This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Samsung Electronics Co., Ltd.. Active years: 2024.
Company Filing History:
Years Active: 2024
Title: Amir Ben-dror: Innovator in Neural Network Architecture
Introduction
Amir Ben-dror is a prominent inventor based in Ness Ziona, Israel. He has made significant contributions to the field of neural network architecture, particularly through his innovative patent. His work focuses on enhancing the design and implementation of hardware and neural networks.
Latest Patents
Amir Ben-dror holds a patent titled "Method for co-design of hardware and neural network architectures using coarse-to-fine search, two-phased block distillation and neural hardware predictor." This patent describes methods, systems, and apparatus for the combined or separate implementation of coarse-to-fine neural architecture search (NAS), two-phase block NAS, variable hardware prediction, and differential hardware design. The invention involves training a variable predictor and using a controller to iteratively modify neural network architectures. The training process incorporates a variable hardware predictor to predict power, performance, and area (PPA) parameters, making it a significant advancement in the field.
Career Highlights
Amir Ben-dror is currently employed at Samsung Electronics Co., Ltd., where he continues to push the boundaries of technology. His work has garnered attention for its innovative approach to neural network design and hardware integration. With a focus on practical applications, he aims to bridge the gap between theoretical research and real-world implementation.
Collaborations
Amir collaborates with talented individuals such as Roy Josef Jevnisek and Niv Zehngut. These partnerships enhance the development of cutting-edge technologies and foster a collaborative environment for innovation.
Conclusion
Amir Ben-dror is a key figure in the advancement of neural network architecture, with a notable patent that showcases his expertise. His contributions to the field are paving the way for future innovations in hardware and neural network integration.
