Santa Clara, CA, United States of America

Mohammad Saleh

USPTO Granted Patents = 9 

 

Average Co-Inventor Count = 5.6

ph-index = 2

Forward Citations = 10(Granted Patents)


Company Filing History:


Years Active: 2021-2025

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9 patents (USPTO):Explore Patents

Title: Innovations of Mohammad Saleh

Introduction

Mohammad Saleh is a prominent inventor based in Santa Clara, CA. He has made significant contributions to the field of technology, particularly in neural networks. With a total of 9 patents to his name, Saleh continues to push the boundaries of innovation.

Latest Patents

One of his latest patents is titled "Attention-based decoder-only sequence transduction neural networks." This invention includes methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. The method involves generating a combined sequence at each of a plurality of generation time steps, which includes the input sequence followed by the output tokens that have already been generated. The combined sequence is processed using a self-attention decoder neural network to generate a time step output that defines a score distribution over a set of possible output tokens. Finally, an output token is selected from the set of possible output tokens as the next output token in the output sequence.

Career Highlights

Mohammad Saleh is currently employed at Google Inc., where he applies his expertise in neural networks and machine learning. His work has been instrumental in advancing the capabilities of artificial intelligence technologies.

Collaborations

Some of his notable coworkers include Peter Junteng Liu and Noam M Shazeer, who are also recognized for their contributions to the field of technology.

Conclusion

Mohammad Saleh's innovative work in neural networks and his impressive portfolio of patents highlight his significant impact on the technology industry. His contributions continue to shape the future of artificial intelligence and machine learning.

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