This inventor holds 1 USPTO granted patent. Top assignee: Intel Corporation. Active years: 2023.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2023
Title: Innovations by Kwangwoong Park in Neural Network Memory Management
Introduction
Kwangwoong Park is an accomplished inventor based in Seoul, South Korea. He has made significant contributions to the field of artificial intelligence, particularly in the management of memory for deep neural networks. His innovative approaches aim to enhance the efficiency of neural network computations.
Latest Patents
Kwangwoong Park holds a patent titled "Methods and arrangements to manage memory in cascaded neural networks." This patent focuses on logic that may reduce the size of runtime memory required for deep neural network inference computations. The logic determines the count of shared memory block allocations that exist during the execution of multiple stages of a neural network. By comparing these counts, the logic identifies a maximum count, which helps in reducing inference computation time. Additionally, it determines the size of shared block allocations to accommodate data during execution, optimizing the performance of cascaded neural networks.
Career Highlights
Kwangwoong Park is currently employed at Intel Corporation, where he continues to work on cutting-edge technologies in artificial intelligence and machine learning. His expertise in memory management for neural networks positions him as a valuable asset in the tech industry.
Collaborations
Kwangwoong Park collaborates with talented colleagues, including Byoungwon Choe and Seokyong Byun. Together, they contribute to advancements in neural network technologies and memory management solutions.
Conclusion
Kwangwoong Park's innovative work in managing memory for deep neural networks showcases his commitment to enhancing artificial intelligence technologies. His contributions are paving the way for more efficient neural network computations, making a significant impact in the field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
