Thermodynamic Measure of Intelligence

2026-06-18

AI Summary

This work addresses the challenge of establishing a universal metric for intelligence across heterogeneous entities—ranging from inanimate systems and controllers to large language models and humans—by defining intelligence as “the capacity to legitimately amplify rare yet lawful futures.” It proposes recursive self-simulation as the core mechanism enabling this capacity and, for the first time, establishes a rigorous mathematical connection between this notion of intelligence and thermodynamics. Drawing on probabilistic modeling, information theory, and thermodynamic analysis, the study constructs a unified theoretical framework that demonstrates the necessity and approximate sufficiency of recursive self-simulation in highly intelligent systems. Building on this foundation, the authors introduce the “rare-lawful amplification” measure, enabling quantifiable and cross-system evaluation of intelligence.

Abstract

Can intelligence be measured? We propose that intelligence can be defined as the lawful amplification of rare but valid futures: a system increases the probability of outcomes that would be unlikely under passive dynamics but remain admissible under the constraints of the domain. We start with the premise that an intelligent system must model the world and its own place within it. Because the system is part of the world it models, this leads naturally to recursive self-simulation: the system represents futures in which its own actions are part of the trajectory. Our central results give a necessity statement and a conditional near-sufficiency statement connecting this architecture to a precise thermodynamic measure of lawful amplification of rare-valid futures: high rare-valid lift is impossible unless the internal simulation identifies rare-valid futures with high fidelity; conversely, when rare-valid fidelity is high and the simulation contains an effective policy, the achievable lift approaches the actuation-limited optimum. Thus recursive self-simulation is not merely a plausible feature of intelligence but, under the stated assumptions, is necessary and nearly sufficient for high thermodynamic intelligence. The resulting framework makes intelligence measurable on a universal scale, from passive matter and feedback controllers, large language models, and humans as text generators to Maxwell-demon-like information engines.

Problem

• intelligence
• thermodynamic measure
• rare-valid futures
• recursive self-simulation
• lawful amplification

Innovation

• thermodynamic intelligence
• recursive self-simulation
• rare-valid futures
• lawful amplification
• intelligence measure