Microsoft Technology Licensing, LLC

Brandon H Paddock

Manav Mishra

Priya Vaidyanathan

Edward Boyle Averett

Richard Jacob White

Dona Sarkar

Stephanie M Monk

Wentao Chen

Brian Eric Uphoff

Yin Liu

Derek S Gebhard

Christopher J Guzak

Relja Ivanovic

Daniel Oliver

Benjamin Betz

Ramaswamy Krishnan-Chittur

Benjamin A Betz

Daniel J Oliver

Jesse Clay Satterfield

Michael Jay Gilmore

Rolf Arnold Ebeling

Steve Ickman

Tom Laird-McConnell

Marc Wautier

Paul Luo Li

Brendan D Elliott

James H Dooley, Iv

Xiaoyu Chai

Kwong K Leung

Arun Gurunathan

Minsuk Kang

Frederick Douglass Campbell

Neeraja Abburu

Jilong Liao

Irina Ioana Niculescu

Ho Jeannie Chung

Brian E Uphoff

A system level search module receives system level search user interface registration information for an application of the computing device. The registration information includes an indication of how the system level search module can launch the application. The registration information is added to a registration store, and the application is included as one of one or more applications that can be searched using the system level search user interface.

Registration for system level search user interface

A server computing device generates training data based upon an identifier for a device, a timestamp, and a label received from a developer computing device. The server computing device trains a computer-implemented machine learning (ML) model based upon the training data. The server computing device also generates client configuration data for the ML model that specifies transformations that are to be applied to values in order to generate input values for the ML model. The server computing device deploys ML assets to client computing devices, the ML assets comprising the ML model and the client configuration data. The client computing devices execute the ML model using input values derived via transformations of (local) values produced by the client computing devices and transmit telemetry data to the server computing device. The server computing device updates the ML assets based upon the telemetry data.

Computing system for training, deploying, executing, and updating machine learning models

Techniques for application activation are described herein. An operating system (OS) can be configured to incorporate various extension points that are serviceable through contracts defining individual invocations of extensible functionality. The extensible functionality is integrated as part of the OS and controlled by the OS in a centralized manner. However, the specific implementations of the extensible functionally are offloaded to applications using the contracts. For example, the OS can include or otherwise make use of a centralized application activation component that employs an object-oriented approach to invoke applications to perform particular contracts. The application activation component can pass information describing a particular contract to activate a designated application and enable the application to service the contract in the manner specified by the OS. In this way, the manner in which contracts are handled by application code can be managed and coordinated through a centralized application activation component.

Application activation framework

A system level search user interface that includes both a data entry portion and an application identification portion is displayed. User data input as a search term is displayed in the data entry portion, and identifiers of each of one or more applications of multiple applications on the computing device that can be searched using the search term are displayed in the application identification portion. The search term is provided to one application of the multiple applications for that one application to generate and display search results based on the search term while the display of at least the data entry portion of the system level search user interface is maintained.

System level search user interface

Computer-readable media, systems, and methods for enabling a rich client search experience. In embodiments, a description is received from a data store. The description includes fields of information existing on the data store that are capable of being searched. A user interface is built based on the description and the user interface provides a user with a mechanism for searching the data store. And the user interface is presented to the user. The description is definable by the data store using a data-driven extension, allowing the data store to express schema and query capability information to a client and allowing the client to dynamically customize the user interface based upon the schema and query capability information expressed by the data store.

Rich client search experience

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Seattle, WA, United States of America

Brandon H Paddock