Abstract: Machine learning model personalization systems and techniques are described. For instance, a system receives input data through a discovery user interface. The input data includes answers from a subject. The answers are associated with questions, and include subject-specific information that is specific to the subject. The system parses and/or processes the input data to generate model personalization data (e.g., training data). The system modifies a trained machine learning model using the model personalization data to generate a personalized machine learning model that is personalized to simulate the subject. The system receives a message through a conversational user interface. The system generates a response to the message using the personalized machine learning model. The response is generated to simulate the subject, for instance by being generated to include at least a subset of the subject-specific information. The system outputs the response through the conversational user interface.

Abstract: A method and system for providing customer service over a packet switched network wherein an operator interactively responds to messages from customers by sending messages over the network. Additionally, the invention is directed to storing the messages in a database and retrieving them for an examination of the level of customer service provided. The invention also allows customers to leave messages to operators who can retrieve the messages via the packet switched network, preferably by means of a web browser.