In this episode, explore how graph-based representations have evolved—from Euler’s foundational graphs to today’s powerful Graph Neural Networks and knowledge graphs—revealing how these structures enable deep learning models to understand complex relationships, support reasoning, and underpin advanced applications like fraud detection, predictive analytics, and semantic search. Discover the role of techniques like graph embeddings, temporal knowledge graphs, and transformer architectures in turning interconnected data into actionable insights for modern enterpriseshttps://blog.datamatics.com/from-euler-to-ai-transforming-graphs-into-a-powerhouse-for-knowledge-representation