Redmond, WA, United States of America

Anamika Bedi

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2022.

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 9.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Anamika Bedi: Innovator in Machine Learning Interfaces

Introduction

Anamika Bedi is a talented inventor based in Redmond, WA (US). She has made significant contributions to the field of machine learning through her innovative patent. Her work focuses on enhancing the interaction between users and machine learning models, making complex technologies more accessible.

Latest Patents

Anamika holds a patent for an "Interface for machine teaching modeling." This patent describes techniques for configuring a machine learning model, which includes instantiating a user interface that communicates with a machine learning model hosted on a collaborative computing platform. The process involves receiving a selection of a file for input to the model, selecting content within that file, and providing instructions for applying the selected content. Additionally, it allows for the selection of directories and instructions to apply the machine learning model.

Career Highlights

Anamika is currently employed at Microsoft Technology Licensing, LLC, where she continues to develop her expertise in machine learning technologies. Her innovative approach has led to the successful filing of her patent, showcasing her ability to bridge the gap between technology and user experience.

Collaborations

Anamika has collaborated with notable colleagues, including Krishna Kant Gupta and Sean Squires. These partnerships have contributed to her success and the advancement of her projects.

Conclusion

Anamika Bedi is a pioneering inventor whose work in machine learning interfaces is shaping the future of technology. Her contributions are not only innovative but also essential for making machine learning more user-friendly.

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