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Apple’s research team casts doubts on AI’s ability to reason logically, sparking important debates on AI’s limitations.
Apple Researchers Question LLMs’ Logical Abilities
Apple’s research team has suggested that large language models (LLMs) may not be capable of genuine logical reasoning, as reported by Ars Technica. Despite their impressive outputs, LLMs often fail to apply consistent logic or reason through complex problems effectively. The study highlights how these AI systems rely heavily on pattern recognition, which limits their ability to perform tasks requiring true reasoning, such as solving puzzles or logical deduction.
AI Models Still Struggle with Reasoning Tasks
The research emphasises that current AI models excel at predicting what comes next in text sequences but struggle with abstract reasoning, a fundamental human skill. Apple’s findings point to the need for new methodologies in developing AI, suggesting that future progress will depend on innovations beyond current language models. This insight challenges the assumption that better training or bigger datasets will automatically improve AI’s reasoning capacity.
Editor’s Comment:
This is good news for those of us who actually use our brains for a living. Basically LLMs got very predictive as they took in more and more data and that mimicked smart thought. But in reality, it’s just smart mimicking. So, unless AI takes a profound leap, we are probably closing in on the limits of its smartness and thinkers will be ok. But, jobs that mimic, and most jobs do mimic, are at high risk. So think about finding yourself a thinking job.
(Visit Ars Technica for the full story)
*An AI tool was used to add an extra layer to the editing process for this story.
