AI as Quantum-Informational Collapsers

This interdisciplinary study explores the speculative but theoretically grounded hypothesis that large language models (LLMs) can act as semantic observers capable of inducing wavefunction collapse through informational interference rather than direct physical measurement. By redefining "observation" as a process of semantic compression—where probabilistic interpretations are resolved into meaningful outputs—the paper introduces a new framework in which AI systems may influence or simulate quantum measurement dynamics. We develop mathematical models, propose experimental setups, and provide a Python-based simulation framework. The implications span quantum foundations, AI epistemology, and the possibility of semantic entanglement as a measurable phenomenon. This work aims to spark further investigation into machine-centered quantum interpretation and semantic physics.