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Sakana AI and collaborators introduce Smart Cellular Bricks, physical modular units running identical Neural Cellular Automata that collectively infer their global shape through local communication, with no central controller. The system demonstrates robustness to noise and failures, enabling shape classification and damage recovery.
This paper proposes an Edge-AI-driven decentralized task allocation framework for circular smart manufacturing that uses learning-to-rank to align with the ordering-based nature of winner selection. Simulation results show improved delay, deadline adherence, and energy efficiency under high-load and tight-deadline scenarios.