智海铸基，数聚砺剑——华为助力国地中心构建全球首个百万量级异构机器人数据集

Core Viewpoint - Embodied Artificial Intelligence (EAI) is a key driver for future productivity transformation, with China's strategic focus on advancing the industry from technology validation to large-scale commercialization, aiming to lead rather than follow in the global market [1][3]. Group 1: Development of EAI in China - The Chinese government has identified EAI as a strategic priority in the 2025 Government Work Report, emphasizing its role in nurturing emerging industries [1]. - The National and Local Joint Innovation Center for Humanoid Robots was established in May 2024, serving as the first national public platform in the humanoid robot field to promote data collection, technology research, enterprise incubation, and talent cultivation [1][3]. Group 2: Training Ground Functions - The training ground aims to achieve five core functions: 1. Data collection and scaling, allowing humanoid robots to gather extensive data through environmental interactions to optimize algorithms and enhance performance [4]. 2. Model training and development, providing infrastructure for humanoid robots to improve skills through methods like imitation learning and reinforcement learning [5]. 3. Scene simulation and application implementation, enabling robots to adapt to various tasks in real-world scenarios such as elderly care and industrial inspections [7]. 4. Model testing and evaluation, focusing on assessing key performance indicators like mobility and decision-making logic [8]. 5. Talent cultivation and ecosystem development, offering practical opportunities for researchers and engineers while promoting industry innovation [9]. Group 3: Huawei's Role in EAI Development - Huawei is assisting the National and Local Joint Innovation Center in building a comprehensive solution for the training ground, covering the entire lifecycle from data collection to model training [11]. - Key initiatives include: 1. Efficient and stable edge data collection solutions using a "cloud-edge" architecture to ensure high-quality data acquisition [13]. 2. A robust data management system that supports real-time data processing and enhances data availability while reducing storage costs by 50% [15][16]. 3. Enabling model training through high-performance caching solutions to maximize computational resource utilization [17]. 4. Fostering ecosystem collaboration by creating a shared dataset, "White Tiger Dataset v0.0.1," which is the first globally to exceed one million heterogeneous robot data points [19][20]. Group 4: Industry Impact - The humanoid robot training ground is expected to fill the gap in large-scale heterogeneous humanoid robot datasets, accelerating the development of EAI technology in China and promoting the industrialization and large-scale application of humanoid robots [20].