At&t Intellectual Property I, L.p.

At&t Mobility Ii LLC

Hyundai Motor Company

Kia Corporation

Nuance Communications, Inc.

Xandr Inc.

Columbia University

The Hong Kong University of Science and Technology

Shopify Inc.

Simplisafe, Inc.

At&t Global Network Services Belgium Luxembourg Sprl

Eric Martin Zavesky

David Crawford Gibbon

James H Pratt

Zhu Liu

Lee Begeja

Behzad Shahraray

Bernard S Renger

Tan Xu

Nigel Bradley

Raghuraman Gopalan

Robert A Koch

Timothy Innes

Ari Craine

Jason Decuir

Yupeng Jia

Amy Ruth Reibman

Rashmi Palamadai

Yadong Mu

Paul Triantafyllou

Andrea Basso

Robert Gratz

Jean-Francois Paiement

Nikhil Shreerang Marathe

Richard Palazzo

Zhi Cui

Jianxiong Dong

Bo Han

Robert Torrence Moton, Jr

Adrianne Binh Luu

Ginger Li Chien

Gregory Wesley Edwards

Miranda Huet

Donald Perciful

Terrel Lecesne

James Jackson

Brian M Novack

John Oetting

Oliver Spatscheck

Michael Gonzales

Sumit Kumar

Mohammed Abdel-Wahab

Bhumit Patel

Martin Patrick McEnroe

Wen-Ling Hsu

Subhabrata Majumdar

Patrick Guy Haffner

Ann K Syrdal

Robert Dailey

Taniya Mishra

Christopher Volinsky

Sumit Chopra

Ilija Zeljkovic

Joshua Whitney

Seungjoon Lee

Benjamin J Stern

Mark Stockert

Cheuk Yiu Ip

Zhengyi Zhou

Moo-Ryong Ra

Deirdre Paul

Emiliano Miluzzo

Samuel Seljan

Pamela Stuckman

Linda Baughman

Qiong Wu

Ashutosh Sanzgiri

William Knotts

Huanle Zhang

Aritra Guha

Rhonda Green

Emily Williams

Gustavo De Los Reyes

Andrea Giuseppe Forte

Juan A Garay

Evgene Vahlis

Ann Eileen Skudlark

Eric Petajan

Lien K Tran

Yizhe Zhang

James Klosowski

Roger Drew Wickes

Molly Hutsler

Alexander Ruditsky

Ni An

Prateek Baranwal

Kelly Dowd

Vijay Gopalakrishnan

Brian Scott Amento

Shih-Fu Chang

Dimitrios Dimitriadis

Kermit Hal Purdy

Simon D Byers

Prince Paulraj

Jeffrey Stein

Pan Hui

Russell Fischer

Wiley C Wilkins

Christopher Kim

Christophe Closset

Wenxiao Zhang

A processing system including at least one processor may obtain description information of a first machine learning model, obtain a set of interpretation criteria for the first machine learning model, and generate, via a second machine learning model, an explanation text providing an interpretation of the first machine learning model in accordance with the set of interpretation criteria and the description information of the first machine learning model.

Automated machine learning model explanation generation

A method performed by a processing system including at least one processor includes detecting that new data has been added to a repository of reusable machine learning models and machine learning model features, applying data protection to the new data, testing the new data for bias, merging at least a portion of the new data with stored data from the repository to build a new machine learning model in which the data protection is preserved, and publishing the new machine learning model in the repository.

Governance mechanisms for reuse of machine learning models and features

Aspects of the subject disclosure may include, for example, determining a first virtual location of a first avatar of a first user within a virtual environment, determining a second virtual location a second avatar of a second user within the virtual environment that is in proximity to the first virtual location, and determining that the second user has an untrusted relationship with the first user. Further embodiments include presenting on a user interface of a first communication device of the first user a group of actions for restricting personal identifiable (PI) data of the first user presented by the first avatar in the virtual environment to the second user, receiving a selection of a first action from the group of actions for restricting the PI data, and restricting presentation of the PI data in the virtual environment according to the first action. Other embodiments are disclosed.

Methods, systems, and devices to protect personal identifiable (PI) data when a user utilizes an avatar in a virtual environment

A processing system including at least one processor may gather first imaging data associated with an infrastructure item via at least a first imaging device, where the first imaging data represents a first condition of the infrastructure item, and gather second imaging data associated with the infrastructure item via at least a second imaging device, where at least one of the at least the first imaging device or the at least the second imaging device is mounted on a vehicle, and where the infrastructure item is visible from a road on which the vehicle operates. The processing system may then determine a second condition of the infrastructure item in accordance with the second imaging data, where the second condition comprises a potentially unsafe condition of the infrastructure item, and generate a report of the potentially unsafe condition of the infrastructure item in response to the determining.

Sensor-based infrastructure condition monitoring

The technologies described herein are generally directed to allocating a resource to perform a task based on a predicted capacity of the resource. For example, a method described herein can include identifying a selected capacity associated with completion of tasks of a particular task type. Further, the method can include, evaluating a result of work by a worker resource performing a task of the particular task type. The method can further include, based on the result, predicting that the worker resource has the selected capacity and, based on this prediction, assign the worker resource to perform another task of the particular task type.

