From Rules to Relationships: How Machines Are Learning to Understand Each Other

This article explores the evolution of communication systems from simple data transmission to intelligent information sharing, highlighting the limitations of traditional systems in machine-to-machine communication. Semantic communication is introduced as a solution, focusing on transmitting meaning rather than raw data to reduce unnecessary bandwidth usage. The article contrasts Semantic Knowledge Base (SKB) systems with knowledge graph-based semantic communication, explaining how SKBs struggle with unknown scenarios due to their reliance on predefined categories. Knowledge graphs overcome these limitations by encoding relationships between nodes, enabling systems to reason through unfamiliar situations and make more contextually aware decisions, improving accuracy in diverse environments.