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A fascinating discussion on Reddit is questioning the exclusive focus on neural networks in artificial intelligence. Inspired by the “Tokyo Slime Experiment,” where slime mold organically replicated the Tokyo subway system by connecting food sources representing cities, the thread explores the potential of non-neural intelligence. This experiment showcases how complex, efficient networks can form without centralized control, sparking reflection on the very definition and design of AI. The original Reddit post (https://old.reddit.com/r/artificial/comments/1kzmlm6/are_we_missing_the_point_of_ai_lessons_from/) raises crucial questions: If intelligence can emerge from systems like slime molds, fungi, and swarm intelligence, should we rethink our approach to building and interpreting AI models, moving beyond the constraints of purely neural architectures?