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This paper proposes a thermodynamic measure of intelligence defined as 'rare-valid lift' and argues that recursive self-simulation is necessary and nearly sufficient for high thermodynamic intelligence, making intelligence measurable on a universal scale.
This is a popular science article of over 25,000 characters, starting from the origin of entropy, reviewing the development of dissipative system theory, and exploring a three-level analysis of whether AI belongs to dissipative systems (hardware level, training level, static model).
Proposes a hybrid framework coupling large language models with thermodynamic databases and simplified kinetic models for inorganic synthesis planning, using the niobium–oxygen system as a case study.