Recent research from the University of Oxford and the École Polytechnique Fédérale de Lausanne (EPFL) has revealed that large language models (LLMs), such as those powering AI chatbots like ChatGPT, generate language by drawing analogies to stored examples rather than by applying explicit grammatical rules. This approach mirrors human reasoning in language processing. EPFL researchers identified specific units within these AI models that play a critical role in language tasks, akin to the brain's language system. Disabling these units significantly impaired the models' language performance. The findings highlight that LLMs generalize language patterns in a human-like manner, relying on analogy and memory rather than abstract grammatical rules. Despite advances in generative AI, challenges such as hallucinations in LLMs continue to affect their safe and scalable deployment in applications like customer service.