Lafayette, CA, United States of America

Dara Bahri

USPTO Granted Patents = 2 

Average Co-Inventor Count = 6.2

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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2 patents (USPTO):

Title: Innovations of Dara Bahri

Introduction

Dara Bahri is an accomplished inventor based in Lafayette, CA, known for his contributions to machine learning and neural networks. With a total of two patents to his name, he has made significant strides in the field of artificial intelligence.

Latest Patents

Dara Bahri's latest patents include "Sorting Attention Neural Networks" and "Efficient Decoding of Output Sequences Using Adaptive Early Exiting." The first patent describes a system for performing a machine learning task on a network input, which involves multiple sorting networks designed to sort vector blocks in a sequence. This innovative approach enhances the efficiency of machine learning tasks by utilizing sorting attention mechanisms. The second patent focuses on methods and systems for generating output sequences using auto-regressive decoder neural networks. This technology employs adaptive early exiting to minimize the time required for output sequence generation, showcasing Bahri's commitment to improving the efficiency of neural network operations.

Career Highlights

Dara Bahri has built a notable career at Google Inc., where he has been instrumental in advancing machine learning technologies. His work has not only contributed to the company's innovative projects but has also positioned him as a key figure in the field of artificial intelligence.

Collaborations

Throughout his career, Dara has collaborated with esteemed colleagues such as Donald Arthur Metzler, Jr. and Yi Tay. These partnerships have fostered a collaborative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Dara Bahri's contributions to the field of machine learning and neural networks exemplify his innovative spirit and dedication to advancing technology. His patents reflect a deep understanding of complex systems and a commitment to enhancing the efficiency of artificial intelligence applications.

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