Shmuel Kalner

Title: Shmuel Kalner: Innovator in Deep Learning for Edge Devices

Introduction

Shmuel Kalner is a notable inventor based in D.N. Menashe, Israel. He has made significant contributions to the field of deep learning, particularly in adapting models for resource-constrained edge devices. His innovative work has garnered attention in the tech community.

Latest Patents

Kalner holds a patent titled "Adaptation of deep learning models to resource constrained edge devices." This patent describes techniques for generating a set of deep learning (DL) models. An example method includes training an initial set of DL models using training data, where the topology of each model is determined based on a parameters vector. The method also involves generating performance functions for each DL model based on edge-related metrics and creating objective functions from these estimated performance functions. Ultimately, a final DL model set is generated, allowing users to select and deploy a chosen DL model to an edge device.

Career Highlights

Shmuel Kalner is associated with International Business Machines Corporation (IBM), where he continues to push the boundaries of technology. His work focuses on enhancing the efficiency and effectiveness of deep learning applications in environments with limited resources.

Collaborations

Kalner has collaborated with notable colleagues, including Lior Turgeman and Nir Naaman. Their combined expertise contributes to the advancement of innovative solutions in the field of deep learning.

Conclusion

Shmuel Kalner's contributions to deep learning and edge devices exemplify the impact of innovation in technology. His patent and collaborative efforts highlight the importance of adapting advanced models for practical applications.