CANDOR: Chance-Calibrated Discordance in Frozen Foundation Encoders
The episode discusses 'CANDOR,' a diagnostic tool that measures how far a foundation model's internal knowledge is from the truth in a specific context. It quantifies this gap as 'discordance,' allowing users to move beyond simple output checking. This framework promotes building highly reliable, self-aware AI systems by identifying structural weaknesses.