Seattle, WA, United States of America

Shruti Sharma

USPTO Granted Patents = 1 

Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Innovations by Shruti Sharma in Machine Learning

Introduction

Shruti Sharma is an accomplished inventor based in Seattle, WA. She has made significant contributions to the field of machine learning, particularly through her innovative patent. Her work exemplifies the intersection of technology and creativity, showcasing her expertise in serverless computing systems.

Latest Patents

Shruti Sharma holds a patent for a groundbreaking invention titled "Machine learning using serverless compute architecture." This patent describes a serverless computing system designed to provide access to a machine learning model. The system associates an endpoint, which includes code that accesses the machine learning model, with an extension that interfaces between the serverless compute architecture and the endpoint. When a request for inference is received, the system processes it using the serverless compute architecture to execute a compute function. This function enables the extension to interface with the endpoint, allowing the machine learning model to perform the necessary inference.

Career Highlights

Shruti currently works at Amazon Technologies, Inc., where she continues to develop innovative solutions in technology. Her role at Amazon allows her to leverage her skills in machine learning and serverless computing, contributing to the company's advancements in these areas.

Collaborations

Some of her notable coworkers include Maximiliano Maccanti and Gowda Dayananda Anjaneyapura Range. Their collaboration fosters a creative environment that encourages innovation and the development of cutting-edge technologies.

Conclusion

Shruti Sharma's contributions to machine learning and serverless computing highlight her role as a leading inventor in the tech industry. Her patent reflects her commitment to advancing technology and improving the efficiency of machine learning applications.

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