How AI can Harmonize and Increase Efficiency with Industrial Design: A Case Study from Ai's Initial Exploration to its Professional Application

DOI

10.2991/978-2-38476-323-8_48How to use a DOI?

Keywords

Human-AI collaboration; Industrial design; AI platforms; Intention images; Creative output; Design efficiency

Abstract

This study examines the current status and future mechanisms of human-intelligence collaboration in industrial design, highlighting the instability and efficiency issues of existing AI platforms (e.g., MJ and SD). While AI can generate numerous intention diagrams, designers must balance creative dispersion with focused direction. The study suggests developing a proprietary AI engine and underscores the designers’ feedback role and the importance of intention maps. It concludes that two-way feedback mechanisms, instrumental reinforcement, and dataset specialization will optimize design efficiency and creative output in the future.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Min Zhang
PY  - 2024
DA  - 2024/12/23
TI  - How AI can Harmonize and Increase Efficiency with Industrial Design: A Case Study from Ai's Initial Exploration to its Professional Application
BT  - Proceedings of the 2024 7th International Conference on Humanities Education and Social Sciences (ICHESS 2024)
PB  - Atlantis Press
SP  - 411
EP  - 417
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-323-8_48
DO  - 10.2991/978-2-38476-323-8_48
ID  - Zhang2024
ER  -