Decoupling memory and computation to enable privacy across multiple knowledge bases of user data

Abstract

Systems and methods are provided herein for utilizing a knowledge base to improve online automated dialogue responses based on machine learning models. Contextual customer data stored in external memory may be used for retraining a machine learning model to incorporate new observations into the model and to reduce bias and/or improve fairness in associated automated responses without having to retrain an entire memory architecture. The disclosed technology may improve the accuracy of machine learning models by using potentially private contextual customer data to inform the model while eliminating the ability of an intruder to access such data when the model is utilized in cloud-based services.