How does ChatGPT work?

Have you ever wondered how ChatGPT can sound so human in under a minute?

ChatGPT is a language model built on a transformer architecture that predicts text one token at a time.

ChatGPT first breaks your prompt into tokens, which can be as small as a character or as long as a word.

Each token is turned into a high-dimensional vector called an embedding that captures meaning and context.

These embeddings go through transformer layers using self-attention to weigh how relevant each token is to every other token.

The model calculates a probability distribution over possible next tokens and selects the most likely one, then repeats this process token by token until the response is complete.

ChatGPT doesn't "understand" facts like a human.

It's a prediction engine that generates the most probable next token based on patterns in its training data.

It can sound confident even when it's wrong—that's why hallucinations happen.

Think of ChatGPT as a supercharged autocomplete that uses embeddings and attention to stitch together fluent responses one token at a time.

Try crafting a smart prompt now and see how precise wording changes what ChatGPT predicts next.

Ever wondered how ChatGPT sounds so human, so fast? This video breaks down the science behind transformer architecture, embeddings, and self-attention — the core mechanics powering OpenAI's language model. Learn how ChatGPT predicts each word (or token) using probability, context, and training patterns to generate natural, fluent responses. Discover why hallucinations happen, how embeddings capture meaning, and why prompt phrasing matters. Perfect for anyone curious about AI, machine learning, and natural language processing, or exploring how smart prompting shapes AI-generated text in real time.