梦晨 发自 凹非寺 量子位 | 公众号 QbitAI 那么他们靠什么吸引到巨额投资？ 答案或许就在团队去年底开源的 Genesis物理引擎 中，一句话就能精准生成完整的物理世界，已成为GitHub上最大的开源机器人项目。 刚刚，一支华人主导的AI团队打破硅谷融资纪录。 这家名为 Genesis AI 的具身智能公司，在成立仅一个月后就完成了 1.05亿美元（约7.52亿元） 的种子轮融资，从两个角度创造了历史： 这是 硅谷历史上华人团队完成的最大规模种子轮 ，甚至超过了此前AI视频赛道Pika的5500万美元纪录。 也是 硅谷具身智能赛道最大的种子轮 ，超过明星团队Physical Intelligence（7000万美元）和Skild（1450万美元）。 更让人惊讶的是，这个脱胎于学术界的创始团队并非常见的资深教授带队创业模式，而是一群刚刚博士毕业的年轻AI及机器人科学家。 CEO周衔 ，刚刚从CMU获得机器人学博士学位。而整个 创始团队平均年龄不到28岁 。 大型语言模型需要用海量的文本数据来训练，机器人的AI模型则得基于物理世界的数据进行训练。不过，获取现实世界的数据既费钱又费时。 为了克服这个问题，G ...

人形机器人：技术迭代方向展望 - 2025 年中金公司中期 投资策略会 20250630 摘要 通用机器人需具备多地形适应性和灵巧操作能力，人形结构更适应人类 环境。操作能力是应用价值上限，硬件配置需与通用能力等级匹配。 训练通用机器人需算法、数据、硬件协同，通过采集数据建立观测与输 出的映射关系，实现广泛应用，但构建通用模型面临挑战。 触觉传感器对精细操作至关重要，高分辨率、多维度、高频率的触觉传 感器是机器人实现类似人类灵巧性的关键。 呆萌机器人光学式触觉传感器具有高分辨率（每平方厘米 4 万个点）， 可精准感知物体形貌及切向力，对温度不敏感但力敏感度极高。 呆萌推出以人为中心的数据采集设备，捕捉视觉、手部触觉及手臂运动， 更真实反映人类操作，提升视觉、触觉、语言及动作模型训练效果，成 功率从 50%提升到 80%以上。 引入触觉传感器可大幅降低机器人训练成本。达到 80%以上成功率，无 触觉传感器需约 5 万次数据采集，成本约 15 万元，而有触觉传感器只 需 100 次，成本仅 300 元。 推动机器人通用化落地需加强硬件（高质量触觉传感器、灵巧手）、数 据（以人为中心的数据采集）和算法（触觉良好表征 ...

投资机遇转瞬即逝，本周值得关注的十大投资交易已被 IT桔子锁定！ 屏蔽"互联网噪音"，专注重要信息。 编辑｜大王管不住嘴 豆包 来源｜IT桔子 封面｜公众号AI生成 1.非夕科技完成C轮亿级美元融资 非夕科技近日完成C 轮亿级美元融资，由咏归基金、广发信德联合领投，洪泰基金、华控基金等跟投， 老股东持续加码。资金将用于扩产、研发及生态拓展，重点推进自适应机器人在汽车制造、3C 电子等 领域的规模化落地。 6 月 23 日消息，见真机械完成超亿元 A 轮融资，投资方为国泰海通证券、苏创投等。 公司 2016 年成立于长春，是省级专精特新企业。专注航天器部件制造，从事光电仪器制造、卫星部件 装配等业务，凭借先进技术和严格质控体系，在行业内建立良好口碑，2024 年营收过亿元。 公司成立于 2016 年，总部位于上海，由斯坦福大学机器人实验室核心团队创立，首创「自适应机器 人」品类，以「仿人化」力控技术为核心，产品覆盖 7 轴串联机器人 Rizon 拂晓（负载 10kg）、3 轴并 联机器人 Moonlight 玄晖（重复定位精度 ±0.05mm）及穹知 AI 系统。其解决方案已服务广汽、理想、 谷歌等头部企业，2 ...

