Messari's Unqualified Opinions
Building Decentralized Physical AI | Fully Diluted with Messari Research | Unqualified Opinions
Feb 27, 2025
Joining the conversation are Michael Cho, Co-founder of FrodoBots, creating autonomous robots for urban navigation, and Jonathan Victor, Co-founder of Onsir Research, specializing in decentralized infrastructure. They unpack how decentralized physical AI overcomes data collection hurdles, enabling innovative applications. They discuss the evolution of robotics, including the importance of human-like designs, and the thrilling competition between AI and skilled gamers, showcasing the potential of collaborative advancements in robotics and AI.
50:43
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Quick takeaways
- Decentralized networks empower robotics by enhancing data collection and evaluation, which are crucial for advancing embodied AI capabilities.
- The concept of cross embodiment suggests that varied robotic tasks can collectively optimize AI model efficiency while reducing data requirements.
Deep dives
The Concept of Cross Embodiment
The discussion emphasizes the innovative concept of cross embodiment, which posits that the aggregate model can improve by training on a diverse array of experiences across different robotic subnets. The idea suggests that varied tasks—like a humanoid washing dishes and another frying eggs—can collectively enhance the overall efficiency of AI models. Research supports that diversifying the types of tasks leads to a reduction in the amount of data required for effective training. This underscores a promising direction for future robotics research, indicating that diversity among robotic experiences can significantly amplify the capabilities of these systems.
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