Core Viewpoint - The article discusses the evolution and commercialization of embodied intelligent robots, emphasizing the importance of creating a sustainable business and data loop to enhance their capabilities and adaptability in real-world scenarios [2][12]. Group 1: Event and Initial Observations - The "Humanoid Robot Half Marathon" in Beijing sparked discussions about the performance of robots, highlighting both their endurance and the disappointment from frequent falls [1]. - The debate around whether the recent excitement about robots and embodied intelligence is mere hype is complex and not easily answered [2]. Group 2: Business and Data Loop - A successful embodied intelligent robot must build on previous generations that have established commercial and real-world data loops [3]. - Pushing Technology has developed logistics robots that can navigate complex environments, achieving a high fulfillment rate of 98.5%, allowing them to break even on costs in high-value scenarios [6][12]. Group 3: Data Collection and Training - The "Rider Shadow System" collects extensive human behavior data to enhance the robot's ability to navigate urban environments autonomously [11][13]. - The system has evolved to capture upper limb operation data, significantly increasing the volume of usable data for training [14][15]. - Pushing Technology has accumulated tens of millions of kilometers of riding data in just a few years, surpassing the historical data collection of leading autonomous driving companies [14][15]. Group 4: Adaptability and Feedback Mechanisms - The company has defined core atomic tasks for robots based on rider behavior, allowing for the development of robots capable of single-arm operations [17][21]. - A multi-level feedback mechanism has been integrated into the robot's model to ensure adaptability in uncertain environments, enhancing task delivery and user experience [23][24]. Group 5: Global Perspective and Future Plans - Pushing Technology has established partnerships with major national delivery platforms, completing nearly 100,000 deliveries, showcasing the model's strong generalization capabilities [26]. - The company aims to expand internationally, leveraging its advantages in data collection and training efficiency in complex urban environments [30].