Unlock AI’s True Potential with STLE! 🌟
Welcome to a breakthrough in AI understanding—STLE (Set Theoretic Learning Environment). This innovative framework teaches AI systems to recognize what they don’t know, preventing overconfidence in unfamiliar scenarios.
Key Features:
- Explicit Uncertainty Quantification: Model uncertainty directly through fuzzy sets.
- Production-Ready: Fully validated, efficient implementation in NumPy and PyTorch.
- Performance Metrics:
- Out-of-Distribution (OOD) Detection: AUROC of 0.668 without OOD training!
- Classification Accuracy: 81.5% with identified learning frontiers.
Real-World Applications:
- Medical AI: Deferring uncertain diagnoses to human experts.
- Autonomous Vehicles: Engaging safe modes for unfamiliar situations.
With STLE, AI learns to be humble—an essential step toward Artificial General Intelligence (AGI).
👉 Join us on this journey! Star our GitHub repo for updates, and feel free to share your insights. Let’s revolutionize AI together! 🚀
