Core Insights - The article presents PhysXNet, the first systematically annotated 3D dataset based on physical properties, addressing the gap between virtual 3D assets and real-world physics [6][9][27] - It introduces PhysXGen, a novel framework for generating 3D assets that incorporates physical attributes, enhancing the realism and applicability of 3D models in various fields [9][18][27] Dataset Overview - PhysXNet includes over 26,000 annotated 3D objects with detailed physical properties, while the extended version, PhysXNet-XL, contains over 6 million programmatically generated 3D objects [9][10][16] - The dataset covers five core dimensions: physical scale, materials, affordance, kinematic information, and textual descriptions, providing a comprehensive resource for 3D modeling [6][9][27] Annotation Process - A human-in-the-loop annotation framework was developed to efficiently collect and label physical information, ensuring high-quality data [11][13] - The annotation process involves two main stages: initial data collection and determination of kinematic parameters, utilizing advanced models like GPT-4o for accuracy [13][11] Generation Methodology - PhysXGen integrates physical attributes with geometric structure and appearance, achieving a dual optimization goal for generating realistic 3D assets [18][27] - The framework demonstrates significant improvements in generating physical properties compared to existing methods, with relative performance enhancements in various dimensions [23][24] Experimental Results - The evaluation of PhysXGen shows notable advancements in both geometric quality and physical property accuracy, outperforming baseline methods in multiple metrics [20][21][23] - The results indicate a 24% improvement in physical scale, 64% in materials, 28% in kinematic parameters, and 72% in affordance compared to traditional approaches [23][24] Conclusion - The article emphasizes the importance of bridging the gap between 3D assets and real-world physics, highlighting the potential impact of PhysXNet and PhysXGen on fields such as embedded AI, robotics, and 3D vision [27]

2025 第二届中关村具身智能机器人应用大赛 欢迎大家踊跃报名参赛! 智源具身智能模型能力挑战赛火热报名中! 本届赛事以 「具身引智 · 应用未来」 为主题，打造一个 汇聚尖端技术与产业应用 的舞台。这里不仅是比拼模型实力的竞技场，更是展示创意与才华的舞台。让我们 一起突破边界，提升模型能力，推动具身智能 走出实验室，走进现实世界，创造真正的价值！ 未来已来，等你出发！ 了解更多信息 资源支持 充足的算力支持 真机数据采集、标注一站式平台支持 机器人本体设备支持 智源专家全程技术指导 场地与环境保障 奖金与荣誉 更靠浪志关 优胜奖(第4-6名) 三等奖 2万 等奖 5万 学奖 3 可 学生选手福利:有机会获得直通智源研究院实习、入职机会 真机实战:人形机器人、高性能机械臂、移动操作平台等 顶级算力 & 自由科研:享用智源充足的算力与海量数据,专注探索与突破 导师天团:PI与资深研究员亲自带队,从思路到代码全程指导 一流薪资与全方位福利:行业领先的待遇+系统化保障,助力科研无后顾之忧 国际化团队:与清华、北大、斯坦福等全球顶尖学者并肩攻关 成长跃迁:优秀实习生可直通 「智星计划」,智源的头部人才计划,同时获得正 ...

Apple supplier BOE Technology Group, the world's largest display maker, has established a new subsidiary to lead its foray into robotics and artificial intelligence software. Launched on Thursday, Beijing BOE Robot has a registered capital of 200 million yuan (US$28 million), according to corporate data provider Qichacha. The subsidiary was described as a developer of industrial robots and AI software, joining other major manufacturers that are pursuing robotics-related development projects. Do you have ...

今年的国庆和中秋赶在一起了，首先提前祝大家节日快乐。也希望每个人都能好好放松下，包括峰哥自己 也真的需要relax下。做了这么久的社区运营和媒体，几乎每天都在线，随时都要处理同学们的问题。 最近在做一个什么事情呢？ 主要推进硬件和社区还有很多公司的商务。 前面有很多同学一直向峰哥吐槽硬件贵、不好用。这块我们正在努力找合适的方案，不久就会推给大家。 近期正在推进一些具身产品的测试和开发，期望能给大家提供几个使用还不错的平台。 到时候，会第一时 间在我们的具身智能之心知识星球公开。 还有就是想着完善社区，减少盲区和不完善的体系。体系大，零散，需要投入很多时间整理。所以小长假 前，还要努力一把子，节后给大家呈现更好的内容。 我们也陆续收到了很多高校在具身方向的招生需求，特别是RA、博士、博士后。感兴趣的同学也提前26年 的升学、工作做好准备，和老师熟悉起来，关注我们日常的一些招生信息。正在秋招或者社招的同学，简 历也可以随时砸给我们，第一时间帮大家内推。 所有的内容都会第一时间沉淀到我们的具身社区内，具身智能之心知识星球一致努力打造成为超大的具身 与机器人社区，期望能够在大家最需要帮助的时候解决问题，求职的时候能够 ...

2025网易未来大会9月27日在杭州举行。北航机器人研究所名誉所长、教授王田苗表示，围绕具身智能 产业，区域竞争不再是简单的"给钱""给地"，而是围绕"技术闭环-量产能力-数据回流-商业闭环"展开的 全链条竞速，未来2—3年将进入"万台级量产、千亿级集群、场景全面渗透"的关键窗口期。 ...

