Cooperatively operating a network of supervised learning processors to concurrently distribute supervised learning processor training and provide predictive responses to input data

Abstract

A supervised learning processing (SLP) system and non-transitory, computer program product provides cooperative operation of a network of supervised learning processors to concurrently distribute supervised learning processor training, generate predictions, and provide prediction driven responses to input objects, such as NL statements. The SLP system includes SLP stages that are distributed across multiple SLP subsystems. Concurrently training SLP's provides accurate predictions of input objects and responses thereto, the SLP system and non-transitory, computer program product enhance the network by providing high quality value predictions and responses and avoiding potential training and operational delays. The SLP system can enhance the network of SLP subsystems by providing flexibility to incorporate multiple SLP models into the network and train at least a proper subset of the SLP models while concurrently using the SLP system and non-transitory, computer program product in commercial operation.