This research exposes the harsh reality that today's "reasoning" AI models are sophisticated pattern matchers, not true thinkers. When faced with novel problems they haven't seen before, these systems collapse completely, proving they're just regurgitating memorized solutions rather than developing genuine problem-solving skills. The industry's rush toward AGI based on these flawed foundations is dangerously misguided.
While Apple's study raises valid concerns about current limitations, reasoning models still represent significant progress in AI capabilities, particularly for medium-complexity tasks where they demonstrate clear advantages over standard models. The research methodology using narrow puzzle environments may not capture the full diversity of real-world reasoning applications where these models excel. Current approaches are stepping stones toward more robust AI systems.