Core Viewpoint - The article emphasizes the ongoing advancements in artificial intelligence (AI) as of 2025, highlighting the rapid iteration of large models and the emergence of new applications, particularly in China, where domestic models are approaching or surpassing international standards [2][3][4]. Summary by Sections AI Development Trends - In 2025, AI continues to evolve with significant breakthroughs in large models, including GPT-4.5, GPT-5, and Genie 3, enhancing capabilities in understanding, generation, and reasoning [3][4]. - The advancements in model capabilities are leading to new application forms, such as automated code generation and multi-step task completion in intelligent agents [4]. Domestic AI Landscape - China's AI development in 2025 is marked by domestic large models not only matching but also leading in performance compared to international counterparts, with a strong open-source ecosystem [4]. - Recent rankings show that all top 15 open-source AI models on the Design Arena leaderboard are from China [4]. Recognition of AI Leaders - The article outlines a curated list of top companies and products in AI for 2025, recognizing those with significant technological strength and innovation [6][7][8][9][10][11][12][13]. - Categories include: - **Top 10 Companies with Strong Technical Strength**: Companies that have made long-term investments in AI technology and maintain a leading position in the field [7]. - **Top 20 AI Leading Companies**: Firms that have established comprehensive operational capabilities and competitive advantages in AI technology and applications [8]. - **Top 20 Best Large Models**: Recognizing representative and powerful foundational models in the domestic market [9]. - **Top 20 Best Large Model Products**: Highlighting valuable new products and applications based on large models [10]. - **Top 10 Leading Companies in Embodied Intelligence**: Companies with systematic technology layouts and continuous innovation in the field of embodied intelligence [12]. - **Top 10 Leading Companies in ScienceAI**: Firms focusing on the intersection of AI and other scientific disciplines, driving industry development through innovative solutions [13].

Group 1 - The company has engaged in collaboration and communication with leading robot manufacturers such as Zhiyuan, Leju, and Zhejiang Renxing [1] - The company has identified over 40 industrial production scenarios suitable for humanoid intelligent robots based on historical project experience and deep understanding of processes [1]

Thank you for that exciting speech about the future of vehicle technology. Can technology sense the world like humans. 9C Skylar explores embodied intelligence.Please welcome Skylar to the stage. [Applause] Hello everyone. I'm Skyler from Nangc.My topic is technology innovation. Today I want to start with a simple yet powerful story about light. A few years ago, a remote village was plugged into darkness every night until a Chinese entrepreneur brought a portable sort device.Suddenly thousands of household ...

沿沪宁产业创新带（以下简称"沿沪宁"），正在不断走深做实。自2019年写入《长三角一体化发展规划 纲要》，2022年国家发改委出台《沿沪宁产业创新带建设方案》和2025年三省一市发布《关于促进长三 角科技创新协同发展的决定》，今年以来，上海市普陀区与南京、无锡、常州、苏州、南通、扬州、镇 江、泰州等八市，携手推动沿沪宁产业创新带建设，逐渐形成一条辐射力强、分工凸显的创新走廊。 机器人是沿沪宁产业链完整、企业数量多、发展质量高的产业之一。沿沪宁机器人产业发展状况如何？ 产业分工呈现怎样的格局？本报告采用了产业通、企查查、IT桔子、国家标准化管理委员会、国家知识 产权局和上市公司年报等数据，梳理沿沪宁机器人产业发展图谱。 本文主要发现如下： • 企业分布：沿沪宁汇聚全国9%的机器人企业，主要集中于上海浦东和苏州昆山。企业整体质量较高， 上海龙头企业优势突出。 •产业分工：上海大模型技术引领具身智能，南京工业机器人，苏州服务机器人，无锡精密电子制造， 常州电池电机，南通机器人小镇，其他地区蕴藏广阔应用场景潜力。 •经营状况：2024年沿沪宁机器人上市公司总体经营表现转弱，上游企业利润走低，中游企业单价高盈 利少，下 ...

Core Insights - Nvidia is considering a $500 million investment in Wayve, a company focused on embodied artificial intelligence for autonomous vehicles [1][2] - Wayve has a history of collaboration with Nvidia since 2018, utilizing Nvidia technology in its robot platforms [2] - The investment evaluation is part of Wayve's upcoming funding round, following a $1.05 billion Series C funding round in May 2024, which included participation from Nvidia [2][5] Company Collaboration - The partnership aims to deliver production-ready autonomous driving technology by integrating Wayve's foundation model with Nvidia's automotive-grade computing platforms [3] - Wayve's next platform, Wayve Gen 3, will utilize Nvidia Drive AGX Thor technology [3] Technology Development - Wayve's AV2.0 approach focuses on self-driving technology that learns from experience rather than explicit programming, which is expected to revolutionize mobility [4] - Nvidia recognizes Wayve as a leader in deep learning for autonomous driving, emphasizing the ability of Wayve's platform to adapt to new environments without costly sensors and high-definition maps [5] Future Prospects - Nvidia's vice president of automotive business highlighted the potential of Wayve's next-generation AV2.0 approach, which leverages Nvidia's advanced architectures for AI workloads [6] - Nvidia has published over 70 research papers to demonstrate AI's capabilities in real-world applications, aiming to enhance embodied intelligence across various industries [6]