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为了在时尚中增强创造力:将生成模型与混合智能集成在一起
Alexander Ryjov1, Vagan Kazaryan2, Andrey Golub3
1Department of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia.
Frontiers in artificial intelligence
|October 14, 2024
概括
大型语言模型 (LLM) 和生成智能正在改变时装设计,生产和零售. 虽然有希望,但LLM需要增强空间理解和设计工具,以充分发挥时尚行业的潜力.
科学领域:
- 人工智能的人工智能
- 时尚技术 时尚技术 时尚技术
- 计算设计的计算设计.
背景情况:
- 大型语言模型 (LLM) 和生成智能正在越来越多地影响各种行业.
- 时装行业正在探索人工智能用于设计,生产和零售方面的创新.
- 当前的时尚LLM应用在理解空间参数和设计复杂性方面存在局限性.
研究的目的:
- 探索时尚行业中LLMs和生成智能的作用和潜力.
- 在时尚工作流程中分析LLM的当前应用和局限性.
- 提出一种混合情报方法来应对已确定的挑战.
主要方法:
- 分析当前的时尚LLM应用程序.
- 识别空间理解和设计细节处理中的局限性.
- 为时尚应用提供混合智能框架的建议.
主要成果:
- 法学士在时尚领域展示了创新,个性化和增强客户互动的巨大潜力.
- 关键的局限性包括需要改进空间理解和用于代设计的工具.
- 建议采用混合智能方法来克服当前的LLM限制.
结论:
- 士课程为时尚行业提供了巨大的机会.
- 需要进一步发展,以提高LLM在空间推理和设计方面的能力.
- 未来的研究应该专注于混合智能解决方案,以充分利用AI在时尚领域.
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