DePAI: The Future of Decentralized Physical AI in the Robotic Economy

In January 2025, Nvidia’s CEO Jensen Huang marked a new phase in the evolution of artificial intelligence. According to him, this phase should be represented by Physical AI (PAI), envisioned as a global «brain» for robots and autonomous devices that enables machines to navigate the real world.

Members of the blockchain industry quickly adopted this concept, suggesting a decentralized interpretation of it. By February, the analytical platform Messari released a report on a fresh form of interaction among humans, machines, and Web3, termed DePAI. The idea of an infrastructure based on DePIN (Decentralized Physical Infrastructure Networks) aimed at fostering the future «robot economy» captured the interest of crypto influencer Miles Deutscher, who, in April, proclaimed DePAI as «the biggest trend in cryptocurrency for the next two years.»

During the CES 2025 event, Huang announced the creation of Cosmos—a platform for developing World Foundation Models (WFM), aimed at revolutionizing the development of physical AI systems, including robots and autonomous vehicles. Cosmos leverages WFMs to simulate real-world conditions, allowing for the testing of AI systems in a controlled environment that reduces costs and accelerates development.

Huang emphasized the open nature of the Cosmos platform, with its source code available on GitHub. «We genuinely hope that the openness of Cosmos provides the robotics and industrial AI communities with the same benefits that Llama 3 has brought to industrial AI,» he remarked.

As per Nvidia, PAI empowers autonomous systems—such as robots, self-driving cars, and smart environments—to perceive, comprehend, and execute complex tasks in the physical world. Large language models (LLMs) like GPT and Llama can generate human language and abstract concepts but fall short in understanding the laws of the physical realm. PAI aims to enhance their capabilities by teaching spatial orientation.

3D data for AI is generated using high-fidelity simulations that serve as both data sources and learning environments. The process begins by creating a digital twin of a space, such as a factory, incorporating sensors and robots. As sensors track the dynamics of solid bodies—such as movements and collisions, or light interactions within the environment—real scenarios are modeled in the virtual replica.

PAI presents new opportunities for transforming many sectors. In robotics, this concept could enhance various performance metrics of units deployed in diverse products. The PAI model receives rewards for successfully completing required actions, which leads to its continual improvement. Over time, machines develop advanced skills, including precise motor actions necessary for real-world applications, like packing boxes, assisting in vehicle assembly, or navigating spaces.

The PAI concept gained traction within the crypto community, which suggested blockchain as a solution to centralization in AI. Analyst Dylan Bain from Messari’s February report appended the prefix «decentralized» to the abbreviation.

The new acronym reads: DePAI—Decentralized Networks of Physical Artificial Intelligence.

DePAI intersects AI, robotics, and Web3, and could potentially drive the future economy, balancing automation with human needs. What began as generative AI for content creation is now evolving toward autonomous agents capable of making decisions independently. The only challenge left is to provide them with effective «bodies.»

On the DePAI landscape outlined by Messari, there are six key groups focused on various endeavors. DePIN projects such as the geospatial network GEODNET and alternatives to Google Maps like Hivemapper naturally fit into the emerging DePAI stack. Products from such startups can act as the eyes and ears of robots in real time, serving as data-gathering layers.

The startup WeatherXM incentivizes users to set up personal weather stations and upload climatic data in exchange for tokens. This information could be utilized by devices within DePAI. For example, smart home systems could automatically adjust ventilation or temperature based on current weather conditions.

In the robotics sector, Frodobots deploy affordable «sidewalk» delivery robots worldwide utilizing DePIN. The data procured mitigates the complexity of human decisions when navigating real environments. Gamers might practice driving vehicles in an accessible format.

Additionally, Robonomics Network, which focuses on creating digital replicas of physical robots on the Polkadot blockchain, is exploring connections between robotic operating systems and IoT devices with blockchains for publishing tasks and delivering services via smart contracts.

Coordination networks for machines are being constructed by blockchain platforms focused on DePIN, such as Peaq and IoTeX, whose rapid architecture facilitates the high volume of parallel transactions required by DePAI.

The Posemesh data transfer protocol from Auki aims to create a global spatial intelligence network, ensuring privacy while aiding in the development of a virtual map for robots. Its capabilities extend beyond logistics, also benefiting AI self-training within simulation environments.

In the investment DAO sector, Xmaquina is focused on creating a structure for collective ownership, management, and development of expensive AI robots. This organization allows communities and investors to jointly fund and advance technologies, equitably distributing benefits.

In the global machine economy, DePAI could theoretically restore power to individuals currently dominated by corporations. Users today should be keenly aware of who owns the technologies, which manufacturers set interaction standards, and ultimately, who profits.

On April 14, 2025, renowned crypto analyst Miles Deutscher dubbed DePAI one of the industry’s biggest trends. The image attached to the post illustrates the complexity of relationships within the DePAI stack, with dynamics reflected in vectors showing the actions taken among infrastructure participants.

The Peaq blockchain team, actively involved in DePAI’s development, has identified seven components essential for every autonomous system. While many of these points may be familiar to ordinary Web3 users, the future machine economy requires clarification. By integrating cutting-edge crypto technologies, the model has the potential to deliver the following positive changes:

As with all new technologies, DePAI faces significant challenges that must be addressed before mass adoption. The main issues include:

The envisioned future of a machine economy benefiting humanity is undeniably enticing and inspiring hope, yet whether giants in robotics like Tesla and other corporations will become part of it remains a substantial question.

Web3, rooted in blockchain, is likely the best solution for implementing decentralized AI today. Meanwhile, the DePAI stack clearly outlines benefits for all parties involved in future advancements, but time will reveal who participates in this evolution.