Ryan Beiermeister, who served as OpenAI’s vice president of product policy, was fired in January after a male colleague accused her of sexual discrimination, the Wall Street Journal has reported. “The allegation that I discriminated against anyone is absolutely false,” Beiermeister told the Journal. TechCrunch reached out to OpenAI for comment and contacted an email that appears to be associated with Beiermeister; neither had responded at the time of publication. Per the Journal’s report, Beiermeister ...

Group 1 - Runway, a US-based AI video generation startup, completed a $315 million Series E funding round, achieving a valuation of approximately $5.3 billion, nearly doubling its previous round valuation [2] - The funding round was led by General Atlantic, with participation from notable investors including NVIDIA, Adobe Ventures, and Fidelity Management & Research Company [2] - Runway plans to use the funds to accelerate the pre-training and productization of its next-generation "world models," which are AI systems capable of understanding, predicting, and planning future events [2] Group 2 - Runway launched its world model in December 2025 and recently introduced the Gen 4.5 video generation model, which supports high-resolution video generation driven by text and includes advanced features [3] - The company's technology strategy indicates an expansion from traditional media and advertising into broader applications such as gaming and robotics, supported by a partnership with CoreWeave for computational resources [3] - The financing reflects strong market confidence in Runway's technological capabilities and the strategic value of AI world models as a core technology for the next generation of AI [3] Group 3 - From an industry perspective, Runway's advancements represent a trend towards higher levels of intelligence in generative AI, with world models enabling a shift from passive responses to proactive planning [4] - The global AI-generated content market is projected to reach hundreds of billions of dollars by 2026, with the maturation of world model technology expected to catalyze market growth [4] - Runway's increased funding and valuation demonstrate investor confidence in its technological leadership and commercialization potential [4] Group 4 - Looking ahead, if Runway can continue to optimize the generalization capabilities of its world models and multi-modal integration technologies, it will be well-positioned in AI application innovation [5] - The decline in computational costs and breakthroughs in algorithms suggest that world models could become the core engine for intelligent systems, driving advancements in autonomous driving, smart manufacturing, and virtual reality [5] - Runway's success may inspire more startups and capital to invest in AI foundational models and application ecosystems, fostering healthy competition and collaborative development within the industry [5]

Core Viewpoint - The establishment of the global AI application scenario center LuckyMate.AI in Huaqiangbei, Shenzhen, aims to create a sustainable "Shenzhen model" for AI applications, facilitating real transactions and industry transformation [1][2][3]. Group 1: Center Overview - The center adopts an innovative collaborative mechanism involving government guidance, professional enterprise operation, and ecosystem partner co-creation, focusing on opening AI application scenarios [2]. - The center is positioned as a landmark for AI technology display, industry connection, and urban application, contributing to Shenzhen's goal of becoming a global AI pioneer city [2][3]. Group 2: Operational Model - The center features a "four-in-one" operational model that includes scenario opening, product experience, real-time sales, and industry connection, targeting high-frequency scenarios in daily life, work, creation, entertainment, and industrial applications [4]. - It aims to create a tangible, continuously iterating space for AI application validation and commercial transformation, attracting various AI hardware products [4]. Group 3: Product Launch - The center announced its first flagship product, the AI smart desktop companion "Luma," which leverages the world's first L4 intelligent body system "MasterAgent" to provide cultural experiences, emotional companionship, and life management services [4][5]. - "Luma" serves as a pioneer demonstration role for AI application scenarios, exploring the integration of "MasterAgent" into physical devices and providing a data foundation for the continuous evolution of intelligent capabilities [5].

Amendment No. 1 to As filed with the U.S. Securities and Exchange Commission on February 10, 2026. Registration No. 333-293008 UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 FORM S-1 REGISTRATION STATEMENT UNDER THE SECURITIES ACT OF 1933 Sky Acquisition Group (Exact name of registrant as specified in its charter) (State or other jurisdiction of incorporation or organization) 1160 Battery Street East, Suite 100 San Francisco, California, 94111 Telephone: (650) 785-7171 (Address, inc ...

