温馨提示 ： 点击下方图片，查看运营团队2025年最新原创报告（共210页） 说明： 欢迎约稿、刊例合作、行业人士交流 ， 行业交流记得先加入 "机器人头条"知识星球 ，后添加（ 微信号：lietou100w ） 微信； 若有侵权、改稿请联系编辑运营（微信：li_sir_2020）； 正文： 摩根士丹利分别于2025年2月初和4月底各发布一份人形机器人研报，两份报告解读，小编早已有发布，今天在往 期基础上，将两份研报结合，聊一些其他内容 （全球头部人形机器人公司及趋势、核心供应链公司及投资分析、 最佳商业化模式及核心壁垒）。 2月初， 大 摩研报： Humanoid 1 00（人形机器人100：全球人形机器人产业链梳理） ； 报告围绕Humanoid 100清单 （包含82家已参与人形机器人领域的公司和18家被认为有潜力参与的公司） 展开， 按"大脑 （Brain）"、"身体（Body）"和"集成商（Integrators）"三个类别 详细梳理了人形机器人核心供应链上市公 司，为读者提供更精准的投资建议（股票玩家必看）。 4月底， 大 摩研报： Humanoid：A $5 Trillion Global Ma ...

Core Viewpoint - The speech by Jensen Huang, CEO of NVIDIA, at COMPUTEX 2025 emphasized the emergence of humanoid robots as a pivotal technology in the AI era, predicting it to become a multi-trillion-dollar industry due to its versatility and scalability [1][2][3]. Group 1: Humanoid Robots - Humanoid robots are deemed the only successful robot style capable of being deployed in various environments, including contaminated areas, thus integrating into human-created spaces [2][3]. - The technology behind humanoid robots is expected to evolve rapidly, requiring significant computational resources for AI learning, simulation, and real-world deployment [2][3]. - Elon Musk predicts that the number of humanoid robots could eventually reach hundreds of billions, indicating a massive market potential [5]. Group 2: Industry Dynamics - Major players in the humanoid robot sector include NVIDIA and Tesla, with Tesla's Optimus robot being a benchmark in the industry [3][6]. - The humanoid robot market is projected to reach a value of $5 trillion, with original equipment manufacturers (OEMs) like Tesla holding the highest value in the core value chain [8]. - The entry of automotive manufacturers and tech giants into the humanoid robot space has shifted the landscape, with 15 notable car companies, including 11 from China, now participating [8]. Group 3: NVIDIA's Strategy - NVIDIA's strategy focuses on building a foundational ecosystem for humanoid robots through its chipsets and middleware, positioning itself as a leading "shovel seller" in the AI era [3][10]. - The company has made significant advancements in robotics since 2018, launching various platforms and tools to support the development of intelligent robots [12][13]. - NVIDIA's recent initiatives include the introduction of the GR00T N1 humanoid model and partnerships with companies like Google DeepMind and Disney to enhance its robotics platform [15][17].

Core Viewpoint - Beijing Qianjue Technology Co., Ltd. has successfully completed a Pre-A+ financing round, indicating strong investor confidence in the company and its technology development in embodied intelligence models [1][2]. Financing History - The company has completed multiple financing rounds, including a Pre-A round in March 2025 and a Pre-A+ round in May 2025, with total financing amounting to hundreds of millions [2][3]. - The latest round was led by Junshan Investment, Xiangfeng Investment, and Shixi Capital, aimed at enhancing core technology, product standardization, and industrial delivery capabilities [1][2]. Company Overview - Qianjue Technology, established in June 2023, focuses on applying "brain-like" technology to robotics for perception, decision-making, and control, aiming to develop a universal robot model capable of cross-form, cross-environment, and cross-task deployment [3][4]. Core Team and Expertise - The core team consists of scholars from Tsinghua University, specializing in reinforcement learning, robotic learning control, and multi-task generalization [9][10]. - The founder and CEO, Dr. Gao Haichuan, has a background in developing autonomous decision-making robots, while the chief technical advisor, Professor Chen Feng, is a pioneer in brain science research in China [11][12]. Technological Advantages - The company leverages support from Tsinghua University's Brain Center and VIPLAB, focusing on embodied perception and decision-making capabilities [12]. - Qianjue Technology is positioned as the only domestic company comparable to Physical Intelligence (PI), having achieved significant advancements in long-term task execution capabilities [12][15]. Product Development and Commercialization - In April 2024, the company launched a product-level robot perception and decision-making model, which has been implemented in various scenarios, including home, commercial, and industrial services [15][16]. - The company has developed a unique product-level robot model that can autonomously operate and adapt to environmental changes, emphasizing the importance of AI capabilities in the humanoid robot market [16][20]. Market Context - The global landscape for embodied intelligence models includes notable competitors like Physical Intelligence and Skild AI, with Qianjue Technology aiming to establish itself as a leader in this emerging field [15][21]. - Major tech companies, including Google and OpenAI, are increasingly investing in humanoid robot manufacturing, indicating a shift in focus towards practical applications of AI and robotics [21][22].

