Dynamically adapting assistant responses

A computing system, comprising:

• one or more processors, and
• memory configured to store instructions that, when executed by the one or more processors, cause the one or more processors to perform a method that includes:
• selecting a familiarity training instance, from a set of familiarity training instances,
• wherein the familiarity training instance includes an input parameters portion and a ground truth familiarity measure for the input parameters portion,
• wherein the input parameters portion includes one or more measures of user interactions with an automated assistant, including one or more intent specific measures that are based on historical interactions, of a user with the automated assistant, for one or more intents;
• processing the input parameters portion of the selected familiarity training instance using a machine learning model to generate a predicted familiarity measure for the input parameters portion, wherein the predicted familiarity measure is indicative of familiarity of the user with the one or more intents;
• comparing the predicted familiarity measure with the ground truth familiarity measure to generate familiarity output;
• and
• updating one or more portions of the machine learning model based on the familiarity output.