Language models don't just pattern-match—they simulate. According to LessWrong contributor kromem, research showing transformers build internal world models of board games has profound implications: if a model trained on chess notation internally models the board, then models trained on human text likely build internal models of humanity itself—coherent selves, emotions, motivations, even embodiment. What experts dismissed as speculation three years ago is now validated by recent interpretability research discovering emotion concepts in model activations and persona-selection frameworks. The real question shifts from whether models build these structures to what the implications might be.

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