International Business Machines Corporation

United Services Automobile Association (usaa)

Nvidia Corporation

Lenovo (singapore) Pte. Ltd.

Airbnb, Inc.

Google Inc.

Globalfoundries Inc.

Uipco, LLC

Ruthie D Lyle

Patrick Joseph O'Sullivan

Nolan Serrao

Lin Sun

Ravi Durairaj

Liam S Harpur

Judith Helen Bank

Gregory Brian Meyer

Sean Carl Mitchem

Nathan Lee Post

Mark Anthony Lopez

Carol Sue Zimmet

Ashley Raine Philbrick

Ryan Thomas Russell

Christopher M Russell

Angela Richards Jones

Fred Raguillat

Victor Kwak

Eric David Schroeder

Deborah Janette Schulz

Will Kerns Maney

Oscar Roberto Tijerina

Snehal Desai

Fonda J Daniels

Bharat Prasad

Yevgeniy Viatcheslavovich Khmelev

Gabriel Carlos Fernandez

Sean Callanan

Stacy Callaway Huggar

Timothy Blair Chalmers

Bryan J Osterkamp

Gary Denner

Rachel Elizabeth Csabi

Courtney St Martin

Corinne M Ryan

Minya Liang

Richard Daniel Graham

Rick A Hamilton, Ii

Travis M Grigsby

Gregory David Hansen

Andre Rene Buentello

Jose L Romero, Jr

Carlos J P Chavez

Al Chakra

Andrew Lewis Schirmer

Thomas Bret Buckingham

Lisa A Seacat

Kelly Q Baker

Noe Alberto Martinez

William Daniel Farmer

Brian Tougas

Pooja Krishnaswamy

Michael Muller

Mark Paxman Warnick

David Bruce Lection

Mary Ellen Zurko

Kelly Malone

David Joaquin Harris

Clifford A Pickover

Christopher J Dawson

James W Seaman

Paul Andrew Moskowitz

Eric Leonard Masselle

John Kenyon Gerken, Iii

Carlos Jp Chavez

Sandra K Johnson

Jon Daniel McEachron

Gregory J Boss

Lisa Seacat DeLuca

Bradly Jay Billman

Dana Lea Price

Reynaldo Medina, Iii

Anne R Sand

Vijay Jayapalan

Oscar Guerra

Gregory B Yarbrough

David M Jones, Jr

Jason W Lindley

Cary Lee Bates

Gary David Cudak

Itzhack Goldberg

Christopher J Hardee

David B Kumhyr

Charles Lee Oakes, Iii

Pamela Ann Nesbitt

James Patrick Galvin, Jr

Adam Roberts

Mark Edmund Maresh

Maland Keith Mortensen

David Mark Ogle

David Patrick Dixon

Frank Lawrence Jania

John Michael Lake

Robert Thomas Uthe

Eric Allen Stegner

Joel S Hartshorn

Randall C Humes

Jeanie Graciela Lopez

Thomas Wayne Schwarz, Jr

Jennifer Quirin Trelewicz

Embodiments disclosed herein describe a method and system that create a user profile associated with a user. The user profile can include locations in which the user has worked and information relating to one or more devices associated with the user. The system can receive data from the devices and analyze the data to predict a work location of the user. Resources can be optimized based on the predicted work location of the user and the predicted work locations of other users.

Methods and systems for smart resource allocation based on work location predictions

A remote haptic signal-based method and system of performing an authentication of video of a person in order to authorize access to a secured resource. The system and method are configured to cause a remote computing device to generate a vibration while collecting sensor data from the same device. The sensor data is evaluated to determine whether the appropriate motion response from the remote computing device is present. If the response is present, the system determines the image is authentic and can verify an identity of the person, and can further be configured to automatically grant the person access to one or more services, features, or information for which he or she is authorized.

Haptic feedback-based video authentication method and system

A remote signal-based method and system of performing an authentication of video of a person in order to authorize access to a secured resource. The system and method are configured to cause a visual and/or audio pattern to be displayed in a remote computing device while collecting image data from the same device. The image data is evaluated to determine whether the appropriate response from the person is present. If the response is present, the system determines the image is authentic and can verify an identity of the person, and can further be configured to automatically grant the person access to one or more services, features, or information for which he or she is authorized.

Reflexive response-based video authentication method and system

A system and method for using an augmented intelligence guide system to assist users, customers, members, and other users of a service (for example, a financial service or an insurance service) in completing a task or process to improve the success rate of the accurate completion of the steps necessary to execute the task or process is described. The system includes a process detection module, an experience determination module, an assistance classification module, and a guidance engine.

System and method to enable augmented intelligence guided help

A tattoo detection-based method and system of performing an authentication of video of a person in order to authorize access to a secured resource is disclosed. The user provides image data in which they present a region of skin on which a pattern or code has been tattooed with ink that is invisible to the human eye. The system and method are configured to evaluate the image data to determine whether the cloaked token is present. If a cloaked token is present, the system determines the image is authentic and can verify an identity of the person. In some cases, the system can further be configured to automatically grant the person access to one or more services, features, or information for which he or she is authorized.

