Company Filing History:
Years Active: 2021-2022
Title: Veni Singh: Innovator in Technology and Ratings Systems
Introduction
Veni Singh is a notable inventor based in San Mateo, CA. He holds 2 patents that showcase his innovative contributions to technology and data analysis. His work primarily focuses on systems for generating ratings for points of interest and advancements in sequence learning.
Latest Patents
One of Singh's latest patents is titled "System and method for generating and displaying ratings for points of interest." This invention describes systems and methods for generating and displaying ratings for various points of interest in a region. The method involves receiving transaction data from multiple points of interest, which represents financial transactions between individuals and each point of interest. It also includes automatically generating ratings for each point of interest based on this transaction data. Additionally, when a user selects a specific point of interest, the system provides the associated rating to enhance user experience.
Another significant patent is "Method for unsupervised sequence learning using reinforcement learning and neural networks." This invention provides a sequence learning model that retrieves input sequence data, encodes it into output symbol data, and decodes it back to match the original input. The method compares the decoded data with the input and updates the learning model accordingly, showcasing a sophisticated approach to machine learning.
Career Highlights
Veni Singh has worked with prominent companies such as Onu Technology Inc. and Visa International Service Association. His experience in these organizations has contributed to his expertise in technology and innovation.
Collaborations
Some of his notable coworkers include Volkmar Frinken and Guha Jayachandran, who have collaborated with him on various projects.
Conclusion
Veni Singh's contributions to technology through his patents and career experiences highlight his role as an innovator in the field. His work continues to influence advancements in ratings systems and machine learning.