Victor Calibration: Enhancing AI Model Confidence and Governance Through Multi-Pass Analysis

This research focuses on improving the calibration of AI model confidence and addresses governance challenges. The use of 'round-table orchestration' suggests a collaborative approach to stress-testing AI systems, potentially improving their robustness.

• •Focuses on improving AI model confidence through calibration techniques.
• •Addresses governance aspects related to AI systems, likely including safety and fairness.
• •Employs a 'round-table orchestration' approach, suggesting collaborative analysis.