Model Learning
Model Learning tracks every event where reality surprised GNI's predictions — and how the system responded. When a Black Swan event occurs, source weights are recalibrated, prompt templates are adjusted in the A/B system, and the adaptive pipeline modifies its escalation thresholds. This page will document GNI's learning trajectory, showing measurable improvement in prediction accuracy over time.
- •Surprise outcome registry — events that defied all 4 agents
- •Source bias corrections triggered by systematic errors
- •A/B prompt template evolution history
- •Escalation threshold recalibration log
- •Accuracy improvement trend across pipeline generations
This page requires verified prediction data from the GPVS system. The earliest MAD predictions were made in March 2026 with verify dates starting April 10, 2026. As predictions verify over time, this page will automatically populate with real accuracy data. No manual intervention is needed — GNI's autonomous pipeline handles verification and scoring automatically.