机器之心PRO · 会员通讯 Week 32 --- 本周为您解读 ② 个值得细品的 AI & Robotics 业内要事 --- 1. 数据困局下的具身智能，谁能率先破局？ 真实数据是否注定是通用机器人的必经之路？合成数据是否永远只能「补量」？遥操作作为当前最直接的数据采集方式，能否 在控制效率和扩展能力之间找到可持续平衡？Sim2Real 的大规模部署是否需要一种「标准化仿真」平台？在多模态遥操作系统 中，语言 + 手势 + 触觉的融合是否意味着人类操控门槛正在被技术主动下探？... 2. OpenAI 董事会主席：「按 token 计费」大错特错！市场终将选择「按成果付费」 Bret Taylor 为何称「应用 AI」才是创业者的生路？「长尾 Agent 公司」将如何取代传统 SaaS？「按 token 计费」有什么根本 缺陷？为什么 AI 市场终将选择「按成果付费」？结果导向的商业模式如何适应当前的 AI 缺陷？Bret Taylor 的商业模式在 Sierra 实践效果如何？什么是 AI 编程的新范式？... 本期完整版通讯含 2 项专题解读 + 30 项 AI & Robotics 赛道要事速递， ...

Core Insights - The 27th Annual Conference of the China Association for Science and Technology (CAST) was held in Beijing from July 1 to 31, focusing on "Tracing Technological Frontiers to Support Innovative Development" [1] - The conference attracted over 7,000 participants, including more than 110 academicians, with 57% of attendees being young scientists under 40 years old [1] - A total of over 990 high-level academic reports were presented during the conference [1] Group 1 - One highlight of the conference was the deep involvement and leadership of young scientists in frontier discussions [2] - The conference fostered an atmosphere of equal communication, allowing young scholars to directly question academicians and experts, which is beneficial for breaking cognitive biases and enhancing problem understanding [4] - The design of forums encouraged embracing uncertainty in research and promoted non-consensus viewpoints, creating a more inclusive and open academic environment [4] Group 2 - Participants engaged in discussions on cutting-edge topics such as "Sim2Real challenges" and "multimodal perception fusion" in the "Embodied Intelligent Robots" forum, inspiring new research directions [3] - The "Key Technologies for Commercialization of Controlled Nuclear Fusion" forum attracted diverse participants from academia, industry, and technology sectors, facilitating in-depth discussions on uncertain topics related to nuclear fusion [4] - The conference emphasized the importance of fostering divergent thinking and academic innovation through collaborative discussions among participants of varying expertise and age [4]

Core Viewpoint - Kuawei Intelligent, a leading domestic embodied intelligent robot company, has completed several hundred million yuan in A1 and A2 round financing, with plans to increase investment in technology research and product innovation [1][3]. Financing History - On July 10, 2025, Kuawei Intelligent completed A1 and A2 round financing, led by Chengdu Kechuang Investment and Hongtai Fund, with participation from various well-known institutions [2]. - The company had previously completed a Pre-A+ round financing on January 16, 2025, with undisclosed amounts [2]. - Kuawei Intelligent has completed a total of eight financing rounds, including angel and Pre-A rounds, with significant investments from various venture capital firms [2]. Company Overview - Kuawei Intelligent was established on June 15, 2021, in Shenzhen, initially focusing on 3D vision software and hardware product development [4]. - The company has evolved to focus on developing highly versatile embodied intelligent technology, positioning itself as a national high-tech enterprise [5]. Product Launch - On January 20, 2025, Kuawei Intelligent launched the DexForce W1, the industry's first humanoid robot based on the Sim2Real embodied intelligent engine [8][9]. - The W1 robot features a height of 170 cm, a maximum arm load of 20 kg, and an 8-hour battery life, with capabilities for autonomous charging and folding [11]. Technological Advancements - The DexVerse embodied intelligent engine enables rapid deployment and application switching in various environments, enhancing the robot's operational capabilities [11][12]. - Kuawei Intelligent has developed a comprehensive product matrix that includes the embodied intelligent brain, sensors, and general-purpose robots [12][14]. Commercialization Strategy - Initially focused on industrial robots, Kuawei Intelligent has shifted its focus to embodied large models and simulation data, emphasizing the end-to-end capabilities of the DexVerse engine [16]. - The company has achieved significant commercial success, with annual revenue reaching the billion yuan level and serving over a hundred clients across various industries [16]. Industry Context - The humanoid robot sector is divided into two main camps: hardware-focused companies like Yushu Technology and software-driven companies like ZhiYuan Robotics [17]. - Kuawei Intelligent is positioned in the software camp, emphasizing the importance of strong AI capabilities for commercialization in the humanoid robot market [17][19].

