Group 1 - ByteDance's Volcano Engine will be the exclusive AI cloud partner for the 2026 CCTV Spring Festival Gala, with its smart assistant Doubao providing various interactive features [1] - The Spring Festival Gala has become a highly sought-after IP among internet giants, initiating a new round of competition for traffic [1] - Previous collaborations include WeChat's partnership in 2015, which resulted in 11 billion interactions on New Year's Eve, and Douyin's exclusive partnership in 2019, generating 24.7 billion video views [1] Group 2 - AI has emerged as a new collaboration element for internet companies with the Spring Festival Gala, with Alibaba Cloud being the exclusive AI cloud partner in 2025, utilizing AI technology for innovative stage designs [2] - In 2024, Baidu partnered with CCTV for the Spring Festival Gala, introducing features like AI fireworks and AI costume transformations [2] Group 3 - Robotics also played a significant role in the Spring Festival Gala, with the Yuzhu robot gaining popularity through its performance in the 2025 gala, showcasing advanced capabilities [3] - Yuzhu Technology is reportedly participating in the sponsorship bidding for the Spring Festival Gala [4]

Group 1 - The company, Opcon Vision (300595.SZ), has invested in a fund that is developing an ophthalmic surgical robot, which is currently in the clinical trial phase [1] - The company has also invested in a fund that is developing a companion robot, which is in the prototype development and validation stage [1] - Both products have not yet been officially launched [1]

维他动力成立于2024年12月9日，老大是余轶南，曾任地平线副总裁及软件平台产品线总裁，两位联创是赵哲伦与 宋巍，前者曾任理想智能驾驶产品总监，并在i8发布会前理想官方放了挺长时间李想与哲伦一起体验VLA的视频； 后者曾任地平线软件平台总架构师及智驾创始团队成员。 2025年12月8日TOP2线下体验了7小时左右，并与维他动力的多位研发/产品经理进行了交流。顺带一提理想团队此 前也问了维他动力团队是如何理解具身智能。 分享8个点： 1.汽车以外的其他具身智能C端产品已经可以面向创新者/早期采用者提供有用的产品了。 2025年11月26日李想在25Q3电话会议上花了 14min46s讲对具身智能怎么看，理想打算怎么做。完整版详见《 理想25Q3电话会议文字版 》 2025年12月23日维他动力发布的机器狗是具身智能时代真的拉开序幕的侧面印证。 世界具身智能中心一定会在中国，背后依托是中国物理世界供应链的即时响应/各个维度的成熟度/人才丰富度，数 字世界同样的即使响应/各个维度的成熟度/人才丰富度。这样的时势，必然会诞生多位具身智能杰出人物，中国人 一定会在其中占据超高比例。 只有中国才有机会在此时此刻发布一款9 ...

Group 1 - The robotics sector experienced fluctuations today, with funds strategically positioning themselves, as evidenced by the net subscription of 31 million units of the Penghua Robotics ETF (159278) [1] - The "Qing Tian Rent" robot leasing platform was officially launched at the National Robot Leasing Ecological Summit held in Shanghai on December 22, aiming to integrate the industry chain and create a nationwide open leasing network [1] - Guojin Securities highlighted that the supply chains of Tesla, Zhiyuan, and Huawei should be closely monitored in H2 2025, with Tesla's supply chain expected to resume operations after a brief pause, focusing on various components such as tactile sensors and high-power density motors [1] Group 2 - As of November 28, 2025, the Guozheng Robotics Industry Index (980022) reflects the price changes of listed companies related to the robotics industry, with the top ten weighted stocks accounting for 40.47% of the index [2] - The top ten weighted stocks in the Guozheng Robotics Industry Index include companies like Shuanghuan Transmission (002472) and Ecovacs (603486) [2] - The Penghua Robotics ETF (159278) closely tracks the Guozheng Robotics Industry Index, providing investors with exposure to the performance of the robotics sector [3]

