About
Last updated
Last updated
Embodied AI refers to artificial intelligence that operates in the physical world through robotic or simulated bodies, enabling machines to perceive, interact with, and adapt to their environments. Unlike traditional AI, which primarily processes text and images, embodied AI integrates perception, reasoning, and physical actions, allowing robots to understand and respond to the complexities of real-world scenarios. This makes it essential for creating future AGI humanoid robots.
At Reborn Network, we spearhead the creation of the first decentralized humanoid data generation protocol for embodied AI. By transforming human motion into tokenized assets for training embodied AI, we are bridging the gap between human intelligence and robotic capabilities through blockchain technology. Enabling the community to contribute VR/AR gaming data, motion capture via our proprietary Rebocap™ hardware, and everyday video data, Reborn Network is establishing a decentralized data economy that democratizes access to robotics development - making everyone contribute to future robotic training and get rewards, i.e., the Reborn tokens and a real robot.
The extraordinary capabilities of modern large models in language and vision stem from their training on vast datasets, freely sourced from decades of internet content contributed by billions of users and communities. Language models, for instance, are trained on 15 trillion tokens, while vision models leverage 6 billion images to achieve remarkable performance. In stark contrast, robotics development is severely constrained by data scarcity. Scientists and robotics leaders, such as Tesla, are striving to build the next generation of general-purpose humanoid robots (AGI Humanoid Robots). These robots require the training of embodied AI models, which depend on massive amounts of human motion data. Currently, the available datasets are severely limited:
Real-World Lab Data: Mostly collected by research institutions at an exorbitant cost, with the largest real-world dataset containing only 2.4 million samples.
Simulator Data: Often generated in virtual environments, failing to fully align with the complexities and physical laws of the real world.
Robotics data scaling laws highlight that achieving truly general-purpose robots requires scaling both the quantity and diversity of data. Without this, the vision of a universal humanoid robot remains unattainable.
The robotics market is poised to revolutionize countless aspects of human life and industrial sectors, spanning healthcare, manufacturing, logistics, personal services, and beyond. The economic potential is staggering, with projections valuing the industry in the $500B market in the coming decades. However, the journey to this future hinges on overcoming a critical challenge: the insatiable demand for high-quality, diverse data. Industry surveys reveal that up to 30% of the operating costs for cutting-edge embodied intelligence companies are spent on data collection alone. This underscores the urgent need for more efficient, scalable, and accessible solutions to bridge the data gap, paving the way for a new era in robotics innovation.
Reborn Network is revolutionizing Robotic Foundation Models (RFMs) training by leveraging a decentralized, community-driven approach to human motion data collection, addressing the critical data scarcity bottleneck in robotics. By combining decentralized contributions with innovative technologies and blockchain infrastructure, Reborn collects massive, diverse, and high-quality human motion data essential for training RFMs. With over 200,000 monthly active users and 4,000 units sold of our affordable $150 Rebocap™ motion capture devices, Reborn has established itself as a leader in decentralized human motion data generation. Our protocol integrates three transformative data streams—Embodied Vlog for real-world task videos, Mocap Life powered by affordable Rebocap™ devices for precise motion capture, and VR Gaming for immersive interaction data—democratizing access to data collection while ensuring global diversity and scale. Blockchain integration secures data integrity, enables tokenized rewards for contributors, and creates a decentralized ecosystem for RFM training. Reborn accelerates the development of adaptable, general-purpose humanoid robots, positioning itself as a transformative force in the robotics ecosystem, driving innovation, and laying the groundwork for the future of robotics.
