In terms of 'stress-testing' an AI, what is the precise method to determine the 'breaking point' where noisy or corrupted input data causes the confidence score to drop below the required acceptance threshold?

To find the breaking point of an AI, you use a process called stress-testing. First, you take a clean, correct piece of data that the AI is currently getting right. Then, you add small, controlled amounts of noise to it. Think of this like adding a little bit of static to a clear radio station until you can no longer hear....