Microsoft Technology Licensing, LLC

Robyn Elizabeth Dunn

Mahesh Suresh Yadav

Donghee Pi

Michael J Patten

Christopher Doan

Ross Nathaniel Luengen

Richard Fang

Phoi Heng Lew

Brian Eric Uphoff

Scott James Krieder

Darren Christopher Laybourn

A machine learning (ML) operating mode is selected for a camera. A physical orientation of a housing of a camera is determined. In response to determining the orientation, an operating mode from a set of operating modes is selected. The set of operating modes includes at least a ML inference mode and a ML training mode. Based on the selected operating mode, images obtained by an image capturing unit are processed. In the ML inference mode, a ML controller applies a ML model to the images to infer or predict characteristics of the image (e.g., detecting objects within the images). In the ML training mode, the ML controller is configured to cause a ML model to be trained using images captured by the image capturing unit, either local to the camera or on a remotely located computing device.

Machine learning operations on different location targets using camera orientation

Techniques for a contextual new tab experience in a heterogeneous tab environment are described. In at least some implementations, relevant content associated with a user's current task is determined based on contextual information collected from tabs presented in a heterogeneous tab environment. According to various implementations, a new tab is launched displaying the relevant content in the heterogeneous tab environment. Thus, contextually relevant content can be determined from a current task and displayed in a single location via a heterogeneous tab environment.

Contextual new tab experience in a heterogeneous tab environment

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Robyn Elizabeth Dunn