Georg Unterholzner @georg.dev · Jun 11 Worst of all, LRMs reduce their reasoning effort as problems get harder. Despite having spare token budgets, they underthink when complexity peaks, like a student giving up on an exam’s toughest question—even with extra time left 😅
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Researchers even handed models step-by-step algorithms (e.g., for Tower of Hanoi). The result: identical failure points. LRMs couldn’t reliably execute prescribed logic—suggesting their "reasoning" is often pattern-matching, not general intelligence.