Microsoft Technology Licensing, LLC

Elwha LLC

Steven Nabil Bathiche

Kenneth Paul Hinckley

Andrew David Wilson

Paul Henry Dietz

Timothy Andrew Large

James H Cauthorn

Anoop Gupta

Vivek Pradeep

Lowell L Wood, Jr

Roderick A Hyde

Clarence T Tegreene

Jordin T Kare

Charles Whitmer

Jaron Zepel Lanier

Nigel Stuart Keam

Edward K Y Jung

Victoria Y H Wood

Carl J Ledbetter

William Henry Gates, Iii

Alistair K Chan

Shahram Izadi

William Hong Vong

Hugh E McLoone

Boyd Cannon Multerer

Karlton David Powell

Muriel Y Ishikawa

Michael Jack Sinclair

Hrvoje Benko

Flavio Protasio Ribeiro

Stephen Edward Hodges

Desney S Tan

Steven W Fisher

Jonathan A Hayes

Andreas Georg Nowatzyk

Adrian Travis

Panos Costa Panay

Neil Emerton

Sarah Graham Williams

Nathan P Myhrvold

David Bazeley Tuckerman

Robert C Petroski

Stephen G Latta

Jesse R Cheatham, Iii

Ralf Groene

Philip Andrew Eckhoff

Craig J Mundie

Kevin Geisner

Matthew Graham Dyor

Willem Den Boer

James Morris Alkove

Anthony Reed

Matthew Bret MacLaurin

William Thomas Blank

Mark William Casebolt

Glen C Larsen

Sasa Junuzovic

Christopher Andrew Whitman

Amir Netz

Steven T Kaneko

Hua Wang

Thomas Charles Oliver

Joseph Benjamin Gault

Bongshin Lee

Brett David Brewer

Randall Edward Aull

Firdosh Kersy Bhesania

William David Duncan

Aditha May Adams

Shai Guday

Dawson Yee

John R Lewis

Jonathan Westhues

Rajesh M Dighde

Kazuhito Koishida

Alice Jane Bernheim Brush

Ying Zheng

David William Voth

David Kim

John Clavin

Michael Bleyer

David Douglas Bohn

Young Soo Kim

Monique Chatterjee

Sing Bing Kang

Charles J Migos

William Jefferson Westerinen

John Allen Tardif

Jamie Daniel Joseph Shotton

Kurt Jenkins

Christopher Hugh Pratley

Craig Steven Ranta

David Alexander Butler

Daniel G O'Neil

Ashok Kuppusamy

Miller Thomas Abel

Shiraz Jitendra Cupala

Alain L Michaud

Nathan C Sherman

Gary Keith Starkweather

Andrew William Hill

Machine learning techniques are leveraged to provide personalized assistance on a computing device. In some configurations a timeline of a user's interactions with the computing device is generated. For example, screenshots and audio streams may be saved as entries in the timeline. Context—the state of the computing device when the entry is created, such as which documents and websites are open—is also stored. Entries in the timeline are processed by a model to generate embedding vectors. The timeline may be searched by finding the embedding vector that is closest to an embedding vector derived from a search query. The user may select a query result, causing the associated context to be restored. For example, if the query is 'show me all documents related to my upcoming trip to Japan', the query result may open documents and websites that were open when booking a flight to Japan.

User activity history experiences powered by a machine learning model

In some examples, systems and methods for formatting ink are provided. Ink stroke data may be received, letters may be identified from the ink stroke data, and spacing may be identified between the letters. A user command and semantic context may be received. An action may be determined based on the user command, the semantic context, and the spacing between the letters. Further, the action may be performed.

Advanced formatting of ink data using spatial information and semantic context

In some examples, systems and methods for generating predicted ink strokes, using ink-based semantics, are provided. Ink stroke data may be received, the ink stroke data and a semantic context may be input into a model. From the model, one or more predicted ink strokes may be determined. Further, an indication of the one or more predicted ink strokes may be generated.

Generating predicted ink stroke information using ink-based semantics

An intelligent assistant records speech spoken by a first user and determines a self-selection score for the first user. The intelligent assistant sends the self-selection score to another intelligent assistant, and receives a remote-selection score for the first user from the other intelligent assistant. The intelligent assistant compares the self-selection score to the remote-selection score. If the self-selection score is greater than the remote-selection score, the intelligent assistant responds to the first user and blocks subsequent responses to all other users until a disengagement metric of the first user exceeds a blocking threshold. If the self-selection score is less than the remote-selection score, the intelligent assistant does not respond to the first user.

