How do large language models like GPT work internally?

Large language models like GPT are like super-smart helpers who can write stories, answer questions, and even chat with you, all by learning from lots of text.

Imagine you have a friend who reads thousands of books, listens to every conversation, and learns how words go together. That’s what these models do, they learn from a huge amount of text on the internet, like stories, articles, and messages.

Inside the model is something like a super-memory made up of many little pieces called neurons. These neurons work together to remember patterns in language, just like how you learn to spell words by practicing over and over.

When you ask the model a question, like “What happens next in this story?”, it uses its super-memory to think about what it learned from all those books and conversations, and then comes up with an answer that sounds natural and makes sense.

The model isn’t just remembering, it’s also creating. It looks at the words you give it, thinks about how they fit together based on everything it learned, and then picks the next word or sentence that feels right, like choosing the next piece in a puzzle.

That’s why GPT can write poems, explain science, or even pretend to be your friend, it's just using its big brain made of neurons and patterns!