Why LLMs Learn by Guessing the Next Token

Large Language Models don’t learn rules, grammar, or facts explicitly. They learn by doing one thing over and over again: predicting the next token. In this video, we break down the actual learning objective behind models like GPT and LLaMA, and show how simple probability, loss functions, and gradient descent scale into intelligence. You’ll learn: - What “next-token prediction” really means - How training data is converted into prediction tasks - Why cross-entropy loss is used for language modeling - How backpropagation updates billions of parameters - Why predicti…