The Google AI research team has proposed a universal method for personalized text generation using large language models. They employ a multi-stage, multi-task structure that includes retrieval, ranking, summarization, synthesis, and generation, to train large language models for personalized text generation. This method has been validated on three public datasets, showing significant improvements over the baseline models across all datasets. This research provides a universal approach to personalized text generation, applicable to various scenarios, and holds promise for enhancing the adaptability and personalized response capabilities of generation systems.