This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Goldman Sachs &Co. LLC. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Manjunath G Hegde: Innovator in Generative Machine Learning
Introduction
Manjunath G Hegde is a prominent inventor based in Bengaluru, India. He has made significant contributions to the field of machine learning, particularly in the area of generative models. His innovative approach has led to the development of a unique patent that enhances the efficiency of information retrieval.
Latest Patents
Manjunath holds a patent titled "Generative machine learning with retriever having reconfigurable sequence of rankers." This method involves obtaining an input query at a retriever model, which includes a reconfigurable sequence of one or more rankers selected from a plurality of rankers. Each ranker is designed to identify a specified number of information chunks relevant to the input query. The method further includes providing these information chunks to a generative model, which creates a response based on the retrieved information. The rankers utilized in this process include a bi-encoder, a cross-encoder, and a large language model (LLM)-ranker. He has 1 patent to his name.
Career Highlights
Manjunath G Hegde is currently employed at Goldman Sachs & Co. LLC, where he applies his expertise in machine learning to drive innovation. His work focuses on developing advanced algorithms that improve data processing and retrieval.
Collaborations
Throughout his career, Manjunath has collaborated with notable colleagues, including Eliot P Brenner and Koustuv Dasgupta. These partnerships have fostered a creative environment that encourages the exchange of ideas and technological advancements.
Conclusion
Manjunath G Hegde is a visionary inventor whose work in generative machine learning is paving the way for future innovations in the field. His contributions are not only enhancing the capabilities of machine learning models but also setting new standards for information retrieval processes.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