Core Viewpoints - Embodied intelligence is injecting new research vitality into the robotics field and has the potential to break through performance limits [1] - The development of embodied intelligence relies on breakthroughs in specific scientific problems and should not dismiss contributions from traditional robotics [2] - General intelligence cannot exist without a focus on specific tasks, as expertise in particular areas leads to advancements in broader capabilities [3] Group 1: Interdisciplinary Collaboration - Embodied intelligence is a cross-disciplinary product that requires collaboration with fields such as material science, biomechanics, and design aesthetics [2] - Breakthroughs often occur at the intersection of disciplines, highlighting the importance of diverse scientific contributions [2] Group 2: Technology Evolution - Technological evolution should not be viewed as a complete replacement of old systems; rather, it is a process of sedimentation where foundational technologies continue to support advancements [5] - The current trend in visual-language-action models may soon be replaced by more efficient alternatives, emphasizing the need for continuous innovation [5] Group 3: Realistic Expectations for AGI - Viewing embodied intelligence as the sole path to artificial general intelligence (AGI) is a dangerous oversimplification; AGI development requires a multitude of conditions and interdisciplinary knowledge [6] - The complexity of embodied systems necessitates a collaborative approach across various fields, rather than relying on a few "genius" individuals [6] Group 4: Current State of Embodied Intelligence - The field of embodied intelligence is still in its early stages, with significant challenges remaining in hardware and algorithm development [7] - Current human-like robots are not yet fully autonomous and often require human intervention, indicating that the technology is still evolving [7] Group 5: VLA Technology Pathway - The development of visual-language-action (VLA) models may not be the most efficient approach, as operational skills often precede language capabilities in learning processes [9] - Many current VLA models are resource-intensive and may be replaced by more efficient solutions in the future [9] Group 6: Balancing Short-term and Long-term Goals - A combination of learning and modeling approaches is seen as more practical in the short term, while pure learning methods may represent the long-term future of robotics [10] - Successful robotic solutions in industry often rely on model-based methods due to their stability and reliability [10] Group 7: Human-like Robots and Practicality - The design of human-like robots is driven by emotional projection and environmental adaptability, but specialized non-human forms may offer better efficiency in many applications [11] - There is a concern about over-investment in human-like robots at the expense of practical and economically viable solutions [11] Group 8: Building Technical Barriers - True competitive advantages in technology arise from extensive practical experience and meticulous attention to detail, rather than solely from innovative algorithms [12] - Long-term technical barriers are built through consistent effort and iterative improvements in engineering practices [12] Group 9: Vision and Practicality - Scientific research requires both grand visions and grounded practices, with embodied intelligence embodying both idealistic aspirations and real-world challenges [13] - The importance of foundational theories, such as control theory, remains critical in ensuring the safety and functionality of robotic systems [13]

