Reasoning, in the context of artificial intelligence and cognitive sciences, can be seen as the process of drawing inferences or making decisions based on avail

Reasoning, in the context of artificial intelligence and cognitive sciences, can be seen as the process of drawing inferences or making decisions based on available information. This doesn't make machines like calculators or LLMs equivalent to human reasoning, but it does suggest they engage in some form of reasoning. Expert systems, for instance, use a set of if-then rules derived from human expertise to make decisions in specific domains. This is a form of deductive reasoning, albeit limited and highly structured. They don't 'understand' in a human sense but operate within a framework of logic provided by humans. LLMs, on the other hand, use statistical methods to generate responses based on patterns learned from vast amounts of data. This isn't reasoning in the traditional philosophical sense, but it's a kind of probabilistic reasoning. They can infer, locally generalize, and even 'extrapolate' to some extent within the bounds of their training data. However, this is not the same as human extrapolation, which often involves creativity and a deep understanding of context.