大衍平台如何重塑具身智能的数据飞轮生态？

Core Viewpoint - The humanoid robot and embodied intelligence sector is experiencing unprecedented explosive growth driven by policies and capital, transitioning from laboratory concepts to industrial applications [1][3] Industry Challenges - The industry faces a significant data scarcity and isolation issue, with over 1 billion interaction data gaps in just the home service sector [3] - The lack of unified standards leads to fragmented data formats among different manufacturers, complicating data integration and reuse [3][4] - Developers often have to "reinvent the wheel" due to disparate tools and platforms, resulting in resource wastage and inefficiency [3][4] Data Platform Development - The Dayan Data Platform aims to address these challenges by providing a comprehensive toolchain for data collection, processing, training, simulation, and deployment [5][11] - It features cross-brand data governance to break down data silos, supporting unified data protocol definitions and multi-modal data access [7][8] - The platform standardizes various data formats, enabling high-quality data sets to be produced from heterogeneous robot data [8] Model Training and Simulation - The platform supports diverse training paradigms, including pre-training and fine-tuning, and can handle large-scale multi-modal data training [10] - It includes a high-fidelity simulation environment that allows for quick deployment across different robot brands, facilitating model testing before real-world application [10] Practical Applications - The platform has demonstrated its value by enabling intelligent trajectory generation in complex scenarios, such as optimizing spray painting processes in manufacturing [11][12] - By integrating 5G technology, the platform allows for real-time data collection and monitoring of robotic operations, enhancing operational efficiency [14] Industry Transformation - The Dayan Data Platform is reshaping the development logic of the embodied intelligence industry by providing an all-in-one toolchain that reduces R&D costs and promotes data resource sharing [15] - It fosters a virtuous cycle of data circulation, model sharing, and application collaboration, accelerating the penetration of embodied intelligence across various sectors [15]