In our previous article (How Large Language Models (LLMs) Guess the Next Word—And Why That Matters), we explored how Large Language Models (LLMs) fundamentally work by predicting the next word in a sequence. It’s a bit like a super-powered autocomplete, constantly guessing what comes next. But if LLMs only looked at the immediately preceding word, their responses would be simplistic and often nonsensical. How do they manage to write coherent essays, answer complex questions, and even generate creative stories? One of the key ingredients in this sophisticated capability is a mechanism called attention, and more specifically, self-attention.