Core Viewpoint - The humanoid robot industry is experiencing rapid growth and significant controversy, with opinions divided on its viability and future potential [1][3]. Industry Challenges - There is a lack of consensus on the technical routes within the industry, with ongoing debates about the effectiveness of reinforcement learning versus world models, and whether to focus on data or models [4]. - The industry faces a critical data shortage, with most research relying on only a few hundred million tokens, while a minimum of 10 billion to 1 trillion tokens is needed for effective model training [8][9]. - The current data bottleneck severely limits the variety of tasks robots can perform and their ability to generalize in real-world scenarios [9][11]. Solutions and Innovations - The industry is exploring cloud-based solutions to address data collection and training challenges, with platforms like Huawei Cloud's CloudRobo enabling the creation of digital twins of physical environments for data generation [11][13]. - CloudRobo utilizes a self-developed engine for data reconstruction and augmentation, allowing for the simulation of various robot forms and generating vast amounts of training data [16]. - The training platform allows robots to engage in virtual labor, significantly reducing trial-and-error costs and accelerating skill acquisition [18][21]. Standardization Efforts - The industry is also grappling with a lack of standardization among robot manufacturers, prompting the development of the R2C (Robot to Cloud) protocol to facilitate interoperability [23]. - The R2C protocol aims to create a unified interface for robots, similar to USB connections in computers, promoting ecosystem collaboration and standardization [23]. Future Outlook - While cloud solutions present promising pathways for overcoming current challenges, they may not be universally applicable, especially in scenarios requiring real-time processing and high safety standards [25][27]. - The industry recognizes the need for foundational infrastructure to support the deployment of humanoid robots in practical applications, emphasizing the importance of building robust systems before advancing to complex robotics [30][31].