How do machine learning models work? And are they really capable of “thinking” or “reasoning” in the same way humans do? This philosophical and practical question has been the subject of ongoing debate. However, a recent paper titled “Understanding the Limitations of Mathematical Reasoning in Large Language Models,” authored by a team of AI research scientists at Apple, suggests a clear answer: not yet.
The core of the research centers around the difference between symbolic learning and pattern reproduction, and while these concepts are complex, the basic premise is straightforward. To illustrate, imagine a simple math problem:
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