Jonathan Newman

Title: Innovations by Jonathan Newman

Introduction

Jonathan Newman is an accomplished inventor based in Menlo Park, California. He has made significant contributions to the field of technology, particularly in the areas of machine learning and data processing. With a total of two patents to his name, Newman continues to push the boundaries of innovation.

Latest Patents

Newman's latest patents include "Weakly supervised extraction of attributes from unstructured data to generate training data for machine learning models." This invention involves an online concierge system that processes unstructured data from various warehouses to extract candidate values for product attributes using natural language processing. Users can associate these candidate values with corresponding attributes, and the system clusters the remaining values to improve accuracy. The labeled items are then used as training data for an attribute extraction model.

Another notable patent is "Verifying association between physical products and identifiers of physical products." This invention allows a server to receive product data entries from multiple retailers, each containing unique product identifiers and descriptive data. By comparing embedding vectors of product data entries, the system computes similarity metrics to determine if any entries are outliers. Notifications are then sent to users based on these determinations.

Career Highlights

Jonathan Newman is currently employed at Maplebear Inc., where he applies his expertise in data processing and machine learning. His work has been instrumental in developing innovative solutions that enhance product identification and data extraction processes.

Collaborations

Newman collaborates with talented coworkers, including Min Xie and Shih-Ting Lin, who contribute to the success of their projects at Maplebear Inc.

Conclusion

Jonathan Newman is a notable inventor whose work in machine learning and data processing has led to significant advancements in technology. His patents reflect a commitment to innovation and a drive to improve systems that rely on unstructured data.