Utilization of a resource to perform a task based on a predicted capacity of the resource

Services for trust conveyances of entities can be provided and managed. In connection with a transaction between first and second devices, a trust management component (TMC) can indicate trust levels of entities associated with the devices with regard to the transaction and/or an action attempted by an entity. With regard to an action attempted by the first entity, the trust level of the first entity can be evaluated to determine whether it is high enough to allow the action to proceed or to have the second entity respond to the action accordingly. If it is not high enough, the second entity, using the second device, can request a trust conveyance from the first entity via the TMC. The TMC can adjust the respective trust levels based on the outcome(s) of the action(s) of the respective entities with regard to executing the transaction.

Services for entity trust conveyances

Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, including receiving a request for an observation of an overhead viewing area from an observer location; discovering an interference of a satellite with the observation of the overhead viewing area; determining possible solutions to the interference; selecting a solution of the possible solutions; receiving the observation from one or more satellites responding to the solution selected; and providing a response to the request including the observation received. Other embodiments are disclosed.

System and method for satellite-based masking and amplification

Concepts and technologies disclosed herein are directed to anticipatory supply chain coordination with connected vehicle fleet and unmanned aerial vehicle ('UAV') integrations. According to one aspect disclosed herein, an energy provider system can obtain connected vehicle information from a connected vehicle. The connected vehicle information can include a vehicle identifier that uniquely identifies the connected vehicle, an energy capacity remaining for the connected vehicle, and a current location of the connected vehicle. The energy provider system can obtain order information from an inventory management system. The order information can include a destination location to which a physical order is to be delivered. The energy provider system can determine a route to the destination location based, at least in part, upon the energy capacity remaining and the current location. The energy provider system can then provide the route to the connected vehicle.

Anticipatory supply chain coordination with connected vehicle fleet and unmanned aerial vehicle integrations

Aspects of the subject disclosure may include, for example, defining at least one requirement for a capture of source content in the physical world, generating a request for the source content in accordance with the at least one requirement, obtaining first source content from a first content generator based on the request, and generating a digital representation of the physical world based on the first source content. Other embodiments are disclosed.

Apparatuses and methods for facilitating crowd sourced content for digital simulation

Concepts and technologies disclosed herein are directed to mental health anomaly detection and guidance. According to one aspect of the concepts and technologies disclosed herein, a mental health user system can create a baseline user behavior profile for a user. The mental health user system can monitor a behavior of the user. The mental health user system can determine whether the behavior of the user is anomalous in comparison to the baseline user behavior profile. The mental health user system can, in response to determining that the behavior of the user is anomalous, provide a treatment to the user to return the behavior to be consistent with the baseline user behavior profile.

Mental health anomaly detection and guidance

A processing system including at least one processor may obtain at least a first identifier associated with an endpoint device of a user at a location, determine, based on the at least the first identifier, that the user is an authorized participant of at least one service at the location, and provide an identity token to the endpoint device, where the identity token is for use at the location in connection with the at least one service, provide to the endpoint device a list of other identity tokens associated with endpoint devices of other users at the location, detect a communication between the endpoint device of the user and an endpoint device of the other user in accordance with the identity token and another identity token, from among the other identity tokens, and record information characterizing the communication in an electronic ledger associated with the at least one service.

Temporary identifiers for network and service access and for transaction recordation

Aspects of the subject disclosure may include, for example, a device that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, including downsampling a full point cloud to obtain a downsampled point cloud, wherein the downsampling reduces a data size of the full point cloud; and using a machine-learning model to assign labels for segmentation and object identification to points in the downsampled point cloud, wherein the machine-learning model is trained on the full point cloud. Other embodiments are disclosed.

Method for accelerating three-dimensional object segmentation with point cloud simplifications

The described technology is generally directed towards emotion detection and translation for electronic communications. An emotional state of a first communication participant can be detected, e.g., through face recognition, biometric information, and/or communication content analysis. The emotional state can be encoded in metadata that can accompany the communication content. The metadata can be translated into one or more embellishments that represent the emotional state, and the embellishments can be inserted into the communication content. The embellished communication content can then be delivered to a second communication participant.

Emotion detection and translation for electronic communications

Methods, computer-readable media, and systems for enhancing food service operations using Internet of Things-enabled dinnerware are disclosed. One method performed by a processing system including at least one processor includes obtaining data about a food item that is being prepared for a consumer, forwarding the data about the food item to an internet of things-enabled item of dinnerware, receiving, from the internet of things-enabled item of dinnerware, data about consumption of the food item by the consumer, and providing feedback to an endpoint device of a person who prepared the food item for presentation to the person who prepared the food item, in response to the data about the consumption of the food item by the consumer.

Internet of things-enabled dinnerware to enhance food service operations

Creating scent models and using scent models in cross-reality environments can include capturing experience data identifying a scent detected and a context in which the scent was detected. The experience data can be provided to a scent modeling service to generate a scent model that can represent perceived scents and perceived scent intensities for a user. The scent model can be used to generate cross-reality session data to be used in a cross-reality session presented by a cross-reality device. The cross-reality device can include a scent generator and can generate the cross-reality session using data obtained from the user device. The cross-reality device can generate a further scent during the cross-reality session based on the scent model.

Creating scent models and using scent models in cross-reality environments

Growing community of inventors

New York, NY, United States of America

Eric Martin Zavesky