Why Large Language Models Are Not Artificial Intelligence

Large Language Models (LLMs) are frequently described as artificial intelligence due to their linguistic fluency, apparent reasoning capabilities, and emergent behaviors at scale. This paper argues that such classification is fundamentally incorrect. LLMs are statistical sequence prediction systems that lack the architectural, physical, and neurocognitive properties required for genuine intelligence or cognitive evolution. Through formal analysis spanning information theory, dynamical systems, neuroscience,physics, and cognitive architecture, this paper demonstrates why LLMs cannot evolve into minds regardless of scale, and why future artificial intelligence must instead arise from persistent, stateful, selfmodeling cognitive systems.