Fault-Tolerant Design of AI Models

Hallucination Prevention in Super Alignment Engineering

• Model Calibration: Regular calibration of AI models to prevent decision-making errors caused by data bias or overfitting.

• Human-AI Collaboration: Critical decisions involve human expert review to ensure AI judgments align with real-world scenarios.

• Multi-Model Validation: Multiple AI models are used for decision-making, cross-validating each other to reduce the risk of errors from a single model.

Exception Handling Mechanisms

• Error Detection and Correction: The AI system can detect abnormal states and attempt automatic corrections.

• Log Recording and Auditing: AI decision-making processes are logged in detail, enabling post-event analysis and accountability tracking.