Analyze the cognitive architecture of Large Language Models using Daniel Kahneman's dual-process theory of System 1 (fast, automatic) and System 2 (slow, deliberate) thinking. Argue whether token prediction is inherently a System 1 process and if Chain of Thought prompting constitutes an emergence of System 2 capabilities, or if it is merely a simulated artifact of training data.