The question of whether AI models actually “think” or merely mimic reasoning has gained attention in response to a recent study published by Apple researchers titled “Understanding the limitations of mathematical reasoning in large language models.” The study identifies the limitations of the mathematical reasoning abilities of existing AI.
The researchers offered the following simple math problem: Oliver harvests forty-four kiwis on Friday, fifty-eight on Saturday, and double that quantity on Sunday. Total number of Kiwis: what? Most language models (LLMs) are capable of handling such calculations, and the answer is 190. The models become confused, though, when extraneous information is added, such as “five of Sunday’s kiwis were smaller.” They fail to fully grasp the problem, as reflected by their improper subtraction of little Kiwis from the total.
There is a regular pattern of failure in many problems that are comparable. The researchers claim that these models don’t really use logic in their reasoning. As an alternative, they mimic the patterns found in their training set. Though under typical settings LLMs may appear competent, small adjustments can cause their logic to become distorted and lead to unexpected outcomes.
The researchers argue that rather than depending on in-depth knowledge, LLMs rely on statistical relationships. Though they aren’t truly reasoning, they imitate the logical processes seen in data. For instance, because it has seen that response pattern numerous times, an LLM may appropriately reply, “I love you too,” to a statement like “I love you.”
Researchers at Apple feel that more sophisticated inputs would be needed to address these problems, despite the suggestion from some, like OpenAI researchers, that better prompting could address these issues. The argument highlights significant issues regarding the marketing of AI, implying that, although remarkable, LLMs are not really capable of reasoning in the same way as humans. The increasing integration of AI into daily life necessitates an understanding of its limitations.
yeah ai models dont really reason in that sense they just predict the outcome which isnt always correct so its always a good idea to double check.