About the Global Seismic Intelligence Network (GSIN)

The Architect's Vision

GSIN was created by Kent "The Architect" Stone, a U.S. Army veteran and independent AI engineer who set out to build a global earthquake forecasting system—without a lab, grant, or supercomputer. Operating from a coastal apartment in Perú, Kent engineered a fully autonomous AI stack that could process seismic telemetry, forecast crustal stress, and identify real-time earthquake swarms using consumer-grade hardware.

In early 2025, GSIN's Autonomic Training Engine (A.T.E.)achieved a world-first: training a physics-informed 3D U-Net–LSTM model on a single RTX 5080 GPU, reproducing continental-scale stress-field behavior validated by geophysical benchmarks.

GSIN's breakthrough demonstrated that earthquake forecasting isn't a luxury reserved for billion-dollar labs—it’s a solvable engineering problem. By merging AI physics simulation with open geophysical data, Kent proved that pattern recognition can reveal pre-seismic anomalies days before major events.

Identifying a Seismic Swarm

In mid-2025, the GSIN models detected an anomalous clustering pattern off the coast of the Philippines. Using the PlateVision subsystem, a multi-modal neural inference pipeline built by Kent, the system flagged a “normal swarm” sequence—fifteen distinct micro-events culminating in a M6.7 shock within 6.2 hours.

This detection validated GSIN's autonomous event-classification pipeline, integrating continuous waveform ingestion, automatic clustering via cosine-distance embeddings, and on-the-fly geospatial labeling. The swarm dataset became the first field confirmation of the A.T.E. system's real-world inference stability.

Technology Stack

Reference Hardware

GSIN runs entirely on consumer hardware. Its purpose is to prove that accessible AI systems can perform scientific research at the frontier of geophysics—without institutional gatekeeping.