How do large language models understand and create human language?

Large language models learn to understand and create human language by learning from lots of examples, just like a child learns to speak by listening to their parents.

Imagine you have a huge book that contains every sentence ever said by everyone in the world. A large language model is like a super-smart kid who reads this whole book, not once, but many times. By reading so much, they start to notice patterns, like how words fit together and what comes next after certain phrases.

When you ask a question, the model looks at the words you used and tries to find similar patterns in the big book it read. It’s like when you say "I’m hungry," and your mom knows you want food, she just understands from the way you talk.

When the model wants to answer or make up a sentence, it uses what it learned from the book. It picks words that fit together well, based on the patterns it saw before. It’s like when you write a story and choose words that sound right, not random ones, but ones you know work well together.

This way, large language models can understand what you're saying and even make up new sentences of their own!