United Services Automobile Association (usaa)

Uipco, LLC

Nolan Serrao

Ravi Durairaj

Ruthie D Lyle

Mark Anthony Lopez

Gregory Brian Meyer

Nathan Lee Post

Christopher M Russell

Bharat Prasad

Joel S Hartshorn

Sean Carl Mitchem

Jeanie Graciela Lopez

Ryan Thomas Russell

Victor Kwak

Yevgeniy Viatcheslavovich Khmelev

Snehal Desai

Jennifer Hunt Erickson

Thomas Wayne Schwarz, Jr

Stacy Callaway Huggar

Oscar Roberto Tijerina

Ashley Raine Philbrick

Mark Paxman Warnick

Pooja Krishnaswamy

Elena Marie Carrasco

Gregory David Hansen

Noemy Diosdado

Minya Liang

Donald Nathaniel Holloway, Iii

Will Kerns Maney, Jr

Brian Francisco Shipley

Christian A Williams

Manfred Amann

Eric David Schroeder

Justin Dax Haslam

Emily Margaret Gray

Michael J Maciolek

Robert Wiseman Simpson

Donnette Moncrief Brown

Will Kerns Maney

Bobby Lawrence Mohs

Sumita T Jonak

Daniel Christopher Bitsis, Jr

Meredith Beveridge

Qunying Kou

Paula Ann Whittington

Celena Dortch

Marta Leigh Argumedo

Surender Kumar

Arthur Quentin Smith

David Patrick Dixon

Carlos J P Chavez

Courtney St Martin

David M Jones, Jr

Kevin Kenneth Fiedler

Brian Tougas

David Joaquin Harris

Megan Sarah Jennings

Justin R Nash

Gideon B Luck

Subhalakshmi Selvam

Theresa Marie Matowitz

John Andrew Weems

Keegan Patrick Hayes

Roberto Virgillio Jolliffe

Ivan Ortiz

Salvador Adrian Bretado

Carol Lyn Lawrence

Mounica Urity

Carl Mehner

Rosa Maria Smith

Ahmad Ali Shaik

Yevgenly Viatcheslavovich Khmelev

Ji Qi

Sean C Mitchem

David Michael Schlittler

Michael Clinton Arndt

Olamide Oluwatomi Fanilola

Ana Rosa Maldonado

Systems and methods described herein facilitate the tracking of events relating to property. For example, in certain embodiments, a system includes a property event detection device (e.g., smart home device, sensor device, and so forth) configured to detect activity (e.g., motion, light, sound, and so forth) proximate the property. The system also includes a property event tracking system configured to receive data (e.g., images, videos, facial recognition, movement recognition, object tracking, sound signatures, wireless data streams, and so forth) relating to the activity from the property event detection device, to determine whether the activity relates to a property event (e.g., home service, and so forth) for the property, and to store data relating to the property event in a distributed ledger (e.g., blockchain network) upon determination that the activity relates to the property event for the property.

Property event tracking systems and methods

Aspects of the present disclosure are directed to a cognition analysis and response system that can A) identify and classify machine learning training data and use the training data to build a cognitive impairment machine learning model; B) identify cognitive impairments by applying the cognitive impairment machine learning model and performing a false positive/false negative analysis; and C) apply various automated adaptive measures for users with identified cognitive impairment. The cognition analysis and response system can generate training data by using an unsupervised training process and verifying results with validations of training items that have been pre-classified. The cognition analysis and response system can then iterate through each set of inputs paired with cognitive impairment classification, applying a machine learning model and updating the model based on a comparison of the model output to the cognitive impairment classification.

Automatic identification of, and responding to, cognition impairment

The techniques provided herein may be used to reversibly anonymize data and to mitigate possible de-anonymization the data by third parties. Specifically, a reverse anonymity data sharing service is used to anonymize personal data by replacing confidential information found in the data with unique identifiers. A reverse anonymity data store is used to store the unique identifiers with the information they replaced such that the anonymization may be reversed if needed. Machine learning models are used to prevent traceback, using publicly available data sources, of the anonymized data to it's the individual who generated the data or whom the data is about.

System and methods for data anonymity trackback mitigation

The present application generally relates to a non-fungible token management system that manages transactions involving non-fungible tokens. In an embodiment, the non-fungible token management system may generate insurance policies for non-fungible tokens. The insurance policy can be based on storage risks of non-fungible token associated content. For example, the associated content may include digital data stored outside of a distributed ledger.

