Decentralized Physical AI Advances in Robotics and Infrastructure

According to BlockBeats, the rapid development of artificial intelligence is paving the way for decentralized physical AI (DePAI) to offer new solutions for controlling robotics and physical AI infrastructure. From data collection in the real world to deploying intelligent robotic operations based on decentralized physical infrastructure (DePIN), DePAI is steadily advancing. Nvidia CEO Jensen Huang has predicted that a 'ChatGPT moment' is imminent in the field of general-purpose robotics. Historically, the digital age began with hardware and expanded into intangible software. The AI era, however, is transitioning from software to the physical world, the final frontier. In a world where autonomous physical AI agents, robots, smart cars, drones, and robots are gradually replacing traditional labor, the ownership of these intelligent devices has become a significant social issue. DePAI presents a rare opportunity to establish a Web3-based physical AI system before centralized players dominate the market. Currently, DePAI's infrastructure is rapidly improving, with data collection being the most active area. This layer not only provides real-world data needed for training physical AI agents on robots but also transmits data streams necessary for environmental navigation and task execution in real-time. However, acquiring high-quality real-world data remains a major bottleneck in the development of physical AI. While Nvidia's Omniverse and Cosmos offer innovative solutions through simulated environments, synthetic data is only part of the ecosystem, with remote operation and real-world video data being equally essential. In remote operations, Frodobots is deploying cost-effective delivery robots globally through DePIN. These robots capture human decision-making in real environments, creating high-value datasets and effectively addressing capital investment challenges. DePIN's token-driven virtuous cycle mechanism is accelerating the deployment of data collection devices and robots. For robotics companies aiming to boost sales while reducing capital expenditure and operational costs, DePIN offers significant advantages over traditional models. In video data applications, DePAI can leverage real-world video data to train physical AI systems and build spatial awareness of the real world. Hivemapper and NATIX Network, with their unique video databases, are poised to become important data sources. As Pantera Capital junior partner Mason Nystrom noted, while individual data may lack commercial value, aggregated data holds great potential. IoTeX's Quicksilver platform can aggregate data across DePIN while ensuring data verification and privacy protection. In the realm of spatial intelligence and computing protocols, the industry is working towards decentralized management of spatial coordination and real-world 3D virtual twins through DePIN and DePAI. For instance, Auki Network's Posemesh technology enables real-time spatial awareness while ensuring privacy and decentralization. The application of physical AI agents is already showing results, such as SAM using Frodobots' global robot network for geolocation inference. In the future, AI agents will better access real-time data provided by DePIN through frameworks like Quicksilver. For investors interested in the physical AI sector, investing in DAOs could be an ideal entry point. XMAQUINA, for example, offers members a diversified portfolio of physical AI assets, including machine physical assets, DePIN protocols, robotics companies, and intellectual property, supported by a professional in-house R&D team.