This chapter breaks down the inner mechanics of large language models in a simple and practical way.
The model takes in a user query or text input and generates a textual response.
Inside, it's a neural network trained on millions of documents.
Based on this training, it learns to predict the next word in a sentence with high accuracy.
It does this word by word, generating coherent text that appears intelligent.
Early models around 2022 were simpler, but the basic logic of token prediction remains the same.
The chapter demystifies the black box by explaining how the model generates text one word at a time based on statistical patterns it learned during training.