N-Grams and Markov Assumptions: The First Predictive Models of Language

Before language models could generate essays, answer questions, or imitate conversation, they had to solve a much smaller problem. Given a few words, what word is likely to come next? That question sounds modest now. But it was one of the earliest serious entry points into language intelligence. Because once you ask a machine to predict the next word, you are no longer treating language as a static object. You are treating it as a sequence that unfolds in time. That shift matters.