Autonomous Reality Convergence System Based on Resonant Computation and Federated Intelligence

This paper proposes an autonomous reality convergence system that integrates resonant computation, federated artificial intelligence, and controlled physical intervention. By abandoning sequential computation in favor of resonance, the system eliminates computational latency. A federation of specialized AI models enables unlimited scalability without performance saturation, while blueprint-based, safeguarded interventions allow AI to actively and safely influence reality. Incorporating antifragile design, circuit breakers, and a meta-ethical feedback layer, the architecture transforms AI from a passive analytical tool into a stable, socially aligned agent capable of guiding reality toward evolving ideal states.