Summary of Key Points Company and Industry Involved - The document discusses the AI industry, specifically focusing on a company named 智谱 (Zhipu) and its upcoming product, GLM-5 [1]. Core Insights and Arguments - A new anonymous AI model named "PonyAlpha" was launched on the global model service platform OpenRouter, generating significant interest and testing within the global developer community [1]. - The anticipation surrounding the release of the new generation model GLM-5 by 智谱 has positively influenced the AI sector in the Hong Kong stock market [1]. - On February 10, the AI sector in Hong Kong experienced a strong performance, with 智谱 continuing its upward trend from the previous day, reaching a total market capitalization of 146.5 billion HKD, and at one point approaching 150 billion HKD [1]. Other Important but Possibly Overlooked Content - The excitement around the GLM-5 model indicates a potential shift or advancement in AI technology that could impact market dynamics and investor sentiment [1].

Core Viewpoint - The article discusses the limitations of current multimodal large models in fine-grained visual recognition tasks and introduces the Fine-R1 model developed by Professor Peng Yuxin's team at Peking University, which significantly improves recognition accuracy with minimal training data [1][2][5]. Group 1: Fine-Grained Visual Recognition Challenges - Current multimodal large models excel in complex tasks but lag in fine-grained visual recognition compared to their visual encoders like CLIP [1]. - Real-world objects exhibit fine-grained characteristics, with numerous subclasses, such as over 500 types of fixed-wing aircraft, highlighting the importance of fine-grained recognition in practical applications [3]. Group 2: Fine-R1 Model Overview - The Fine-R1 model aims to leverage the rich knowledge of fine-grained subclasses and a generative decoding paradigm to overcome the limitations of traditional recognition methods, enabling fine-grained recognition of any visual object in an open domain [5]. - Fine-R1 enhances the model's ability to reason about unseen subclasses using a small number of training images (only 4 per subclass), outperforming models like OpenAI's CLIP and Google's DeepMind's SigLIP [5][15]. Group 3: Model Development Process - The development of Fine-R1 involves two main steps: 1. Chain-of-thought supervised fine-tuning, which simulates human reasoning to build inference capabilities [7]. 2. Triplet enhancement strategy optimization, which improves robustness to intra-class variations and inter-class distinctions by using positive and negative samples [8][10]. Group 4: Experimental Results - Fine-R1's performance was evaluated on six authoritative fine-grained image classification datasets, demonstrating superior accuracy in both seen and unseen categories compared to other models [15][17]. - The model's ability to utilize fine-grained subclass knowledge effectively was identified as the primary factor for its improved recognition accuracy, rather than enhancements in visual representation or knowledge storage [19]. Group 5: Conclusion and Future Work - The article concludes with the potential of Fine-R1 to excel in fine-grained visual recognition tasks, emphasizing its innovative approach to reasoning and knowledge application [21]. - The research has been accepted for ICLR 2026 and the code is open-sourced for further exploration [2][22].

字节，阿里等大厂聚焦安全性与可追溯性，阿里通过ACT协议强制要求支付环节必须通过支付宝完成，利用其成 熟支付协议保障链路安全，并通过交易日志记录实现全流程可追溯，便于问题回溯； 国家层面尚未出台针对AlAgent执行权限的具体法规或监管条文； 千问调研 AlAgent落地的潜在风险： 千问调研 AlAgent落地的潜在风险： 随着AlAgent从辅助决策向直接执行操作延伸国内企业及监管机构面临新风险，AI可能跳过用户确认直接决策，导 致意外后果； 千问海外市场拓展规划 虽未发布独立出海产品，但已完成多语言模型开发，接入海外产品并统一使用谷歌UCP协议整合 海外电商，本地生活，Uber等，中间层打 阿里 海外电商及支付产品； 目标市场优先选择东南亚，南美，阿里生 态布局 完善，份额大； 第三方：头部平台如亚马逊接入意愿弱，垂直领域如Uber及中腰部/尾部服务商合作意愿高，目前处于接触阶段； AI驱动电商模式GMV渗透率预期： 2026年AI驱动电商GMV占比预计1.5%-2%;2027-2028年渗透率加速提升，2027年达5%，2028年超15%-20%; -驱动因素：用户心智快速转变；产品迭代重点转向任务执 ...