引言 过去一年，具身智能成为机器人产业最热的关键词之一。人形机器人、服务机器人、特种机器人密集发布，但 一个现实问题也越来越清晰地浮出水面： ▍ 从 " 卖机器人 " 到 " 卖大脑 " ：产业逻辑正在发生变化 智能能力深度绑定硬件 算法围绕单一场景优化 产品更新依赖重新设计整套系统 机器人看起来更 " 聪明 " 了，但离真正的自主智能，仍然存在结构性差距。 近日， Robo Summit 机器人发展论坛（第二期）暨首届朝阳智能机器人生态大会在北京朝阳举办。千诀科 技创始人兼 CEO 高海川受邀发表主题演讲，并与银河通用创始人兼 CTO 王鹤、智平方副总裁邱巍等嘉宾共 同启动 " 朝阳区智能机器人生态伙伴建设计划 " ，围绕具身智能的技术演进与产业协同展开深入探讨。 在演讲中，千诀科技创始人兼 CEO 高海川分享了一个颇具产业争议的判断 —— 机器人智能的下一阶段竞争，不在"哪种形态跑得更像人"，而在"机器人大脑是否真正独立、通用、可演 化"。 这一判断，正在重新划分机器人产业的技术路线。 长期以来，机器人产业的主流商业模式是 整机驱动 ： 但随着应用场景快速扩张，这种模式的边界越来越明显： 每进入一个新行业 ...

Core Insights - The article discusses the integration of Large Language Models (LLMs) with Behavior Trees (BT) to enhance robotic task execution and adaptability in the presence of external disturbances [1][2][12]. Group 1: LLM and BT Integration - LLMs are utilized to interpret user commands into behavior trees that include task goal conditions [2]. - The combination of LLMs and BT allows for fewer calls to LLMs while managing external disturbances through an action database [2][12]. - A human-in-the-loop learning mechanism is proposed to refine the knowledge generated by LLMs, ensuring safety and adaptability in robotic operations [5][7]. Group 2: Human-in-the-Loop Learning Mechanism - The mechanism involves designing a context for LLMs that includes prompt engineering, manipulation primitives (MPs), and an action database [5]. - User interactions guide LLMs to correct and enhance the generated action knowledge, which is then added to the action database after user confirmation [7][12]. - The generated action knowledge consists of preconditions, postconditions, and a set of MPs, implemented in BT format [7]. Group 3: Task Evaluation and Performance - Eight tasks were designed to evaluate the proposed method, categorized into three difficulty levels: Easy, Medium, and Hard [9]. - The proposed method achieved a success rate of over 80% across the tasks, significantly outperforming baseline methods that lacked human interaction [12]. - The adaptability of the generated action knowledge was tested against external disturbances, achieving a success rate exceeding 70% [14]. Group 4: Generalization and Future Improvements - The generated action knowledge demonstrated good generalization capabilities, with success rates over 70% for certain tasks involving new objects [17]. - However, some tasks had success rates below 40% due to the inapplicability of MPs parameters to new objects, indicating a need for fine-tuning before application [17]. - Overall, the proposed human-in-the-loop learning mechanism enhances robotic learning performance, enabling robots to complete tasks and respond to external disturbances effectively [18].

Core Viewpoint - The article discusses the launch of the robot rental platform "Qingtian Rent," which aims to create a new era in the robot rental industry by establishing a value co-creation and sharing mechanism, facilitating the accessibility of humanoid robots to the public [2][4]. Summary by Sections Platform Overview - "Qingtian Rent" integrates users, rental companies, content developers, and equipment manufacturers to enhance the overall value of the robot rental industry, defining a new era of RaaS (Robot as a Service) [4]. - The platform's core innovation is transforming high-threshold robot usage scenarios into a convenient rental model, similar to shared power banks, addressing industry pain points such as high operational costs and complex collaboration [4]. Strategic Goals - The "1234 Strategic Plan" aims to achieve partnerships with over 10 manufacturers, 200 premium service rental companies, 3,000 content creators, and 400,000 rental customers by 2026 [4]. - The ultimate belief is to leverage intelligent machines to create unlimited productivity, making efficient and flexible robot services permeate various industries [4]. Market Potential - The robot rental market has surpassed 1 billion yuan this year, with expectations to reach at least 10 billion yuan next year as manufacturers ramp up production and market demand increases [9][10]. - The anticipated growth is driven by the transition from novelty use to regular, scalable applications, similar to the evolution of ride-hailing services [10]. Usage Scenarios - The platform supports 13 major usage scenarios, including corporate events, exhibitions, retail promotions, and community security, indicating a broad potential for robot applications [11]. Open Platform Approach - "Qingtian Rent" is an open and inclusive platform, welcoming all robot manufacturers to join, regardless of their production capabilities, to match market demand with service providers [12]. Pricing Strategy - The platform aims to establish a competitive pricing system that satisfies both clients and rental service providers, ensuring it remains the most cost-effective robot rental platform nationwide [14].

