Abstract: A computer-implemented method includes: learning, by a computer device, a delivery for response content in view of types of queries; awakening, by the computer device, in response to receiving an activation command; receiving, by the computer device, a query; determining, by the computer device, a context of the query; determining, by the computer device, a digestibility of a response to the query; and determining, by the computing device, to output a response to the query as one of an audio response, a displayed response, and an audio response and a displayed response to the user, wherein the determining is based on the learning, the determined context of the query, the determined digestibility of the response, and the preferences of the user for receiving the response.

Abstract: A computer-implemented method includes: learning, by a computer device, a delivery for response content in view of types of queries; awakening, by the computer device, in response to receiving an activation command; receiving, by the computer device, a query; determining, by the computer device, a context of the query; determining, by the computer device, a digestibility of a response to the query; and determining, by the computing device, to output a response to the query as one of an audio response, a displayed response, and an audio response and a displayed response to the user, wherein the determining is based on the learning, the determined context of the query, the determined digestibility of the response, and the preferences of the user for receiving the response.

Abstract: A computer-implemented system and method comprises tagging media information obtained in response to a user action of a user, storing user event information regarding a further user action related to the tagged media information, and training a machine learning engine with the user event information and the tagged media information. The method further comprises capturing IoT data associated with the user, determining whether the captured IoT data meets a relevance threshold utilizing the machine learning engine, and responsive to meeting the relevance threshold, saving the captured IoT data as relevant captured data in an IoT relevant data store. The method further comprises receiving search criteria from the user to search for data meeting the search criteria, modifying the search criteria utilizing the machine learning engine and the user history, and returning search results for display on the user device based on the modified search criteria.