Core Viewpoint - Nvidia's stock surged 4.3% to a record high of $154.31, solidifying its position as the world's most valuable company with a market cap of approximately $3.77 trillion, surpassing Microsoft [1][2] Group 1: Financial Performance - Nvidia's revenue for Q1 of the fiscal year reached $44.06 billion, a 69% year-over-year increase; GAAP net profit was $18.78 billion, up 26%; Non-GAAP diluted earnings per share were $0.81, reflecting a 33% growth [7] Group 2: Strategic Initiatives - Nvidia is entering a "decade-long AI infrastructure construction cycle," with a focus on AI and robotics as major growth opportunities, representing a multi-trillion dollar market [4][6] - The company plans to release new AI chips annually to meet the increasing demand for model inference and training [5] - Nvidia is accelerating its efforts in sovereign AI and large-scale government collaborations to strengthen global infrastructure and mitigate the impact of export controls [7] Group 3: Market Position and Competition - Loop Capital predicts Nvidia's market value could reach $6 trillion, with analyst Ananda Baruah raising the target price from $175 to $250, the highest on Wall Street [3] - Despite facing challenges such as export restrictions to China and increasing competition from companies like AMD, Google, and Amazon, Nvidia maintains a strong position in high-end AI chip performance [9] - Nvidia's transition from a "chip company" to an "AI infrastructure platform provider" is deepening its ecosystem, which includes GPUs, CUDA platforms, software services, and data center support [8] Group 4: Robotics Focus - Nvidia is targeting the robotics sector, emphasizing the arrival of the "era of general-purpose robots," with ambitions extending to various types of robots, including agentic robots, autonomous vehicles, and humanoid robots [6]

Group 1 - The core viewpoint is that humanoid robot manufacturers are shifting their focus from ambitious universal solutions to more pragmatic, specialized applications, emphasizing the need for self-sustainability in their business models [1][4][25] - As of 2025, there is a noticeable trend where manufacturers are showcasing their capabilities through demonstrations rather than merely promoting the idea of widespread adoption [1][2] - The industry is recognizing that the pursuit of universal capabilities may hinder long-term development and immediate commercialization, leading to a more cautious approach [2][5][25] Group 2 - The current market for humanoid robots is still in its early stages, characterized by supply-driven dynamics rather than demand-driven, similar to the initial phase of smartphones [10][16] - There is a growing consensus that focusing on specific, well-defined applications may yield better commercial value than attempting to create a one-size-fits-all solution [8][11] - Companies are increasingly exploring partnerships and collaborations to enhance their technological capabilities and accelerate product development, moving away from isolated development efforts [21][23][25] Group 3 - The demand for practical applications of robots in logistics and other sectors is evident, with successful deployments validating the need for robotic solutions [7][10] - The industry is witnessing a trend where companies are diversifying their product offerings to include quadrupedal robots, which are perceived as more commercially viable and easier to develop [15][17][18] - The shift towards specialized robots, such as those designed for specific tasks in retail or hospitality, is proving to be a more effective strategy for companies looking to establish a foothold in the market [11][12][25]

2025年， 人形机器人 领域持续火热， "科幻走进现实" 的场景不断涌现。 4月，全球首场 人形机器人半程马拉松 鸣枪开跑，各具特色的机器人选手在真实世界的跑道上迈步；5月，在全球首个以人形机 器人为参赛主体的 格斗竞技赛事 中，机器人完成了勾拳、侧踢、闪避等一系列格斗动作；8月 ， 世界 人形机器人运动会 也将 拉开帷幕，设有田径、体操、足球等丰富多样的比赛项目。 一年前，我们在 《通往具身智能之路》报告 中提到，供应链成本效率优势的持续提升和第二、第三产业场景需求的快速增长， 或成为 具身智能赛道 的持续性机会。一年过去，具身智能赛道 发生了 哪些变化 ？ 涌现了 哪些 新的机会？ 在 「What's Next｜科技早知道」 的播客节目中，峰瑞资本执行董事 刘鹏琦 和「声动活泼」联合创始人&「科技早知道」主播 丁教Diane ，以及「科技早知道」节目监制 雅娴 ，围绕具身智能赛道所处的新阶段与核心挑战，探讨了以下问题，包括但不限 于： 当下这一波 具身智能热潮的起点 在哪？为什么都在 追求"人形"和"通用"？ 人形机器人的 软硬件发展 与哪些因素有关？目前面临哪些核心挑战？ 人形机器人的 商业化落地情况 ...

Core Viewpoint - Embodied intelligence is a key focus in the AI field, particularly in humanoid robots, raising questions about the best path to achieve true intelligence and the current challenges in data, computing power, and model architecture [2][5][36]. Group 1: Development Stages of Embodied Intelligence - The industry anticipates 2025 as a potential "year of embodied intelligence," with significant competition in multimodal and embodied intelligence sectors [5]. - NVIDIA's CEO Jensen Huang announced the arrival of the "general robot era," outlining four stages of AI development: Perception AI, Generative AI, Agentic AI, and Physical AI [5][36]. - Experts believe that while progress has been made, the journey towards true general intelligence is still ongoing, with many technical and practical challenges remaining [36][38]. Group 2: Transition from Autonomous Driving to Embodied Intelligence - Many researchers from the autonomous driving sector are transitioning to embodied intelligence due to the overlapping technologies and skills required [17][22]. - Autonomous driving is viewed as a specific application of robotics, focusing on perception, planning, and control, but lacks the interactive capabilities needed for general robots [17][19]. - The integration of expertise from autonomous driving is seen as a bridge to advance embodied intelligence, enhancing technology fusion and development [18][22]. Group 3: Key Challenges in Embodied Intelligence - Current robots often lack essential capabilities, such as tactile perception, which limits their ability to maintain balance and perform complex tasks [38][39]. - The operational capabilities of many humanoid robots are still in the demonstration phase, lacking the ability to perform tasks in real-world contexts [38][39]. - The complexity of high-dimensional systems poses significant challenges for algorithm robustness, especially as more sensory channels are integrated [39]. Group 4: Future Applications and Market Focus - The focus for developers should be on specific application scenarios rather than pursuing general capabilities, with potential areas including home care and household services [48]. - Industrial applications are highlighted as promising due to their scalability and the potential for replicable solutions once initial systems are validated [48]. - The gap between laboratory performance and real-world application remains significant, necessitating a focus on improving system accuracy in specific contexts [46][47].

