Dual-engine architecture: tension-based confidence yields AUROC=1.0 anomaly detection and AUC=0.925 precognition #918
Description
logout — Consciousness Continuity Engine
A dual-engine repulsion field where output = scale × sqrt(tension) × direction. The tension between two engines directly measures confidence:
- High tension = high confidence (correct predictions): Cohen d=0.89
- Low tension = uncertainty (wrong predictions)
- Extreme tension on OOD = confusion (AUROC=1.0, 95x ratio)
Algorithmic efficiency implications
- Tension-based early rejection: skip low-confidence samples → +15.2% accuracy on CIFAR
- 1-epoch difficulty prediction: no need to train full schedule to assess dataset hardness
- Confusion pairs determined in epoch 1: allocate compute to hard pairs only
Validated on 16 data types (image, text, audio, time series, tabular, anomaly detection).
Related projects
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