Capital One Services, LLC

Gurpreet Singh Sandhu

Lee Adcock

Nahid Farhady Ghalaty

Sarvani Kare

Patrick Sofo

Farshid Marbouti

Benjamin Polk

Daniel Liu

Milan Mehta

In some embodiments, holographically displaying items based on item compatibility with user account features may be facilitated. In some embodiments, first and second mobile devices may be detected as being within a proximity threshold of a holographic display device, where the first mobile device is associated with a first user account and the second mobile device is associated with a second user account. Based on the detection, (i) navigation information of the first and second mobile devices, (ii) return value information indicating respective return values associated with candidate items, and (iii) account feature compatibility information may be obtained and inputted into a machine learning model. Despite a first candidate item being incompatible with a second account feature set for the second mobile device, a first holographic representation of the first candidate item may be displayed.

Systems and methods for holographically presenting items based on item compatibility with account features

Methods and systems comprising a first portion of a model that includes a model component that is trained to perform sentiment analysis based on training data for a plurality of users (e.g., what language, phrases, and/or responses the population at large uses). The first portion of the model also includes a model component that is trained to identify user intent based on the sentiment analysis that is specific to user groups. For example, the system first determines the likely context and/or meaning of communications of the user. The system then determines a likely intent of the user based on the likely context and/or meaning of communications (e.g., based on a correlation of the meaning of communications of the user and the intents of users corresponding to a user group of the user).

Methods and systems for cyber threat detection using artificial intelligence models in data-sparse environments

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Walnut Creek, CA, United States of America

Gurpreet Singh Sandhu