Los Angeles, CA, United States of America

Eugene Lok

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: The Innovative Mind of Eugene Lok

Introduction

Eugene Lok is a notable inventor based in Los Angeles, CA. He has made significant contributions to the field of technology, particularly in the realm of video learning models. His innovative approach combines machine learning with video content to enhance user engagement.

Latest Patents

Eugene Lok holds a patent for a "Video clip learning model." This computer-implemented method involves accessing a video clip associated with a media item and comparing it to various previously selected video clips. The method determines the similarity between the accessed video clip and a specified video clip, accessing a take fraction value that indicates how well the specified video clip has correlated to user views of the associated media item. Based on this association, the method trains a machine learning model to predict a video clip take fraction value for the accessed video clip, indicating its potential correlation to user views. This innovative approach has the potential to revolutionize how media items are promoted and consumed.

Career Highlights

Eugene Lok is currently employed at Netflix Inc., where he continues to develop and refine his innovative ideas. His work at Netflix allows him to explore the intersection of technology and media, contributing to the company's mission of delivering engaging content to users.

Collaborations

Eugene has collaborated with talented individuals such as Amirreza Ziai and Shervin Ardeshir Behrostaghi. These collaborations have fostered a creative environment that encourages the exchange of ideas and innovative solutions.

Conclusion

Eugene Lok's contributions to the field of video learning models exemplify the power of innovation in technology. His patent and work at Netflix highlight his commitment to enhancing user experiences through advanced machine learning techniques.

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