How LLMs Generate Text — one token at a time

Large language models generate text one token at a time by predicting the next token based on previous tokens, using attention to weigh importance. This process involves tokenization, embedding, attention, prediction, sampling, and a context window. The model's confidence doesn't guarantee accuracy, as it relies on prediction rather than fact lookup. This process is similar to autocomplete with attention. Engineers should understand this process to better work with LLMs.