2025 人形机器人大时代 - 具身智能大脑的进化之路 20251120 摘要 具身智能正从模型驱动转向数据驱动，分层控制框架、VLA 模型和世界 模型是当前主流的三种机器人算法架构。分层架构适用于工业场景， VLA 模型擅长人机交互，而世界模型则依赖高保真仿真，但实际应用仍 面临挑战。 数据是具身智能的关键，行业内主要通过真机获取、视频学习和仿真数 据三种路径获取数据，成本与价值量呈正相关。数据安全问题日益突出， 企业需加强数据保护，欧盟等机构已启动相关研究。 为应对行业发展需求，提高研发投入效率至关重要。企业应优化研发流 程，加强跨部门协作，并引入先进工具和方法。跨本体训练是通用智能 的关键，MIT 和 Meta 已发布相关异构训练框架。 具身智能领域缺乏统一评测基准，斯坦福大学发布的 Behavior 1K 是首 个用于评测具身智能模型的 benchmark。国内重视 benchmark 建设 将加速技术发展与应用落地。 Q&A 2025 年机器人行业在算法层面上有哪些主要变化？ 2025 年，机器人行业在算法层面上经历了显著的变化，主要体现在从模型驱 动到数据驱动的转变。过去，机器人控制算法依赖于工程 ...

Core Insights - World Labs, co-founded by Fei-Fei Li, has launched a new real-time generative world model called RTFM (Real-Time Frame Model) which utilizes large-scale video data for efficient end-to-end training [3][4] - RTFM can generate new 2D images from one or more 2D inputs without relying on explicit 3D representations, marking a significant advancement in AI rendering capabilities [3][4] - The model can render persistent and 3D-consistent scenes in real-time using a single NVIDIA H100 GPU, enabling interactive experiences in both real and virtual environments [4][10] Company Overview - World Labs was founded in March 2023 by Fei-Fei Li and three other scholars, focusing on developing efficient, scalable, and persistent world models [8][10] - The company raised $230 million in September 2023, achieving a valuation of $1 billion within three months of its establishment [10] - The team consists of approximately 24 members, with a significant representation of Chinese individuals [10] Technology and Innovation - RTFM addresses scalability issues that have long plagued world models, enhancing spatial intelligence in machines, which allows for better navigation and decision-making in complex 3D environments [6][7] - The model's efficiency is highlighted by its ability to support interactive frame rate inference with a single H100 GPU, while its scalability allows for continuous optimization as data and computational power grow [8][10] - Future plans include developing a large model (LWM) that comprehensively understands three-dimensional, physical, and temporal concepts, with applications in AR and robotics [10][12] Research and Development - Fei-Fei Li is also spearheading the Behavior 1K challenge, aimed at standardizing tasks in embodied intelligence and robotics research, providing a platform for training and evaluation [11][12] - The Behavior 1K challenge includes 1,000 tasks focused on long-horizon tasks in everyday environments, promoting collaboration and comparison among researchers [12] - The integration of various AI technologies is seen as a transformative moment for society, emphasizing a human-centered approach in AI development [12][13]