IT之家 2 月 11 日消息，xAI 联合创始人吉米 · 巴（Jimmy Ba）表示，他已于当地时间周二离开埃隆 · 马斯克的这 家初创公司。 巴在 X 平台上写道："是时候重新校准我对大局的认知梯度了。2026 年将会非同寻常，很可能是关乎人类未来最 忙碌（也最具决定性）的一年。" 根据去年年初的一份组织架构图，巴此前还管理着一支负责超千名 AI 导师的团队，该职位已于去年 9 月交由迭 戈 · 帕西尼（Diego Pasini）接任。 巴是不到 48 小时内第二位离职的公司联合创始人，托尼 · 吴已于当地时间周一晚间宣布从这家 AI 初创公司辞 职。 在吴离职前，xAI 再次进行了架构调整，他的多项工作职权被划归至张国栋名下。 马斯克于 2023 年与其他 11 位创始人共同创立了这家 AI 公司。目前已有 6 人离开，其中 5 人是在过去一年内离 职。 除在 xAI 任职外，巴还是多伦多大学计算机科学系的助理教授。他在该校师从被誉为"AI 教父"的诺贝尔奖得主 杰弗里 · 辛顿（Geoffrey Hinton），并获得博士学位。 马斯克曾表示，他创立 xAI，是为了打造有别于他口中"觉醒派"聊天机器人 ...

贝默斯特被解雇 OpenAI CEO萨姆.奥特曼(Sam Altman)已为扩大平台允许内容范围的决定辩护，称此举是"将成年用户当 作成年人对待"的一部分。 据知情人士透露，在被解雇前，贝默斯特曾向同事表示她反对成人模式，并担忧该功能可能对用户产生 有害影响。她向同事指出，她认为OpenAI防止儿童剥削内容的机制不够有效，且公司无法充分阻隔青 少年接触成人内容。 知情人士称，她是OpenAI内部对推出成人模式表达担忧的多名员工之一。 贝默斯特对此发布声明称："对于我歧视他人的指控完全不实。" OpenAI发言人在一份声明中表示，贝默斯特"在任职期间做出了宝贵贡献，她的离职与她在公司工作期 间提出的任何问题无关"。 贝默斯特在2024年中加入OpenAI，担任OpenAI产品政策团队副总裁，该团队负责制定用户使用公司产 品的规则，并协助设计这些政策的执行机制。她被解雇发生在OpenAI计划于今年年初推出的成人模式 之前，该模式将允许用户在ChatGPT中创作AI成人内容。 据部分知情人士透露，这项计划中的功能将允许成人用户进行包含性话题在内的成人主题对话，但这一 计划已引发公司内部研究人员的批评，这些研究人员曾 ...

来源：独角兽早知道 合同助理。公司的合同助理解决方案透过支援合约审阅、建议潜在争议解决方法及精简法律文件模板的 生成流程，将商业合约工作流程数字化及自动化。 综合 | 招股书 编辑 | Arti 投资助理。公司的投资助理解决方案透过提供包括风险评估的全面投前报告、分析海量商业合同数据， 并生成投后报告追踪项目表现，从而简化投资生命周期。 品牌助理。公司的品牌助理解决方案透过对社交媒体及其他数字渠道进行实时多模态监测与分析，助力 消费品牌预测市场趋势及优化策略，从而帮助公司的客户实现营运转型、降低成本并发掘新的增长机 遇。 据招股书，第零智能是中国领先的企业AI智能体解决方案提供商。企业级AI智能体解决方案是指以大 语言模型(LLMs)及多智能体体系为核心基础，旨在透过为企业配置自动化AI智能体，以优化现有工作 流程、自动化复杂程序，并为决策提供辅助及支持的系统化解决方案。 公司致力于开发AI智能体解决方案，为客户提升效率、扩展性及精准度，根据弗若斯特沙利文，就 2024年的收益而言，第零智能已跃居中国企业级AI智能体解决方案第五大供应商，市场份额为3.0%。 第零智能的AI智能体解决方案由公司的专有AI平台B ...