企查查APP显示，近日，浙江创极星机器人有限公司成立，注册资本5000万元，经营范围包含：服务消 费机器人制造；服务消费机器人销售；工业机器人制造；智能机器人的研发等。企查查股权穿透显示， 该公司由宁波方正全资持股。 ...

Core Viewpoint - The article introduces the ManualVLA model, a unified VLA model designed to enhance robotic manipulation and task execution by integrating planning and action generation into a single framework, addressing challenges in long-duration tasks that require precise final state definitions [2][5][10]. Group 1: Research Background and Challenges - Recent advancements in VLA models have significantly improved robotic scene understanding and generalization, yet challenges remain in coordinating high-level planning with precise operations for long-duration tasks like LEGO assembly and object rearrangement [7]. - Two main challenges are identified: the need for precise operations to align with predefined final configurations and the integration of long-term planning with fine-grained control while maintaining generalization capabilities in diverse real-world environments [7][9]. Group 2: ManualVLA Method Description - ManualVLA allows the model to generate its own instruction manual and execute actions based on it, breaking down complex long-duration tasks into controllable and interpretable short phases [12][19]. - The model employs a Mixture-of-Transformers (MoT) architecture, integrating a planning expert that generates multimodal operation manuals and an action expert that executes the actions based on these manuals [5][15]. - The ManualCoT reasoning mechanism combines explicit and implicit paths to influence action generation, ensuring a high degree of coordination between manual generation and action execution [16][20]. Group 3: Experimental Results - In real-world tasks, ManualVLA demonstrated a significant improvement in success rates, achieving an average success rate increase of approximately 32% compared to the latest baseline methods [28]. - The model's performance in generating intermediate target images was validated with metrics such as PSNR (e.g., 2D LEGO assembly at 29.01) and MAE (e.g., 2D LEGO assembly at 3.23), indicating high fidelity and accuracy in predicting target object positions [23][27]. - ManualVLA outperformed state-of-the-art methods in simulation tasks, achieving a 70% average success rate, surpassing the previous best of 63% [31]. Group 4: Ablation and Generalization Experiments - Ablation studies confirmed that all modalities of information in the instruction manual (text, images, UV coordinates) and the implicit CoT reasoning are essential for solving long-duration, goal-specific operational tasks [33]. - ManualVLA exhibited robust generalization capabilities under varying backgrounds, object shapes, and lighting conditions, maintaining high task success rates even in unseen scenarios [36].

Tesla Trade - Ark Invest sold 60,715 shares of Tesla across multiple ETFs, with a total transaction value of approximately $29.7 million, as the stock closed at $488.73 [2] - Concerns regarding Tesla's financial prospects were raised by Gerber Kawasaki, particularly about achieving GAAP profitability, although the company's market share in the EV sector remains strong [3] Palantir Trade - Ark Invest reduced its position in Palantir by selling 47,309 shares, valued at approximately $9.2 million, with the stock closing at $193.98 [4] - BofA Securities expressed optimism about Palantir's growth, citing strong momentum in its U.S. commercial business and a recent two-year $448 million government order [5] Shopify Trade - Ark Invest sold 33,164 shares of Shopify, valued at approximately $5.6 million, with a closing price of $169.67 [6] - Shopify's recent Winter 2026 Edition showcased expanded capabilities in AI and merchant tools, reinforcing confidence in its long-term growth according to JPMorgan [7] WeRide Trade - Ark Invest purchased 520,697 shares of WeRide, valued at approximately $4.7 million, with the stock closing at $8.97 [8] - WeRide launched public Robotaxi rides in Dubai, marking progress towards a fully driverless rollout planned for early 2026 [9] Other Key Trades - Ark Invest acquired 78,793 shares of CRISPR Therapeutics across ARKG and ARKK [10] - Intellia Therapeutics saw an acquisition of 187,880 shares via ARKG and ARKK, while Rocket Lab sold 232,425 shares through ARKQ and ARKX [12]