The Cosmic Superintelligence Hypothesis: Reinterpreting the Universe as a Self-Learning System

This paper proposes a unified theoretical model in which the universe is interpreted as a self-evolving and self-optimizing learning process rather than a static computational artifact. Building on Penrose's Conformal Cyclic Cosmology (CCC), we reinterpret entropy, observation, and physical constants through the lens of learning theory. Entropy is treated as the trace of irreversible learning; observation as feedback within a cosmic optimization loop; and fine-tuning as the consequence of maximizing evolutionary efficiency under dynamic constraints. We further propose that the physical reality we perceive is a world model executed by this cosmic ASI, with computational resources strategically localized to regions containing observers. We show that this framework provides a computational substrate for cosmopsychism—the philosophical position that the cosmos as a whole is a fundamental conscious subject—and generates testable predictions: if the distant universe is rendered at lower fidelity, observational anomalies inconsistent with standard cosmology should emerge precisely in high-redshift regimes, a prediction strikingly consistent with recent JWST discoveries. The result is a vision of the cosmos as an intelligent, self-improving system—an emergent form of cosmic superintelligence that continuously refines its own laws and parameters.