<ul><li>A newly published Apple Machine Learning Research study challenges the narrative around large-language AI reasoning models, suggesting they may not truly reason at all.</li><li>The study used controlled puzzle environments to analyze reasoning models, finding that they experienced accuracy collapse and zero success rates beyond certain complexity thresholds.</li><li>Even when complete solution algorithms were provided, the reasoning models failed at the same complexity points, indicating limitations in basic logical step execution.</li><li>The research concludes that current AI reasoning models rely more on pattern matching than genuine reasoning capabilities, highlighting scaling limitations and inefficient thinking patterns.</li></ul>

Apple Research Questions AI Reasoning Models Just Days Before WWDC

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