  This paper aims to explore a generative approach for knowledge-based design
ideation by applying the latest pre-trained language models in artificial
intelligence (AI). Specifically, a method of fine-tuning the generative
pre-trained transformer using the USPTO patent database is proposed. The
AI-generated ideas are not only in concise and understandable language but also
able to synthesize the target design with external knowledge sources with
controllable knowledge distance. The method is tested in a case study of
rolling toy design and the results show good performance in generating ideas of
varied novelty with near-field and far-field source knowledge.
