Learn the basics of LLMs in 60 seconds with Beau Carnes

A quick 60-second explainer on how large language models (LLMs) work. LLMs are next-word prediction machines trained on trillions of tokens from the internet. Text is split into tokens (numbers), and the transformer architecture allows the model to look at all tokens simultaneously, learning relationships between words. When given a prompt, the model calculates probabilities for the next token, picks one, adds it to context, and repeats until done. The core concepts are training data, tokenization, attention mechanisms, and probabilistic prediction — not true thinking, but pattern matching at massive scale.