服务场景差异巨大。推荐是典型的低延 迟、高并发服务，需要实时响应海量请求；而在 Chatbot 等场景中，用户可以接受更长的等待时间，请求量也与推荐系统不在同一量级。 因此，当被询问"能不能用 LLM 来做推荐"时，团队往往会给出"想法很好但不现实"的反馈，常见理由有三点：其一，推荐模型本身已经很大。若将 用于表示物料 ID 的稀疏 Embedding 计算在内，推荐模型规模已达 T 级（万亿 ...

Core Insights - DeepSeek has released a new mathematics reasoning model, DeepSeek-Math-V2, with 685 billion parameters, which is the first open-source model to reach the gold medal level of the International Mathematical Olympiad (IMO) [2][9] - The model outperforms its predecessor, DeepSeek-Math-7B, which had only 7 billion parameters and was comparable to GPT-4 and Gemini-Ultra [4] - The model's performance in the IMO-ProofBench benchmark shows it scored nearly 99% in the Basic subset, surpassing Gemini DeepThink's 89%, while in the Advanced subset, it scored 61.9%, slightly below Gemini DeepThink's 65.7% [5][9] Performance Metrics - In real competition problems, DeepSeek-Math-V2 achieved gold medal levels in IMO 2025 and CMO 2024, and scored 118 out of 120 in Putnam 2024, demonstrating strong theorem proving capabilities [7][8] - The model's performance in specific contests includes 83.3% in IMO 2025 and 73.8% in CMO 2024 [8] Technical Advancements - The accompanying technical paper highlights significant breakthroughs in mathematical reasoning rigor, theorem proving capabilities, and surpassing some benchmarks set by Google's Gemini DeepThink [9][12] - A key innovation of DeepSeek-Math-V2 is its self-verification mechanism, allowing the model to check its reasoning chain for completeness and logical consistency, which is crucial for mathematical tasks [13][16] Community Response - The open-source release has garnered strong reactions from developer communities, with many expressing surprise at the model's performance and potential future applications in programming [18][20] - Users have noted the importance of mathematical correctness in AI-generated code, indicating a demand for models that excel in mathematical reasoning [20][23] Industry Implications - The release of DeepSeek-Math-V2 is redefining the competitive landscape of large model mathematics reasoning research, with self-verification becoming a key technological pathway for the next generation of mathematical AI [25]

作者 ｜ 木子、高允毅 卢泽宇表示，入职小米后，希望可以"加速灵巧手技术路径收敛和工程化落地"，并公开招募"志同道合"的研发人员加入团队。 他也欢迎大家一起探讨与机器人相关的前沿技术，感兴趣的朋友可以通过本文文末的"传送门"去和他留言互动。 今年， 小米机器人团队 "集邮"似的招揽了各路顶尖人才。 这不， 前特斯拉 Optimus 灵巧手团队成员卢泽宇 ，最近也在社交平台公开了自己 加入小米机器人团队 的消息，接过 灵巧手负责人 这一要职。 在特斯拉工作的 2 年多时间内，他深度参与 Optimus 机器人的手部研发 ，包括触觉传感器开发、灵巧抓取与操作、手部结构设计等关键技术——工作 履历对口堪称完美。 另据领英信息，卢泽宇其实已经加入小米 2 个多月了，不过相关信息刚刚公开。 | 工作经历 | | | --- | --- | | Dexterous Hand R&D Lead והו | | | Xiaomi Technology · 全职 | | | 2025年10月 - 至今 · 2 个月 | | | 混合办公 | | | Robotics Engineer | | | Tesla · 全职 | | ...

Core Insights - Tencent's "Hunyuan 3D" has accelerated its global outreach by launching an international version of its creative engine and achieving over 3 million downloads of its open-source model, marking a significant step in its AI strategy [2][3][21] - Tencent's unique position as a technology company lies in its combination of massive 3D demand from various sectors, mature multi-modal capabilities of its Hunyuan model, and a comprehensive distribution network through WeChat, QQ, and Tencent Cloud [3][4] Group 1: Business and Technology Integration - The traditional 3D industry faces challenges of high costs and long production times, with art costs in game development often accounting for 50%-80% of total expenses, and 3D asset creation being the most resource-intensive [6][7] - Hunyuan 3D aims to address these issues by enhancing the efficiency of 3D asset production and solving scene-level construction problems through two main technical lines [8][9] - The integration of Hunyuan 3D into Tencent's internal game projects has shown promising results, significantly reducing the time required to create 3D assets from days to mere hours [12][14] Group 2: Market Applications and Expansion - Hunyuan 3D's applications extend beyond gaming, with over 150 companies across various industries, including e-commerce, film, advertising, and 3D printing, utilizing its models to enhance production efficiency [25][27] - The technology has enabled a shift in consumer 3D printing, allowing users to generate personalized models with minimal expertise, thus expanding the market [26] - In advertising and content creation, Hunyuan 3D is poised to transform how brands engage with consumers by moving from static displays to interactive experiences [27][29] Group 3: Strategic Vision and Competitive Edge - Tencent's AI strategy focuses on building ecological barriers rather than merely scaling operations, emphasizing quality, controllability, and cost-effectiveness as foundational capabilities [31][32] - The company has achieved recognition for its Hunyuan image model, which topped global rankings, indicating its leadership in multi-modal technology [31] - Tencent's approach to 3D generation is characterized by a commitment to understanding industry pain points and fostering an ecosystem that supports sustainable growth [39][40]