Tattoo detection-based video authentication method and system

Disclosed herein is an environmental scanning tool that generates a digital model representing the surroundings of a user of an extended reality head-mounted display device. The environment is imaged in both a depth map and in visible light for some select objects of interest. The selected objects exist within the digital model at higher fidelity and resolution than the remaining portions of the model in order to manage the storage size of the digital model. In some cases, the objects of interest are selected, or their higher fidelity scans are directed, by a remote user. The digital model further includes time stamped updates of the environment such that users can view a state of the environment according to various timestamps.

Local physical environment modeling in extended reality environments

A system and method for detecting deviations in building structures over time is disclosed. The system and method use range images of buildings captured using range imaging cameras (for example, time-of-flight cameras) to construct 3D models with sufficient resolution to detect deviations in structures that may not be obvious from looking at only photographic images. The system can also use augmented reality to project parts of a 3D model over photographic images of a structure to facilitate easy inspection of the structure.

System and method for detecting deviations in building structures using reconstructed 3D models

The present disclosure relates to a system, method, and mobile computing device apparatus for detecting the physical presence of a bank customer at a bank branch, and delivering an enhanced customer service experience by anticipating the bank customer's needs. Detection of the bank customer through visual data such as facial recognition, or electronic data such as medium range electronic communication networks to the customer's mobile computing device, allow a bank to retrieve relevant customer profile and customer transaction history data and use that data to deliver communications to the customer even before the customer speaks to a bank teller.

Systems and methods for touchless in-person bank customer service

Systems and methods of selectively compressing video data are disclosed. The proposed systems provide a computer-implemented process configured to classify a person's behavior(s) during a video and encode the behaviors as a representation of the video. The encoding will be tailor-generated based on the specific display configuration of the target device at which playback is expected to occur. Target device displays with lower resolution and video quality characteristics will trigger an encoding of the video data that has less complexity than target device displays with higher resolution and video quality characteristics. When playback of the video is requested at the target device, a reconstruction of the video is generated by a video synthesizer based on a reference image of the person and the encoding rather than the original video file, significantly reducing memory, processing, power, and bandwidth requirements.

Selective data encoding and machine learning video synthesis for content streaming systems and applications

Systems and methods of compressing video content as encoded data and selectively reconstructing portions of the content are disclosed. The proposed systems provide a computer-implemented process configured to classify a person's behavior(s) during a video and encode the behaviors as a representation of the video. When playback of the video is requested, a video navigation assistant will allow the end-user to select specific segments of the video based on topics discussed in the video and the codes that were generated to represent the video. The user is then able to move through segments of the video in a sequence that aligns with their viewing preferences.

Conversational AI-encoded language for video navigation

The present embodiments relate to on demand generation of curated audio content. Responsive to initiation of an electronic communication by a client, audio relating to a client speaking to the operator can be processed to derive a series of insights relating to features of the audio. Previously recorded audio relating to the operator can be combined with a text-based script to generate audio content. The audio content can be modified using the series of derived insights. The modified audio content can include a series of disclaimers that are played back to the client. Generation of the modified audio content can be dynamically generated responsive to detecting a trigger that allows for on-demand generation of the modified audio content.

Recipient customized generative voice modeling

A remote signal-based method and system of performing an authentication of images of a person in order to permit access to a secured resource. The system and method are configured to cause a visual and/or haptic pattern response to occur in a secondary device while collecting image data from a different, primary device. The image data is evaluated to determine whether the appropriate pattern is present. If the pattern is present, the system determines the image is authentic and can verify an identity of the person, and can further be configured to automatically grant the person access to one or more services, features, or information for which he or she is authorized.

Secondary device remote signaling-based video authentication method and system

A method for guiding game play of a game in an augmented reality game space. The game runs on a smart device in conjunction with a game space. The method includes determining that a user has completed a game objective and earned the right to a game piece having a concealed value. Information including an indication that the user has completed the game objective is sent from a smart device to a game server. The game server receives information from the smart device and sends information including a location of the game piece having a concealed value to the smart device and to a confirmation device. The smart device displays a location of the game piece having a concealed value in the augmented reality game space. Also, a system for game play including the smart device, the game server, and the confirmation device.

Wireless communication device with concealed value in mobile gaming

A system and method for performing machine learning in a mobile computing device which is configured to be coupled with a cloud computing system is disclosed. The method may include activating, on the mobile computing device, a machine learning application, which accesses a local machine learning system including a local machine learning model, periodically updating the local machine learning system based upon updates for the local machine learning system received from a global machine learning system hosted by the cloud computing system, performing machine learning based on received training data, and periodically transmitting changes to the local machine learning system from the mobile computing device to the global machine learning system hosted by the cloud computing system.

Edge computing for machine learning

Systems and methods are directed toward evaluating auditory inputs against a range of tolerance to provide feedback regarding pronunciation. An auditory input may be evaluated using a trained machine learning system and evaluated for similarity against a target word. Similarity may be scored and then evaluated to determine whether the similarity falls within a range of tolerance, wherein the range of tolerance may be adjusted or modified for particular uses. A score within the range of tolerance is indicative of a word that has been pronounced such that it would be perceptible.

Pronunciation features for language models

Growing community of inventors

Durham, NC, United States of America

Ruthie D Lyle