Core Viewpoint - The article discusses the unprecedented advancements in AI, particularly in embodied intelligence, which is transforming the relationship between humans and machines. Major tech companies are competing in this revolutionary field, which has the potential to significantly impact various industries such as manufacturing, healthcare, and space exploration [1][2]. Group 1: Embodied Intelligence - Embodied intelligence is characterized by machines that can understand language commands, navigate complex environments, and make intelligent decisions in real-time [1]. - Leading companies like Tesla, Boston Dynamics, OpenAI, and Google are actively developing technologies in this area, emphasizing the need for AI systems to possess both a "brain" and a "body" [1][2]. Group 2: Technical Challenges - Achieving true embodied intelligence presents significant technical challenges, including the need for advanced algorithms and a deep understanding of physical simulation, robot control, and perception fusion [2][4]. - MuJoCo (Multi-Joint dynamics with Contact) is highlighted as a key technology in overcoming these challenges, serving as a high-fidelity training environment for robot learning [4][6]. Group 3: MuJoCo's Role - MuJoCo is not just a physics simulation engine; it acts as a crucial bridge between the virtual and real worlds, enabling researchers to conduct millions of trials in a simulated environment without risking expensive hardware [4][6]. - The advantages of MuJoCo include simulation speeds hundreds of times faster than real-time, the ability to test extreme scenarios safely, and effective transfer of learned strategies to real-world applications [6][8]. Group 4: Educational Opportunities - A comprehensive MuJoCo development course has been created, focusing on practical applications and theoretical foundations, covering topics from physics simulation to deep reinforcement learning [9][10]. - The course is structured into six modules, each with specific learning objectives and practical projects, ensuring a solid grasp of embodied intelligence technologies [11][13]. Group 5: Project-Based Learning - The course includes six progressively challenging projects, such as building a robotic arm control system and implementing vision-guided grasping, which are designed to reinforce theoretical concepts through hands-on experience [15][17][19]. - Each project is tailored to address specific technical points while aligning with overall learning goals, providing a comprehensive understanding of embodied intelligence [12][28]. Group 6: Career Development - Completing the course equips participants with a complete skill set in embodied intelligence, enhancing their technical, engineering, and innovative capabilities, which are crucial for career advancement in this field [29][31]. - Potential career paths include roles as robot algorithm engineers, AI research engineers, or product managers, with competitive salaries ranging from 300,000 to 1,500,000 CNY depending on the position and company [33].

Core Insights - The article discusses the unprecedented turning point in AI development, highlighting the rise of embodied intelligence, which allows machines to understand language, navigate complex environments, and make intelligent decisions [1][2]. Group 1: Embodied Intelligence - Embodied intelligence is defined as AI systems that not only possess a "brain" but also have a "body" capable of perceiving and interacting with the physical world [1]. - Major tech companies like Tesla, Boston Dynamics, OpenAI, and Google are competing in this transformative field, which is expected to revolutionize various industries including manufacturing, healthcare, and space exploration [1]. Group 2: Technical Challenges - Achieving true embodied intelligence faces significant technical challenges, requiring advanced algorithms and a deep understanding of physical simulation, robot control, and perception fusion [2][4]. - MuJoCo (Multi-Joint dynamics with Contact) is identified as a key technology in this domain, serving as a high-fidelity training environment for robot learning [4][8]. Group 3: MuJoCo's Role - MuJoCo allows researchers to create realistic virtual robots and environments, enabling millions of trials and learning experiences without the risk of damaging expensive hardware [6][4]. - The simulation speed can be hundreds of times faster than real-time, significantly accelerating the learning process [6]. - MuJoCo has become a standard tool in both academia and industry, with major companies utilizing it for robot research [8]. Group 4: Practical Training - A comprehensive MuJoCo development course has been designed, focusing on practical applications and theoretical foundations, covering topics from physical simulation to deep reinforcement learning [9][10]. - The course is structured into six modules, each with specific learning objectives and practical projects, ensuring a solid grasp of the technology stack [13][16]. Group 5: Project-Based Learning - The course includes six progressively challenging projects, such as building a robotic arm control system and implementing vision-guided grasping [19][21]. - Each project is designed to reinforce theoretical concepts through hands-on experience, ensuring participants understand both the "how" and "why" of the technology [29][33]. Group 6: Target Audience and Outcomes - The course is suitable for individuals with programming or algorithm backgrounds looking to enter the field of embodied robotics, as well as students and professionals interested in enhancing their practical skills [30][32]. - Upon completion, participants will have a complete technology stack in embodied intelligence, gaining advantages in technical, engineering, and innovation capabilities [32][33].

以下文章来源于晚点Auto ，作者晚点团队 文丨王与桐 晚点Auto . 编辑丨程曼祺 从制造到创造，从不可能到可能。《晚点LatePost》旗下汽车品牌。 今年 5 月，一批身高 1.72 米的新工人来到美国得州工厂上班，他们负责把一粒粒圆柱形的 4680 电芯从传 输台上码放到面前的红色盒子里。他们不算熟练，甚至动作迟缓、笨手笨脚。但这批工人是 Optimus，特 斯拉 2022 年发布的人形机器人，一切不一样了。 "完美的使用场景""进步神速""失业警告"，在特斯拉释放的机器人工作视频下，人们的评论有惊叹，有担 忧。 银河通用的 Galbot 在捡垃圾，它没有双腿，而是可折叠的单腿 + 轮式底盘。 获取足够多的数据是具身智能发展的难点，特斯拉、Google 都选择用 "遥操" 采集数据，即让真人戴上一 些采集设备来完成机器人要学的动作。王鹤觉得这样算不过账："Google 做十几万条数据，就用了十多个 月、花费巨大。" 银河通用选择 all in "Sim2Real（从仿真到真机的迁移）"，即主要依靠合成仿真数据。 美国的人形机器人公司钱多、胆大，王鹤的一个观察是，这让他们没有严格地寻找 PMF（Pro ...