Large Language Models (LLMs) may not be as smart as they seem, according to a study from Apple researchers. LLMs from OpenAI, Google, Meta, and others have been touted for their impressive reasoning skills.

A recent study by Apple researchers raises important questions about the true reasoning capabilities of Large Language Models (LLMs).

For a while now, companies like OpenAI and Google have been touting advanced "reasoning" capabilities as the next big step in their latest artificial intelligence models. Now, though, a new study from six Apple engineers shows that the mathematical "reasoning" displayed by advanced large language models can be extremely brittle and unreliable in the face of seemingly trivial changes to common benchmark problems.

Apple's AI research team has uncovered significant weaknesses in the reasoning abilities of large language models, according to a newly

Apple's Latest Study Challenges the Notion of AI's Problem-Solving Abilities and Highlights Its Limitations! (Sophisticated Pattern Matching).

Apple researchers have argued that performance benchmarks may overstate AI reasoning capabilities. In an experiment, they found that even minor changes to benchmark questions resulted