Non-fungible token transaction management systems and methods

A phone case includes a cold wallet that holds various cryptocurrencies. A method provides for operation of a smartphone placed in the phone case to interact with the cold wallet. The cold wallet can be incorporated into a system that includes secure storage, a battery, and communications hardware. The system has robust security features, including features that require surface to surface proximity. For example, the system may use wireless charging, which only operates with a limited range. The phone case can use the wireless charging system to send and receive authentication signals from the smartphone. Based on the authentication signals the phone case can power up and connect the secure storage to the rest of the system, thereby only providing secured access to the keys in the cold wallet. After use, the system disconnects the secure storage and the powers down to cold wallet, protecting the private keys.

Phone case with integrated cold wallet

A location-based safety alert system can gather data describing potential health- and safety-related issues at various geographic locations (e.g., crime statistics, disease spread rates, weather reports, and travel advisories). The location-based safety alert system can develop models that characterize how dangerous a location is based on the data describing it. The location-based safety alert system can apply the model, as circumstances at a location change, to compute danger scores that reflect how dangerous the location is at that time. Using the danger scores, the location-based safety alert system can alert users of dangers present in areas of interest to them (e.g., where they will be traveling to soon, where they have family members living, or where they are presently located). The alerts can notify users of the risk present at a geographic location as well as advise them of services and resources available to mitigate the risk.

Providing location-based safety alerts

A system includes at least one processor and at least one non-transitory computer-readable media communicatively coupled to the at least one processor. In an embodiment, the at least one non-transitory computer-readable media stores instructions which, when executed, cause the processor to perform operations including receiving a request to insure an item of personal property. The operations also include determining ownership of the item based on information stored on a distributed ledger. The operations also include determining authenticity of the item based on the information stored on the distributed ledger. The operations also include determining a value of the item based on the information stored on the distributed ledger. The operations also include generating an insurance policy for the item based at least in part on the ownership, the authenticity, the value, or any combination thereof.

Systems and methods for managing financial transaction information

A transactional method and system of incentivizing task performance using token-based exchange for digital media access. The system and method are configured to reward a person with electronic tokens for tasks that are performed and verified by the system. These tokens can then be exchanged by the user for access to desired digital media. Verification can involve the use of natural language processing and image comparison algorithms to determine whether a particular task has been successfully completed.

System and method for incentivizing task performance using token-based digital media access

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

Systems and methods that can automatically and intelligently edit audio signals to correct issues with voices and background noise. Such features may be especially useful as more people decide to work remotely. With remote work, some employees may be multi-tasking, for example by dropping off and picking up their kids while in meetings. Background noise reduction is essential for these remote workers. Using the exemplary systems and methods, remote workers could participate in live calls and/or create recordings while going about their daily chores. In particular, these remote workers would not need to wait until they are back home or in a quieter environment for participating in calls and/or making recordings.

System and method for automatically editing voice signals

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 for determining an authenticity of an asset includes one or more hardware processors. The system also includes a non-transitory memory, the non-transitory memory storing instructions that, when executed by the one or hardware processors, causes the one or more hardware processors to perform actions. The actions include receiving an asset, wherein the asset includes a digital asset or a digital representation of a physical asset. The actions also include receiving an input related to the asset to assist in determining the authenticity of the asset. The actions further include utilizing an augmented intelligence module to analyze the asset and to determine the authenticity of the asset based on the analysis of the asset and the received input.

System and method for authenticity service

Systems and methods that can automatically generate synthetic videos depicting alternative scenarios that may be consistent with recorded video. Systems and methods leverage machine learning systems that can generate synthetic video information using autoencoders and generative adversarial networks that have been trained on previous video data. Systems and methods further include a scenario dashboard that allows users of the system to select recorded videos and other settings that serve as inputs, or constraints, on the synthetically generated videos.

System and method for generating and evaluating synthetic video scenarios

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

An all-in-one multi-access device that provides access points for opening doors, using credit cards, obtaining and displaying tickets, storing information and other applications. The device may include one or more biometric sensors that ensure that it could only be used by an authorized person. In addition to providing keyless entry, the all-in-one multi-access device may also include a digital screen that can display information for credit cards, concert tickets, and airline tickets. In some embodiments, the device may include a magnetic strip and/or a chip to maintain backwards compatibility with older devices, such as magnetic strip readers and chip readers.

All-in-one multi-access wireless devices

Growing community of inventors

Plano, TX, United States of America

Nolan Serrao