Large language models power today's AI assistants, coding tools and search experiences. They learn by predicting the next token across vast amounts of text, are refined with instruction and preference training, and remain prone to confident errors — so important facts should always be verified.
AI agents go beyond answering questions: they combine a language model with tools, memory and a decision loop to plan multi-step tasks, act, observe results and adjust. They work best on well-defined tasks, and human oversight remains essential for high-impact actions.
