Imagine you have a universal toolbox that contains many different tools, but is too large and cumbersome for certain tasks. To perform certain tasks efficiently, you can use small, specialized attachments called adapters. These adapters attach to the general-purpose tool and extend its function. For example, you can attach a screwdriver adapter to a drill to tighten screws, or a sanding head adapter to smooth surfaces. In artificial intelligence, adapters work in a similar way: they are small, specialized modules that dock onto a large, general AI model and optimize it for specific tasks. This allows large, complex models to be used efficiently for specific tasks without having to retrain the entire model.