Parameter efficient tuning is a technique that aims to update only a small subset of parameters when adapting a generative AI model to a specific task, domain, or application. It can reduce the computational cost and memory footprint of fine-tuning, while maintaining or improving the performance of the model. One example of parameter efficient tuning is prompt tuning, which updates only the parameters associated with a special token or a prompt that is prepended or appended to the input.