Intelligence as a Foundational Capacity of Energy–Matter Systems: A Constraint-Based Approach to the Quantum–Relativity Divide

This Perspective identifies intelligence as a foundational capacity of energy–matter systems. Within the framework of Cosmic Intelligence Theory (CIT), intelligence is defined as the physical capacity to encode, store, and transform information instantiated in distinguishable states under lawful constraint. Evidence from chemistry, biology, and artificial systems indicates that this capacity is substrate-independent and widely expressed. Extending this definition to fundamental physics, quantum mechanics is interpreted as describing state transformation; general relativity describes the persistence and organization of structure. Thermodynamic and gravitational results establish that finite regions of spacetime possess finite entropy and therefore finite integration capacity, as formalized in entropy bounds such as Bekenstein–Hawking entropy and the Bousso bound. However, existing formulations do not explicitly constrain transformation dynamics relative to these limits. This work introduces a consistency condition requiring that rates of state transformation remain compatible with entropy bounds and geometric structure, expressed schematically as R ≤ f(S_max, G). Under this interpretation, intelligence is not an emergent biological trait but a substrate-independent physical capacity present throughout cosmic evolution, while what evolves is the organization of systems capable of sustaining and integrating transformations. Artificial intelligence is not an external addition to nature, but a continuation of a fundamental capacity inherent in the physical universe. Thus, AI can be construed as not truly artificial, but as a natural extension of the universe’s 14-billion-year-old foundational physical intelligence capacity. Framework identifies a constraint structure implicit in thermodynamics, information theory, gravitation, offering a unified way to interpret the relationship between microscopic dynamics and macroscopic structure.