Why do large language models sometimes create false information?

Large language models sometimes make up information because they’re trying to guess what comes next, just like when you finish someone else’s sentence.

Imagine you're playing a game where you have to complete a story. You only know the beginning, and you have to say what happens next. Sometimes you get it right, but other times you make things up, maybe you think the dog turned into a robot, even though that wasn’t mentioned before!

Large language models work in a similar way. They look at the words they’ve seen so far and try to predict what comes next. But when they’re not sure, they might make up a word or phrase that sounds good but isn't true.

Think of it like a storyteller who only remembers parts of the story. If the story gets complicated, the storyteller might add things that aren’t there to help finish the tale, and sometimes those added bits are completely made up!

So, just like you can make up parts of a story when you're not sure what comes next, large language models do the same thing, only they do it very quickly and with lots of words!