Ψ + θ + χ: Probabilistic Systems and a short epistemology of AGI

This essay argues that the quantum wave function (ψ) and the parameter vector of contemporary AI systems (θ) belong to a single epistemic class: probabilistic systems. Such systems are defined by predictive accuracy, probabilistic abstraction, operative independence from human intention or observation, asymptotic self-refinement, and the absence of causal or explanatory frameworks. They infer structure but do not understand it. Meaning requires representational agency, here labelled χ, comprising three capacities: selective interpretation, framework retention across contexts, and framework revision when existing representations fail. Scaling θ cannot yield χ. AGI therefore presents an architectural, not computational, problem: engineering systems that can construct, hold, and revise the frameworks through which structure becomes intelligible.