Graph Neural Networks (GNNs): AI Beyond Grids Meta Description : Explore the world of Graph Neural Networks (GNNs), their unique capabilities beyond traditional grids, and applications in social networks, molecular biology, and recommendation systems. Introduction Artificial intelligence has primarily revolved around data structures like grids, sequences, and tables. However, many real-world problems are best represented as graphs—a collection of nodes and edges that capture relationships between entities. Graph Neural Networks (GNNs) have emerged as a powerful AI tool to handle graph-structured data, providing insights into areas ranging from social networks to molecular biology. This blog dives into what GNNs are, their working principles, transformative applications, and why they represent a leap forward for AI's capability to understand complex relationships. What Are Graph Neural Networks? Graph Neural Networks are a class of machine learning models designed to proc...
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