At&t Intellectual Property I, L.p.

At&t Corp.

At&t Mobility Ii LLC

Xandr Inc.

Other

Hyundai Motor Company

Lucent Technologies Inc.

Kia Corporation

Nuance Communications, Inc.

Shopify Inc.

At&t Wireless Services, Inc.

Cingular Wireless Ii, LLC

At&t Wireless Svcs. Inc.

Lee Begeja

David Crawford Gibbon

Zhu Liu

Behzad Shahraray

Bernard S Renger

Eric Martin Zavesky

Andrea Basso

Raghuraman Gopalan

Benjamin J Stern

Pradeep K Bansal

Yadong Mu

Jeffrey Joseph Farah

Carroll W Creswell

Amy Ruth Reibman

Tan Xu

Jay Gordon Wilpon

Paul Triantafyllou

Kenneth H Rosen

Paul Van Vleck

Sumit Kumar

Mazin G Rahim

Patrick Guy Haffner

Allen Louis Gorin

Steven Hart Lewis

Jean-Francois Paiement

Harris Drucker

Richard Vandervoort Cox

Mitchell J Weinraub

Stephanie A Morrison

Robert Edward Markowitz

Charles Douglas Blewett

Neil A Ostroff

Rajesh Kapadia

Gary Lee Zamchick

Dilek Zeynep Hakkani-Tur

Gokhan Tur

Giuseppe Di Fabbrizio

Jianxiong Dong

Daniel Selig Furman

Donald J Youtkus

John Rotondo

John C Songrady

John A McMaster

Michael Joseph Haller

Thomas Wasilewski

Steven Neil Tischer

Timothy Innes

Robert J Andres

Samuel Seljan

Mohammed Abdel-Wahab

John Gerow Ramage

Ashutosh Sanzgiri

Ganesh K Subramaniam

Andrew J Berkley

Rittwik Jana

Steven Lloyd Greenspan

Narendra Kumar Gupta

Sarangarajan Parthasarathy

Yih-Farn Robin Chen

Karrie Jo Hanson

Gerald Michael Karam

Sandeep Sibal

Sanjay Agraharam

Richard Palazzo

Ram S Ramamurthy

Kenneth Mervin Huber

Murat Saraclar

Terrel Lecesne

Charles Alfred Lewis

Huale Huang

David Arthur Berkley

Bernard S L Renger

Giuseppe DiFabbrizio

Robert B Pladek

Anil Dass Chaturvedi

Daivd C Gibbon

Edward Chapman Durkee

Eric Zevesky

Mitchell S Mayer

Concepts and technologies disclosed herein are directed to machine learning model understanding as-a-service. According to one aspect of the concepts and technologies disclosed herein, a model understanding as-a-service system can receive, from a user system, a service request that includes a machine learning model created for a user associated with the user system. The model understanding as-a-service system can conduct an analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can compile, for the user, results of the analysis of the machine learning model in accordance with the service request. The model understanding as-a-service system can create a service response that includes the results of the analysis. The model understanding as-a-service system can provide the service response to the user system.

Machine learning model understanding as-a-service

Aspects of the subject disclosure may include, for example, a system and method for selecting media content for a group of persons located at a venue. The system and method identify a plurality of viewers in a vicinity of a venue that has one or more display devices from location data and extracts a content viewing preference of each viewer from their profile data. The process includes aggregating the content viewing preference of each of the plurality of viewers to generate an aggregated content profile. Based on the aggregated content profile, a list of content is generated. Next, a first group of viewers approaching a viewing range of a display device are sensed by imaging data. Any conflicts between content viewing preferences of the first group of viewers are detected and resolved based on weighting the viewing preferences of the group. Other embodiments are disclosed.

Automated content selection for groups

Devices, computer-readable media, and methods for providing an enhanced indication of an object that is located via a visual feed in accordance with a user context are disclosed. For instance, in one example, a processing system including at least one processor may detect a user context from a visual feed, locate an object via the visual feed in accordance with the user context, and provide an enhanced indication of the object via an augmented reality display.

Context-based object location via augmented reality device

A method for validating objects appearing in volumetric video presentations includes obtaining a volumetric video presentation depicting a scene, wherein the volumetric video presentation is associated with a metadata file containing identifying information for the scene, identifying user-generated content that depicts the scene, by matching metadata associated with the user-generated content to the metadata file associated with the volumetric video presentation, comparing a first object appearing in the volumetric video presentation to a corresponding second object appearing in the user-generated content, assigning a score to the first object based on the comparing, wherein the score indicates a probability that the first object has not been manipulated, and altering the volumetric video presentation to filter the first object from the volumetric video presentation when the score falls below a threshold.

