Generalized dissipative catalysis as a physical principle for life, evolution and artificial intelligence

Abstract Living systems are usually defined through replication and Darwinian evolution, yet this leaves unexplained why replicating structures arise and persist in open physical environments. Here I propose that the more primitive feature is generalized dissipative catalysis: the acceleration, widening or stabilization of free-energy dissipation pathways by inheritable constraints. In this view, chemical catalysts, compartments, genomes, nervous systems, societies and artificial intelligence differ in substrate but share a physical role: they make new dissipative channels accessible while preserving the constraints that enable them. A secondary analysis of AnAge Build 15 shows that metabolic rate, maturation time and longevity retain systematic allometric signatures, consistent with life histories occupying constrained energetic frontiers rather than maximizing instantaneous replication. The framework predicts that efficient but fragile catalysts should select for compartments, repair, inheritance and anti-parasitic control, and that AI represents a non-biological expansion of informational dissipative catalysis. Keywords: generalized dissipative catalysis, origin of life, constraint closure, dissipative structures, artificial intelligence