论文标题
生成设计构想:一种自然语言生成方法
Generative Design Ideation: A Natural Language Generation Approach
论文作者
论文摘要
本文旨在通过在人工智能(AI)中应用最新的预训练的语言模型来探索一种基于知识的设计构想的生成方法。具体而言,提出了一种使用USPTO专利数据库微调生成预训练的变压器的方法。 AI生成的想法不仅具有简洁而易于理解的语言,而且还能够用具有可控知识距离的外部知识来源合成目标设计。该方法在滚动玩具设计的案例研究中进行了测试,结果表现出良好的表现,可以通过近场和远场源知识产生各种新颖性的想法。
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.