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Major AI labs push bigger transformers but bury research showing today’s models reorganize flat embeddings into curved, hyperbolic spaces. Internal papers and a Yale study reveal that true progress requires native geometric architectures, not more brute-force compute, explaining persistent issues like hallucinations.