温馨提示 ： 点击下方图片，查看运营团队2025年最新原创报告（共210页） 说明： 欢迎约稿、刊例合作、行业人士交流 ， 行业交流记得先加入 "机器人头条"知识星球 ，后添加（ 微信号：lietou100w ） 微信； 若有侵权、改稿请联系编辑运营（微信：li_sir_2020）； 正文： 人工智能、大模型技术突破性进展催生了本身具身智能浪潮，但同时大模型发展瓶颈也同样是人形机器人商业化 核心壁垒；相较于上游机器人核心零部件基本成熟，软件算法（具身智能大模型）进步将是推动人形机器人功能 提升和应用场景拓展的关键。 近日，摩根士丹利发布最新人形机器人研报 「摩根士丹利」最新人形机器人研报：5万亿美元全球市场和最佳商 业模式解读（附报告 ） 中指出，在人形机器人核心价值链中，拥有机器人大脑、身体、品牌和生态系统的集成 类人形机器人原始设备制造商（OEM）具备最高价值（如特斯拉等）；其次是 具备独立大型机器人模型开发者 具备第二高价值； 并做出解释，机器人大模型(如：视觉-语言-动作(VLA)模型)是人形机器人的最有价值部分，决 定了机器人的泛化水平；同时数据是当前模型的关键瓶颈，规模是模型玩家获胜的唯一决定性因 ...

Core Viewpoint - The article discusses the recent developments and challenges faced by Yushu Technology, a leading humanoid robot company in China, highlighting the disparity between impressive demonstrations and actual commercial viability [1][10][14]. Group 1: Company Developments - Yushu Technology's humanoid robots gained significant attention after their performance at the Spring Festival Gala in 2025, showcasing their advanced movement capabilities [3]. - The company has faced backlash following founder Wang Xingxing's controversial statements about the potential of humanoid robots, which were met with skepticism from the public and media [1][11]. - Despite initial success, Yushu Technology is experiencing a backlash as real-world evaluations of their robots reveal limitations, leading to a decline in public perception [11][14]. Group 2: Market Dynamics - The humanoid robot market is characterized by a "show-off" cycle, where companies focus on impressive demonstrations rather than practical applications, leading to a temporary surge in interest but potential long-term sustainability issues [10][14]. - Yushu Technology and other similar companies have seen a spike in demand for robot rentals, with rental prices significantly exceeding purchase prices, indicating a strong market interest [10][11]. - The capital market has shown enthusiasm for Yushu Technology, with original shares becoming scarce and stock prices of related companies rising sharply [8][10]. Group 3: Industry Challenges - The article highlights a fundamental issue in the humanoid robot industry: the gap between technical capabilities and actual market needs, with many robots being unable to perform meaningful tasks despite their impressive physical abilities [17][14]. - The focus on entertainment and demonstration rather than practical applications has led to questions about the long-term viability of these companies, as they struggle to create sustainable business models [15][14]. - Industry experts emphasize the need for breakthroughs in the "brain" technology of humanoid robots to achieve true commercial viability, rather than relying solely on physical performance [17][14].

温馨提示 ： 点击下方图片，查看运营团队2025年最新原创报告（共210页） 说明： 欢迎约稿、刊例合作、行业人士交流 ， 行业交流记得先加入 "机器人头条"知识星球 ，后添加（ 微信号：lietou100w ） 微信； 若有侵权、改稿请联系编辑运营（微信：li_sir_2020）； 正文： 目前国内已有很多家人形机器人本体企业已宣布完成交付或者即将百台交付，如优必选、乐聚机器人、宇树科 技、 傅利叶、魔法原子、众擎机器人、松延动力、零次方 等等；星动纪元、星尘智能等多家公司都开启产 品预 售；但深究交付或者预交付场景，绝大多数创企以教育、科研、数据采集场景为主，其次是展示、表演场景； [ 魔法原子]则是将工业场景作为率先落地场景典型代表企业之一 。 小编往期文章： 【原创】ToB、ToC or ToG，全球人形机器人产品优选落地场景梳理 有提到人形机器人落地场景 包括 ToB、ToC 和ToG（科研场景），市场规模上ToC>ToB>>ToG； 其实，人形机器人创企 将教育、科研场景 作为主攻赛道，其次是展示、表演场景，而非工业场景，人形机器人本体公司更像是硬件卖铲人，这也国内人形 机器人赛道乱象之一；因为 ...

