Barum Rho

Barum Rho is a notable inventor based in Toronto, Canada. He has made significant contributions to the fields of artificial intelligence and model visualization. With a total of 3 patents, Rho's work focuses on enhancing the understanding of model behavior and generating adaptive explanations for AI outputs.

Latest Patents

One of Rho's latest patents is titled "Visualizing feature variation effects on computer model prediction." This innovative model visualization system analyzes model behavior to identify clusters of data instances with similar behavior. For a selected feature, data instances are modified to set the selected feature to different values evaluated by a model to determine corresponding model outputs. The feature values and outputs may be visualized in an instance-feature variation plot. The instance-feature variation plots for the different data instances may be clustered to identify latent differences in behavior of the model with respect to different data instances when varying the selected feature. The number of clusters for the clustering may be automatically determined, and the clusters may be further explored by identifying another feature which may explain the different behavior of the model for the clusters, or by identifying outlier data instances in the clusters.

Another significant patent is "Generating adaptive textual explanations of output predicted by trained artificial-intelligence processes." This patent includes computer-implemented processes that generate adaptive textual explanations of output using trained artificial intelligence processes. An apparatus may generate an input dataset based on elements of first interaction data associated with a first temporal interval. Based on an application of a trained artificial intelligence process to the input dataset, the apparatus generates output data representative of a predicted likelihood of an occurrence of an event during a second temporal interval. Furthermore, based on an application of a trained explainability process to the input dataset, the apparatus may generate an element of textual content that characterizes an outcome associated with the predicted likelihood of the occurrence of the event, where the element of textual content is associated with a feature value of the input dataset. The apparatus may also transmit a portion of the output data and the element of textual content to a computing system.

Career Highlights

Barum Rho is currently employed at the Toronto-Dominion Bank, where he applies his expertise in artificial intelligence and model visualization. His work contributes to the bank's innovative approaches in utilizing technology for enhanced decision-making processes.