Multi-user intelligent assistance

Aspects of the present disclosure relate to adjusting an illumination of a user depicted in one or more images when using a video conferencing application. In one example, one or more images depicting the user may be received from an image sensor. Further, an illumination of the user depicted in the one or more images may be determined to be unsatisfactory. For example, the user's face may be too bright or too dim. Accordingly, content displayed at a display device may identified and then modified. The modified content may then be rendered to a display device thereby changing the illumination of the user depicted in subsequent images. In examples, the modified content may include a graphical element, such as a ring of a specific color at least partially surrounding content rendered to and displayed at the display device.

Optimized facial illumination from adaptive screen content

Methods and systems for generating and using a semantic index are provided. In some examples, content data is received. The content data includes a plurality of subsets of content data. Each of the plurality of subsets of content data are labelled, based on a semantic context corresponding to the content data. The plurality of subsets of content data and their corresponding labels are stored. The plurality of subsets of content data are grouped, based on their labels, thereby generating one or more groups of subsets of content data. Further, a computing device is adapted to perform an action, based on the one or more groups of subsets of content data.

Generating and using a semantic index

A 'Concurrent Projector-Camera' uses an image projection device in combination with one or more cameras to enable various techniques that provide visually flicker-free projection of images or video, while real-time image or video capture is occurring in that same space. The Concurrent Projector-Camera provides this projection in a manner that eliminates video feedback into the real-time image or video capture. More specifically, the Concurrent Projector-Camera dynamically synchronizes a combination of projector lighting (or light-control points) on-state temporal compression in combination with on-state temporal shifting during each image frame projection to open a 'capture time slot' for image capture during which no image is being projected. This capture time slot represents a tradeoff between image capture time and decreased brightness of the projected image. Examples of image projection devices include LED-LCD based projection devices, DLP-based projection devices using LED or laser illumination in combination with micromirror arrays, etc.

Real-time mapping of projections onto moving 3D objects

A computing system, a method, and a computer-readable storage medium for adjusting eye gaze are described. The method includes capturing a video stream including images of a user, detecting the user's face region within the images, and detecting the user's facial feature regions within the images based on the detected face region. The method includes determining whether the user is completely disengaged from the computing system and, if the user is not completely disengaged, detecting the user's eye region within the images based on the detected facial feature regions. The method also includes computing the user's desired eye gaze direction based on the detected eye region, generating gaze-adjusted images based on the desired eye gaze direction, wherein the gaze-adjusted images include a saccadic eye movement, a micro-saccadic eye movement, and/or a vergence eye movement, and replacing the images within the video stream with the gaze-adjusted images.

Eye gaze adjustment

A connection device for computing devices is described. In one or more implementations, a connection device comprises a plurality of connection portions that are physically and communicatively coupled, one to another. Each of the plurality of connection portions has at least one communication contact configured to form a communicative coupling with a respective one of a plurality of computing devices and with at least one other communication contact of another one of the connections portions to support communication between the plurality of computing devices. Each of the plurality of connection portions also includes a magnetic coupling device to form a removable magnetic attachment to the respective one of the plurality of computing devices.

Connection device for computing devices

A system and method are disclosed for pairing computing devices using an authentication protocol that allows an initiating computing device to gain access to a secure, encrypted network of a target computing device.

Networked device authentication, pairing and resource sharing

A system for dynamic content delivery is provided. The system includes a control component to determine location, preferences, and state of a user. A delivery component dynamically selects and provides content to the user as a function of the user's location, preferences, and state.

Dynamic awareness involving location

Described herein is a multi-view display (based on spatial and/or temporal multiplexing) having an optimization mechanism that dynamically adjust views based upon detected state changes with respect to one or more views. The optimization mechanism determines viewing parameters (e.g., brightness and/or colors) for a view based upon a current position of the view, and/or on the multi-view display's capabilities. The state change may correspond to the view (a viewer's eye) moving towards another viewing zone, in which event new viewing parameters are determined, which may be in anticipation of entering the zone. Another state change corresponds to more views being needed than the display is capable of outputting, whereby one or more existing views are degraded, e.g., from 3D to 2D and/or from a personal video to a non-personal view. Conversely, a state change corresponding to excess capacity becoming available can result in enhancing a view to 3D and/or personal.

Optimization of a multi-view display

Growing community of inventors

Redmond, WA, United States of America

Steven Nabil Bathiche