Patent ID: 11948083
Assignee: UMNAI LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 23:
24. The method of claim 1, further comprising forming an explainable first model using a black-box first model; forming a discriminator using the second model, and measuring a loss function between the second model and the explainable model, and wherein the explanation comprises an identification of a potential bias, performance effects, causal effects and risk effects or anomaly, wherein the second model is configured to combine the training dataset with a plurality of samples generated from the first model and generate a probability to indicate if the samples were retrieved from the training dataset, and
constantly monitoring one or more of the explainable model, first model, or second model to detect one or more of: anomalous behavior, instances of data drift and OOD instances, abnormal deviations from nominal operational cycles, or to analyze and assess behavior under OOD and anomalous instances, variation, deviation, performance and resource usage monitoring, or a phase-space.