Microsoft Technology Licensing, LLC

Kuleen Haresh Mehta

Alan Mark Thomas

Matthew D Wood

Michael Francis Palermiti, Ii

Poonam Ganesh Hattangady

Caleb Whitmore

Matheus Camasmie Pavan

Anton Oguzhan A Andrews

Erich Jose Martino Pena

An electronic message computing system tracks new activity items that reflect activities that have not yet been seen by the user. A. generative artificial intelligence (AI) model generates a digest summary that is provided to the user the next time the user accesses the electronic message system. The digest summary summarizes new activity. The generative AI model also generates importance summaries that summarize the importance of a particular activity to the user, and content summaries that summarize the content of an activity item (such as an electronic mail message). The electronic messaging system also assigns a priority to each new activity item and provides the summaries, along with a priority, to a client computing system. The client computing system conducts a user experience, navigating the user through the new activity items, based upon the priority assigned by the electronic message computing system.

Electronic message system with artificial intelligence (AI)-generated personalized summarization

Methods and systems for generating automation rules based on natural language inputs. In an example, the technology relates to a computer-implemented method for generating automation rules from natural language input. The method includes receiving a natural language input into a communications application for performing an action on communications received by the communications application; providing the natural language input into a trained machine learning model; receiving, as output from the trained machine learning model, a tagged primitive and an identified action from the natural language input; generating an automation rule for performing the action on a subset of communications received by the communications application, the subset of communications corresponding to the tagged primitives; and executing the generated automation rule to perform action on the subset of communications.

Natural language understanding for creating automation rules for processing communications

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Sammamish, WA, United States of America

Kuleen Haresh Mehta