Validating objects in volumetric video presentations

One example of a method includes receiving a plurality of video streams depicting a scene, wherein the plurality of video streams provides images of the scene from a plurality of different viewpoints, identifying a target that is present in the scene, wherein the target is identified based on a determination of a likelihood of being of interest to a viewer of the scene, determining a trajectory of the target through the plurality of video streams, wherein the determining is based in part on an automated visual analysis of the plurality of video streams, wherein the determining is based in part on a visual analysis of the plurality of video streams, rendering a volumetric video traversal that follows the target through the scene, wherein the rendering comprises compositing the plurality of video streams, receiving viewer feedback regarding the volumetric video traversal, and adjusting the rendering in response to the viewer feedback.

Selecting viewpoints for rendering in volumetric video presentations

Aspects of the subject disclosure may include, for example, obtaining portions of video content from a video game from video game server(s) associated with a video game provider, selecting a first portion of video content from the portions of the video content, and providing the first portion to device(s) associated with viewer(s). Each device presents the first portion of the video content. Further embodiments include obtaining popularity information from the device(s) according to feedback based on presenting the first portion of the video content to the device(s), determining that the popularity information satisfies a popularity threshold associated with the video content, determining a subject matter corresponding to the first portion of the video content, and identifying a second portion of the video content from the video game to be recorded according to the subject matter. Other embodiments are disclosed.

Methods, systems, and devices for identifying a portion of video content from a video game for a player or spectator

Management and configuration of internet of things network connected devices is facilitated herein. A proxy device comprises a memory that stores executable instructions that, when executed by a processor, facilitate performance of operations that comprise determining a first identity and a first operational parameter of a first device and a second identity and a second operational parameter of a second device. The first device and the second device can be associated with a defined communication network. The proxy device can be provisioned within the defined communication network and can operate as a security update proxy node for the first device and the second device. The operations can also comprise facilitating a first security update at the first device and a second security update at the second device based on a determination that the first device and the second device have delegated responsibility for security synchronization to the proxy device.

Drop-in probe that facilitates management and configuration of internet of things network connected devices

Methods, computer-readable media, and apparatuses for composing a video in accordance with a user goal and an audience preference are described. For example, a processing system having at least one processor may obtain a plurality of video clips of a user, determine at least one goal of the user for a production of a video from the plurality of video clips, determine at least one audience preference of an audience, and compose the video comprising at least one video clip of the plurality of video clips of the user in accordance with the at least one goal of the user and the at least one audience preference. The processing system may then upload the video to a network-based publishing platform.

Video-log production system

A method for gaze-based workflow adaptation includes identifying a workflow in which a user is engaged, where the workflow comprises a plurality of tasks that collectively achieves a desired goal, creating a trigger for a given task of the plurality of tasks, wherein the trigger specifies an action to be automatically taken in response to a gaze of the user meeting a defined criterion, monitoring a progress of the workflow, monitoring the gaze of the user, and sending a signal to a remote device in response to the gaze of the user meeting the defined criterion, wherein the signal instructs the remote device to take the action.

Gaze-based workflow adaptation

Task delegation and cooperation for automated assistants is presented. A method comprises receiving, at a centralized support center that is in contact with a plurality of automated assistants including a first automated assistant and a second automated assistant, a request to perform a task on behalf of an individual, formulating, at the centralized support center, the task as a plurality of sub-tasks including a first sub-task and a second sub-task, delegating, at the centralized support center, the first sub-task to the first automated assistant, based on a determination at the centralized support center that the first automated assistant is capable of performing the first sub-task, and delegating, at the centralized support center, the second sub-task to the second automated assistant, based on a determination at the centralized support center that the second automated assistant is capable of performing the second sub-task.

Task delegation and cooperation for automated assistants

Aspects of the subject disclosure may include, for example, comparing an input received from a peripheral device associated with an execution of a gaming application with a threshold value, wherein the threshold value is based on a first identification of a first user, a second identification of the peripheral device, and a third identification of stimuli presented as part of the execution of the gaming application. Responsive to the comparing, a determination may be made that the input exceeds the threshold value. Responsive to the determination, a validation request may be transmitted to a user device of the first user. Other embodiments are disclosed.

Method to detect and counteract suspicious activity in an application environment

Aspects of the subject disclosure may include, for example, obtaining a first group of video content streams of an event, determining a first point of view of a plurality of audience members of the event, and selecting a first portion of the first group of video content streams of the event according to the first point of view of the plurality of audience members. Further aspects can include aggregating the first portion of the first group of video content streams resulting in first aggregated video content, generating first augmented reality content from the first aggregated video content according to the first point of view, and providing the first augmented reality content to a communication device. The communication device can present the first augmented reality content. Other embodiments are disclosed.

Methods, systems, and devices for identifying viewed action of a live event and adjusting a group of resources to augment presentation of the action of the live event

Growing community of inventors

Gillette, NJ, United States of America

Lee Begeja