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用于可视化的生成式人工智能:机遇与挑战。

Generative AI for Visualization: Opportunities and Challenges.

作者信息

Basole Rahul C, Major Timothy, Basole Rahul C, Ferrise Francesco

出版信息

IEEE Comput Graph Appl. 2024 Mar-Apr;44(2):55-64. doi: 10.1109/MCG.2024.3362168.

Abstract

Recent developments in artificial intelligence (AI) and machine learning (ML) have led to the creation of powerful generative AI methods and tools capable of producing text, code, images, and other media in response to user prompts. Significant interest in the technology has led to speculation about what fields, including visualization, can be augmented or replaced by such approaches. However, there remains a lack of understanding about which visualization activities may be particularly suitable for the application of generative AI. Drawing on examples from the field, we map current and emerging capabilities of generative AI across the different phases of the visualization lifecycle and describe salient opportunities and challenges.

摘要

人工智能(AI)和机器学习(ML)的最新发展催生了强大的生成式人工智能方法和工具,这些方法和工具能够根据用户提示生成文本、代码、图像和其他媒体。人们对这项技术的浓厚兴趣引发了关于哪些领域(包括可视化)可以通过此类方法得到增强或替代的猜测。然而,对于哪些可视化活动可能特别适合应用生成式人工智能,人们仍然缺乏了解。借鉴该领域的实例,我们梳理了生成式人工智能在可视化生命周期不同阶段的当前和新兴能力,并描述了显著的机遇和挑战。

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