How do large language models learn new information after training?

Large language models can keep learning new things even after they’ve already been trained, like a student who keeps growing smarter even after leaving school.

Imagine your favorite toy is a robot that knows how to play games, tell jokes, and answer questions. At first, someone taught it everything by showing it lots of examples, just like you learn from reading books or watching videos. But once it's done learning, it still can keep getting better if it practices with new information.

Think of the robot as a musician who knows how to play many songs already. When it learns something new, it’s like practicing a brand-new song, it listens carefully and adjusts its playing so it sounds just right.

When it keeps learning after being trained, it's like the musician tries out new music every day, some familiar, some completely new, and gets better at playing them all.

This way, the robot doesn’t stop growing, it just keeps getting smarter, one little piece of information at a time.