San Francisco, CA, United States of America

Valerie Moy


Average Co-Inventor Count = 13.0

ph-index = 1


Company Filing History:


Years Active: 2023-2024

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2 patents (USPTO):Explore Patents

Title: The Innovations of Valerie Moy

Introduction

Valerie Moy is an accomplished inventor based in San Francisco, CA. She has made significant contributions to the field of technology, particularly in the area of hair pattern determination and filtering. With a total of two patents to her name, her work has garnered attention for its innovative approach to content indexing and filtering.

Latest Patents

Valerie's latest patents focus on systems and methods to determine hair patterns presented in content items. These patents describe how determined hair patterns can be associated with content items to facilitate indexing and filtering. In exemplary implementations, a corpus of content items is associated with an embedding vector that includes a binary representation of the content item. The embedding vectors associated with each content item can be provided as inputs to a trained machine learning model. This model processes the embedding vectors to determine one or more hair patterns presented in each content item, eliminating the need for image pre-processing prior to the determination of the hair patterns.

Career Highlights

Valerie Moy currently works at Pinterest, Inc., where she applies her expertise in machine learning and content analysis. Her innovative solutions have the potential to enhance user experience by improving the way content is indexed and filtered based on hair patterns.

Collaborations

Some of Valerie's coworkers include Nadia Fawaz and Anh Tuong Ta, who contribute to the collaborative environment at Pinterest, Inc. Their teamwork fosters creativity and innovation in their projects.

Conclusion

Valerie Moy's contributions to the field of technology through her patents and work at Pinterest, Inc. highlight her role as a leading inventor. Her innovative approaches to hair pattern determination and filtering are paving the way for advancements in content analysis.

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