Abstract
Design intelligence is an important branch of artificial intelligence (AI), focusing on the intelligent models and algorithms in creativity and design. In the context of AI 2.0, studies on design intelligence have developed rapidly. We summarize mainly the current emerging framework of design intelligence and review the state-of-the-art techniques of related topics, including user needs analysis, ideation, content generation, and design evaluation. Specifically, the models and methods of intelligence-generated content are reviewed in detail. Finally, we discuss some open problems and challenges for future research in design intelligence.
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Acknowledgements
Figs. 5c, 5d, and 8 in this study were generated by the pre-trained models of Runway toolkit (https://runwayml.com).
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Yong-chuan TANG, Jiang-jie HUANG, Meng-ting YAO, Jia WEI, Wei LI, Yong-xing HE, and Ze-jian LI declare that they have no conflict of interest.
Project supported by the National Science and Technology Innovation 2030 Major Project of the Ministry of Science and Technology of China (No. 2018AAA0100703), the National Natural Science Foundation of China (Nos. 61773336 and 91748127), the Chinese Academy of Engineering Consulting Project (No. 2018-ZD-12-06), the Provincial Key Research and Development Plan of Zhejiang Province, China (No. 2019C03137), and the Ng Teng Fong Charitable Foundation in the form of ZJU-SUTD IDEA Grant
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Tang, Yc., Huang, Jj., Yao, Mt. et al. A review of design intelligence: progress, problems, and challenges. Front Inform Technol Electron Eng 20, 1595–1617 (2019). https://doi.org/10.1631/FITEE.1900398
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DOI: https://doi.org/10.1631/FITEE.1900398