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The linked article is about an introduction to Graph Neural Networks (GNNs). It explains the basics of GNNs, how they work, and their applications. The article covers the key concepts of how GNNs leverage the structure of graph data, the types of GNN architectures, and the challenges and limitations of these models. It provides a comprehensive overview of this emerging field of deep learning, which has applications in areas such as social network analysis, drug discovery, and recommendation systems.