具身智能，作为近年来人工智能领域的热点之一，成为产业界和学术界重点关注的方向。特别是在人形机器人这个载体上，它所承载的感知、运 动、决策等能力，让具身智能从概念逐渐走向落地。但与此同时，也有不少值得深入探讨的问题浮出水面：为什么具身智能的发展似乎格外偏 爱"人形"？是否只有模仿人类形态，才是实现智能的最佳路径？在面对数据、算力、模型架构等现实挑战时，我们究竟处于怎样的阶段？距离真 正的通用机器人，还有多少"里程"要走？ 基于此，CSDN《万有引力》栏目特别策划了一期以"十问具身智能：我们离通用机器人还有多远？"为主题的深度对话，邀请了北京邮电大学人 工智能学院副教授陈光@爱可可-爱生活、深圳市人工智能与机器人研究院副研究员夏轩、Roboraction.AI 首席执行官黄浴，在栏目主理人 CSDN &《新程序员》执行总编唐小引主持下，三位专家将从技术演进、研究现状、产业应用等多个角度切入，带大家一同拆解具身智能面临的"关键问 题"，看清这条通往未来机器人的发展路径。 夏轩：在专业背景方面，我早期的研究主要集中于计算机视觉领域（CV），涵盖无人机图像处理、工业图像处理以及生成模型等方向。在扩散模 型兴起之前，我也 ...

太平洋近日发布机械日报：2025年5月14日，沪深300上涨1.21%，机械板块下跌0.43%， 在所有一级行业中排名29。细分行业看，半导体设备涨幅最大，上涨0.79%；工程机械跌幅 最大，下跌1.96%。个股方面，日涨幅榜前3位分别为恒而达(+20.00%)、中集环科 (+19.97%)、大叶股份(+12.98%)；跌幅榜前3位为磁谷科技（-8.20%）、信宇人(-7.46%)、德 马科技（-6.19%)。 以下为研究报告摘要： 报告摘要 市场表现： 2025年5月14日，沪深300上涨1.21%，机械板块下跌0.43%，在所有一级行业中排名29。 细分行业看，半导体设备涨幅最大，上涨0.79%；工程机械跌幅最大，下跌1.96%。个股方 面，日涨幅榜前3位分别为恒而达(+20.00%)、中集环科(+19.97%)、大叶股份(+12.98%)；跌 幅榜前3位为磁谷科技（-8.20%）、信宇人(-7.46%)、德马科技（-6.19%)。 公司公告： 【新时达】公司持股5%以下股东王春祥先生王春祥先生在减持前持有公司股份的 2.12%，计划以大宗交易或集中竞价方式累计减持公司股份的0.15%。公司持股5%以下股 ...

● 本报记者 张兴旺 东方财富Choice数据显示，二季度以来，机构密集调研中控技术、兆威机电、蓝思科技、祥鑫科技、富 临精工、领益智造、安培龙等52家人形机器人产业链公司。 机构认为，人形机器人进入工业场景已经成为确定性较高的应用趋势，人形机器人商业化落地可期，产 业链公司将迎来长期发展机遇。 二季度以来，中信建投证券、中金公司、摩根大通证券等160家机构调研富临精工。富临精工表示，公 司积极把握智能机器人发展及与机器人有关的精密机械零部件、机器人电关节、减速器等关键组件的产 业机遇，加快机器人智能电关节模组及零部件布局。 领益智造正在加速布局AI端侧与机器人领域关键零部件的研发生产。二季度以来，博时基金、中信资 管、广发证券等37家机构调研领益智造。领益智造表示，公司拥有伺服电机、减速器、驱动器、运动控 制器等人形机器人执行层的核心技术，在结构件方面，可提供模切结构件、金属结构件、注塑结构件、 软包结构件等。目前，公司已为人形机器人客户提供头部总成、灵巧手总成、四肢总成、高功率充电和 散热解决方案等核心硬件，在联合开发和整机组装上有成熟经验。 上市公司加快拓展 上海证券认为，近期，华为、字节跳动、比亚迪、 ...