Real-time AI hallucination detection using physics-inspired semantic uncertainty analysis
Test our semantic uncertainty engine with real examples
Click "Analyze" to see semantic uncertainty detection in action
Quantum-inspired uncertainty principle applied to semantic analysis with Golden Scale calibration for real-world applications
Δμ (Precision): Measures semantic stability and consistency across interpretations
Δσ (Flexibility): Quantifies adaptability and contextual variability
High hallucination risk - Block content
Uncertain content - Human review required
Legitimate content - Approve
Chain ID: 16600 (0G Newton Testnet)
Real blockchain transaction support with verification hashes
~38K gas per verification
$0.0002 cost with 95%+ batch savings
Content hashing and on-chain storage
Immutable verification history
The Semantic Uncertainty Firewall represents a breakthrough in AI safety and content verification. By applying physics-inspired uncertainty principles to semantic analysis, we've created the first production-ready system capable of detecting AI hallucinations at web scale.
Our quantum-inspired semantic uncertainty metric (ℏₛ) provides objective, quantifiable measures of content reliability. Benchmarked at 85.3% AUROC on TruthfulQA with 0.147 Brier score calibration while maintaining sub-millisecond processing latency.