The Evolution of Knowledge Graphs and AI Agents

The Evolution of Knowledge Graphs and AI Agents

The development of Knowledge Graphs (KG) is closely linked to the advancements in Artificial Intelligence (AI) agents. Starting from their static origins, knowledge graphs have evolved to include dynamic, temporal, and event-driven paradigms, each unlocking new capabilities for AI systems. This article explores their evolution and how Large Language Models (LLM) integrate into these advancements. … Read more

Dynamic Localization of Spatio-Temporal Graph Neural Networks

Dynamic Localization of Spatio-Temporal Graph Neural Networks

Spatio-temporal data is the foundation of many intelligent applications, revealing the causal relationships between measurements at a specific location and historical data from the same or other locations. In this context, Adaptive Spatio-Temporal Graph Neural Networks (ASTGNNs) have emerged as a powerful tool for modeling these dependencies, particularly through data-driven approaches rather than predefined spatial … Read more