Determining intents and responses using machine learning in conversational ai systems and applications

Abstract

In various examples, hybrid models for determining intents in conversational AI systems and applications are disclosed. Systems and methods are disclosed that use a machine learning model(s) and a data file(s) that associates intents with one another (e.g., using a tree-like structure) in order to determine a final intent associated with text. For example, the text may initially be processed using the machine learning model(s) (e.g., a first machine learning model) in order to determine a first intent associated with the text. The data file(s) may then be used to determine information (e.g., anchors) for one or more second intents (e.g., one or more sub-intents) that are related to the first intent. The text and the information may then be processed using the machine learning model(s) (e.g., a second machine learning model) to determine a second intent, from the one or more second intents, that is associated with the text.