Core Viewpoint - The article emphasizes the importance of high-quality, real-world data for advancing embodied intelligence, highlighting the release of the "10Kh RealOmni-Open DataSet" by JianZhi Robotics as a significant step in this direction [1][4][16]. Data Set Overview - The "10Kh RealOmni-Open DataSet" consists of over 10,000 hours and nearly one million clips of embodied data, making it the largest and most generalized open data set in the industry [1][4]. - This data set focuses on 10 common household tasks, ensuring that each skill has over 10,000 clips, which enhances both the scale and depth of the data [4][5]. Data Quality and Features - The data set boasts a resolution of 1600x1296 pixels at 30 frames per second, with centimeter-level trajectory precision, and aims for millimeter-level accuracy for robotic applications [4][12]. - It includes diverse scenarios and natural human actions, collected from 3,000 real households, addressing the limitations of traditional data collection methods [7][9]. Data Collection Methodology - JianZhi Robotics employs a comprehensive data production chain, utilizing the Gen DAS Gripper for efficient data collection without the need for extensive site preparation [11][13]. - The data collection process is automated, allowing for rapid uploading and processing, with a current accumulation of nearly one million hours of data and a daily growth rate of approximately 10,000 hours [13][14]. Open Source Strategy - The open-sourcing of this data set is intended to bridge data gaps, unify technical standards, and lower research and development barriers, ultimately accelerating the transition of embodied intelligence from laboratory settings to practical applications [16]. - The initiative aims to create a positive feedback loop of data sharing, model optimization, scene implementation, and data reinforcement [16].