Summary

Large language models understand text by turning words into numbers called tokens, then giving each token meaning through embeddings and position information. They use attention to let tokens share information and a feed-forward network to process each token independently. Finally, the model predicts the next token step-by-step, learning from huge amounts of text to get better at this task.