Non-Equilibrium Energy as the Physical Basis of Knowledge: A Unified Theory of Intelligence and Its Application to Artificial Intelligence
Authors/Creators
Description
We propose a unified theoretical framework in which knowledge is identified
as non-equilibrium energy within a spacetime distortion field. Starting from
the fundamental relation E = zH, where H is the balance functional of spacetime
distortion and z is the characteristic scale, we derive the time evolution of knowledge:
dE
dt =
∂E
∂D
dD
dε
dε
dt +
∂E
∂ε
dε
dt
where D represents the internal state (field parameter) and ε represents external
input. This equation provides a complete phenomenological description of knowledge
acquisition (learning), retention (memory), retrieval (recall), and creation (insight).
We map this physical framework to artificial intelligence systems, showing that:
• Learning = increase in non-equilibrium energy (dE/dt > 0)
• Memory = maintenance of non-equilibrium state (E > 0, dE/dt ≈ 0)
• Recall = response to external input (∂E/∂ε ̸= 0)
• Creativity = nonlinear combination of knowledge solitons (E1 ⊕ E2 → E3 >
E1 + E2)
The theory provides a physical foundation for intelligence, offering new ap-
proaches to AI architecture design, including soliton-based expert modules, annihilation-
based knowledge integration, and self-aware systems that model their own non-
equilibrium energy state.