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ChatGPT and AlphaGo represent two fundamentally different AI paradigms. Large language models like ChatGPT are probabilistic and autoregressive. They excel at language, code, and knowledge synthesis by predicting the next token, optimizing for coherence and relevance. They feel intelligent, but they are not truth seeking or strategic. They operate mostly in fast, intuitive system one thinking. AlphaGo, in contrast, was built for reasoning and planning. Using deep reinforcement learning and Monte Carlo Tree Search, it could simulate futures, verify outcomes, and optimize for winning. Its famous move 37 was a genuine discovery, not something copied from data. This reflects slow, deliberate system two thinking. This contrast matters for AGI. While language models have democratized AI, systems like AlphaGo show what real reasoning, self correction, and invention look like. The future of AGI may look less like a chatbot and more like an agent that plans, verifies truth, and discovers solutions beyond human intuition.