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Ontology-supported AI Model and Dataset Management· 支持本体的AI模型和数据集管理

Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling transparent comparisons, and fostering a more profound understanding of AI. In that process, different organizations generate and use plenty of assets that need to be tracked, traced and managed. Moreover, it is important to discover assets relevant for the task at hand. This paper presents research aiming to contribute to answering the question of what is required to exchange and manage AI models and related assets effectively without semantic gaps in an industrial context. We introduce a platform for AI model exchange, which facilitates the usage, exchange, and analysis of AI models and datasets. The platform incorporates an ontology that can

AI 解读论文

工业背景下有效管理AI模型和数据集的本体支持平台

核心方法
引入一个基于本体的平台,用于AI模型和数据集的使用、交换和分析
适合谁读
研究者 / 工程师
要解决的问题
解决工业环境中AI模型及相关资产的高效交流与管理问题,避免语义鸿沟
关键实验
未提供
主要贡献
提供了工业AI模型管理的有效方法,促进透明比较和更深层次理解
意义与局限
意义在于提高工业AI应用的透明性和可管理性,影响较大,但可能局限于特定行业
领域:cs.AI作者:Jan Novacek、Ali Ahari、Tobias Müller
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