Capital One Services, LLC

Asyst Technologies, Inc.

Daniel Liu

Lee Adcock

Nahid Farhady Ghalaty

Arun Kumar Sharma

Jose Moreno

Sarvani Kare

Patrick Sofo

Farshid Marbouti

Thomas J O'Connor

Norma B Riley

Alec Sokol

Gurpreet Singh Sandhu

Saianirudh Kantabathina

Selwyn Lehmann

Patrick Ryan

Forrest Thomas

Michael Qiu

Scott Mandrell

Christopher Cellucci

Navaneet Galagali

Sathi Chowdhury

David Woods

Daniel Fritschen

Richard Hightower

Mary Baum

Disclosed herein are system, method, and computer program product embodiments for performing in-flight transformations of data streams. Complex event processing (CEP) operating on event records from various data streams can operate by storing the streamed event record data in a database, and then querying the data to perform a data transformation. However, in order to improve the performance of the data transformations and streamline CEP, a serverless architecture is introduced that can perform data transformations directly on streams, using attributes of the streamed record data defined in a schema. The resulting transformed data can then be provided by the serverless architecture to the CEP for direct access of the data most needed by the CEP.

In-flight transformations over a data stream

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

The present invention generally comprises an apparatus that allows an RFID antenna to obtain information from an RFID tag mounted on a container. The apparatus reproduces the RF field generated by the antenna to a location proximate to the RFID tag. In one embodiment, the apparatus comprises a pickup device and a reproduction device electrically coupled with the pickup device. In another embodiment, the apparatus comprises at least one magnetic rod, which creates a magnetic path for the RF field to travel between the antenna and the RFID tag. In another embodiment, the apparatus comprises a pickup antenna and a reproduction antenna for transmitting the RF signal from the antenna proximate to the RFID tag.

Extended read range RFID system

Growing community of inventors

San Francisco, CA, United States of America

Daniel Liu