LLMは模倣者のままとSutton氏が主張、一方でAlphaGoこそ本物の科学
チューリング賞受賞者のRichard Sutton氏は、純粋な生成AIには真の科学的発見に必要な内部評価ループが欠けていると主張する。
reinforcement learning pioneer richard sutton critiques pure generative ai, stating it cannot perform true science because it lacks the ability to evaluate and select its own novel outputs. while models like alphago or alphafold succeed via objective feedback loops, llms rely on human or external verification, meaning their novelty is often just hallucination. sutton argues that combining generation with automated evaluation—formal proofs, code tests, or game wins—is the only path to genuine ai-driven discovery.