Researchers demonstrate that reasoning models in AI exhibit transient chaos and fractal basin structures that increase with task difficulty, causing longer reasoning times on harder problems. This phenomenon occurs when reasoning becomes trapped near saddle points corresponding to nearly-correct solutions, explaining why frontier models spend more computational effort on complex tasks like theorem solving and puzzle solving.