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ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI in Business
Volume 7 - 2024 |
doi: 10.3389/frai.2024.1460217
This article is part of the Research Topic Large Language Models in Work and Business View all 4 articles
Towards Enhanced Creativity in Fashion: Integrating Generative Models with Hybrid Intelligence
Provisionally accepted- 1 MSU, Moscow, Russia
- 2 ELSE Corp., Milano, Italy
This study offers several important insights into the role and potential use of large language models (LLMs) and generative intelligence in the fashion industry. The implementation of these technologies can significantly transform traditional approaches to design, production, and retail, providing new avenues for innovation, product personalization, and enhanced customer interaction. However, the study also identifies several limitations and challenges associated with the application of LLMs in the fashion industry, including the need for further model improvement to better understand spatial parameters and design details. One of the key areas for future research and development is the integration of LLMs into fashion industry workflows to maximize their potential and overcome existing limitations. This includes developing new approaches for iterative design enhancement based on hybrid intelligence, as well as creating more effective tools for personalization and customer interaction.
Keywords: linguistic models (LLMs), generative intelligence (GI), Fashion industry, Hybrid intelligence, co-design
Received: 05 Jul 2024; Accepted: 26 Aug 2024.
Copyright: © 2024 Ryjov, Golub and Egorova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Alexander Ryjov, MSU, Moscow, Russia
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