Paper
23 May 2023 Research on artificial intelligence product design method based on product semantics
Zonghua Zhu
Author Affiliations +
Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260428 (2023) https://doi.org/10.1117/12.2674615
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China
Abstract
With the development of Internet of Things, cloud computing, big data and other information technologies, the design objects and design methods have changed greatly. In order to meet the development direction of the times, this paper studies and analyzes the product design method of artificial intelligence based on product semantics. Firstly, this paper analyzes the design method and theoretical basis of product semantics, and then makes an in-depth research and analysis on the formation of artificial intelligence technology, including detailed discussion and planning of behaviorism, connectionism and symbolism of AI. Finally, it expounds the method of using artificial intelligence technology in product semantics design. By making full use of network technology, big data and artificial intelligence technology, a user model which is more in line with the user's thinking is established, and the application and development of artificial intelligence in product semantics are promoted.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zonghua Zhu "Research on artificial intelligence product design method based on product semantics", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260428 (23 May 2023); https://doi.org/10.1117/12.2674615
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Artificial intelligence

Design and modelling

Product engineering

Semantics

Deep learning

Machine learning

Artificial neural networks

Back to Top