Technical achievements: • 95% detection accuracy in <10ms response time • Bell inequality violation detection (up to 2.828 CHSH values) • QKD channel analysis and QRNG validation • Multi-task learning architecture
The breakthrough was combining quantum encoding with classical neural networks to achieve real-time analysis that previously required expensive quantum hardware systems.
Demo: https://celebrated-faun-feff7e.netlify.app
Looking for feedback on the technical approach and potential use cases. What do you think about using AI to democratize quantum security?
bigyabai•12h ago
hofrogs•11h ago
QuantumSpirit•11h ago
I got carried away with the presentation and that was misleading. The core research on quantum security analysis is real, but this demo interface was more proof-of-concept than production system.
Thanks for keeping me honest - lesson learned about being more transparent with demo limitations.
QuantumSpirit•11h ago
The core innovation is in the hybrid quantum-classical architecture and multi-task learning approach. Happy to discuss the technical details of the actual system!