Haifa, Israel

Eran Geva


Average Co-Inventor Count = 5.3

ph-index = 1


Company Filing History:


Years Active: 2019-2025

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4 patents (USPTO):Explore Patents

Title: The Innovations of Eran Geva

Introduction

Eran Geva is a notable inventor based in Haifa, Israel, recognized for his contributions to deep learning technologies. With a total of four patents to his name, Geva has made significant strides in enhancing the efficiency of neural network processing.

Latest Patents

One of Geva's latest patents focuses on deep learning inference efficiency technology with early exit and speculative execution. This technology provides systems, apparatuses, and methods that process an inference workload in a first subset of layers of a neural network. It prevents or inhibits data-dependent branch operations and conducts an exit determination to assess whether the output of the first subset of layers meets specific exit criteria. Based on this determination, the technology selectively bypasses processing of the output in a second subset of layers. Additionally, it may speculatively initiate processing in the second subset while the exit determination is pending. When handling multiple batches of inference workloads, the technology can mask one or more of these batches from processing in the second subset of layers.

Career Highlights

Eran Geva is currently employed at Intel Corporation, where he continues to innovate and develop advanced technologies in the field of artificial intelligence and machine learning. His work has contributed to the ongoing evolution of deep learning applications.

Collaborations

Geva collaborates with talented individuals such as Haim Barad and Barak Hurwitz, who share his passion for advancing technology and innovation.

Conclusion

Eran Geva's work in deep learning technologies exemplifies the impact of innovative thinking in the tech industry. His patents reflect a commitment to improving the efficiency of neural networks, paving the way for future advancements in artificial intelligence.

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