Google Inc.

Golden Gopal Krishna

Devin Mancuso

Daniel June Hyung Park

Henry Owen Newton-Dunn

Miroslav Bojic

Mindy Pereira

Carl Magnus Borg

Jacob M Klinker

Lily Sin

Clement Wright

Carsten Hinz

Sarah Fay Smith

Rosemary Margaret La Prairie

Shadia Walsh

Zhipeng Pan

Stacy Lou Chiou

Simon Edward Roberts

Visual search in an operating system of a computing device can process and provide additional information on the content being provided for display. The computing device can include an operating system that includes a visual search interface that obtains and processes display data associated with content currently being provided for display. The visual search interface can generate display data based on the current content provided for display, process the display data with one or more on-device machine-learned models, and provide additional information to the user. The visual search interface may transmit data associated with the display data to perform additional data processing tasks. Application suggestions may be determined and provided based on the visual search data.

Visual search interface in an operating system

This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.

Suggesting actions based on machine learning

Application prediction based on a visual search determination

This document describes techniques and devices for a refined search with machine learning. These techniques improve computer-aided searches through enabling selection of search criteria used in a prior search and providing a refined search result based on that selection. Furthermore, a machine-learning component of a search engine can be altered to improve future search results based on the selection and an indication of the desirability of the refined search result.

Refined search with machine learning

Display screen or portion thereof with a graphical interface

Display screen or portion thereof with an animated graphical interface

This document describes techniques and devices for task-related sorting, application discovery, and unified bookmarking for application managers. Through use of an application manager, multiple applications (including standalone applications, instant applications, websites, and other content) that a person can use to accomplish a single task, or multiple related tasks, are sorted into discrete groups for display in the application manager. The application manager can automatically recognize relationships between activities performed with the applications and recognize user actions with the applications that are related to the activities. Based on the relationships and user actions, the application manager can automatically determine that the activities and actions represent a task and display a task group that includes the applications that represent the task. The task groups may be visually displayed as a stack, strip, or pile of windows or thumbnails representing each application or other content the person could use for the task.

Task-related sorting, application discovery, and unified bookmarking for application managers

Growing community of inventors

Berkeley, CA, United States of America

Golden Gopal Krishna