Dr. Jerry Smith's article explores using social network analysis and percolation theory to detect "left-of-X" events—precursors to major disruptions. The analysis focuses on identifying vulnerabilities within networks by examining node centrality, community structures, and the cascading effects of removing nodes or connections. The goal is early identification of instability to enable timely intervention and prevent catastrophic outcomes. The article uses network science concepts like degree, betweenness, and eigenvector centrality to reveal hidden power dynamics and influential actors. Several academic references support the theoretical framework.

Left-of-X Event Detection

In-Depth Explorations of Neuroscience-Inspired Architectures Revolutionizing AI.

New tracks tagged #left-of-x