温馨提示 ： 点击下方图片，查看运营团队2025年最新原创报告（共210页） 说明： 欢迎约稿、刊例合作、行业人士交流 ， 行业交流记得先加入 "机器人头条"知识星球 ，后添加（ 微信号：lietou100w ） 微信； 若有侵权、改稿请联系编辑运营（微信：li_sir_2020）； 正文： 摩根士丹利分别于2025年2月初和4月底各发布一份人形机器人研报，两份报告解读，小编早已有发布，今天在往 期基础上，将两份研报结合，聊一些其他内容 （全球头部人形机器人公司及趋势、核心供应链公司及投资分析、 最佳商业化模式及核心壁垒）。 2月初， 大 摩研报： Humanoid 1 00（人形机器人100：全球人形机器人产业链梳理） ； 报告围绕Humanoid 100清单 （包含82家已参与人形机器人领域的公司和18家被认为有潜力参与的公司） 展开， 按"大脑 （Brain）"、"身体（Body）"和"集成商（Integrators）"三个类别 详细梳理了人形机器人核心供应链上市公 司，为读者提供更精准的投资建议（股票玩家必看）。 —— | | | General | | | | Trading Data | | | ...

Core Viewpoint - The article discusses the launch of the Alpha Brain and AlphaBot 2 by the company Zhi Ping Fang, highlighting advancements in embodied intelligence and the integration of DeepSeek technology into their VLA model [1][3][7]. Summary by Sections Product Launch - Zhi Ping Fang introduced the Alpha Brain, a fully self-developed global and omni-body VLA model, and the new generation bionic robot AlphaBot 2, showcasing capabilities in efficient interaction and autonomous action across various environments [1][3]. Technology Overview - The GOVLA model consists of a spatial interaction base model, a slow system for complex reasoning, and a fast system for real-time actions, enhancing the robot's ability to understand and execute long-range complex tasks [5][12]. - The integration of DeepSeek technology into the VLA model significantly improves reasoning capabilities, allowing for better task understanding and analysis [5][7]. Market Position - Zhi Ping Fang is positioned as a leading player in the embodied intelligence sector, being one of the first companies to systematically develop end-to-end VLA models, achieving commercial success ahead of competitors [14][22]. - The company has signed contracts with several top-tier domestic and international automotive and high-end manufacturing companies, aiming for significant revenue growth in the coming years [20][24]. Business Development - The company has set ambitious commercialization goals, including achieving a production scale of 10,000 units by 2028 and contributing to a revenue target of 10 billion by 2030 [20][22]. - Recent funding rounds have attracted significant investment, indicating strong market interest and confidence in the company's technology and business model [25]. Industry Trends - The article notes a trend of automotive industry professionals transitioning into the embodied intelligence sector, leading to increased competition and innovation within the field [22][23]. - The embodied intelligence market is becoming crowded with companies from the automotive and autonomous driving sectors, indicating a shift towards more integrated approaches in robotics [23][24].

Core Insights - The article discusses the rapid rise and subsequent challenges faced by humanoid robot companies, particularly focusing on Yushu Technology and Songyan Power, highlighting their market performance and public perception [1][10][24]. Group 1: Yushu Technology - Yushu Technology's humanoid robot H1 gained significant attention after its appearance on the Spring Festival Gala in 2025, followed by the G1 robot showcasing impressive athletic abilities, leading to increased interest in the capital and talent markets [1]. - The rental market for humanoid robots has seen a surge, with the G1 robot renting for 15,000 yuan per day, leading to quick returns for early adopters [6]. - However, Yushu Technology faces a trust crisis due to negative reviews revealing limitations in the G1's capabilities, which has led to a cooling off in the rental market [7]. Group 2: Songyan Power - Songyan Power emerged as a competitor with its humanoid robot N2, which performed well in a recent marathon, leading to a surge in orders and interest from investors [10][14]. - The company has received over 700 orders for the N2 robot, with a target of reaching 1,000 units sold this year [14]. - Songyan Power's strategy includes a focus on B2B markets, aiming for sustainable cash flow before expanding to consumer markets [23]. Group 3: Market Dynamics - The article highlights a trend where the novelty of humanoid robots attracts initial interest but may not sustain long-term demand, as seen with Yushu Technology's G1 [7][24]. - The commercialization of humanoid robots remains unclear, with many companies focusing on performance rather than creating lasting value for customers [24][25]. - The industry faces challenges in balancing technological advancements with practical applications, as many companies lack the necessary AI capabilities to enhance their products beyond mere physical performance [26][27].