Mountain View, CA, United States of America

Yong Cheng

This inventor holds 1 USPTO granted patent and 5 published patent applications. Top assignee: Google Inc.. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Yong Cheng. Retrieved from https://idiyas.com/inventor/yong-cheng-cj362niq

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 25.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Yong Cheng - Innovator in Neural Network Training

Introduction

Yong Cheng is a prominent inventor based in Mountain View, CA. He has made significant contributions to the field of machine learning, particularly in the training of large neural networks. His innovative work has implications for various applications in artificial intelligence.

Latest Patents

Yong Cheng holds a patent for the "Training of large neural networks." This patent encompasses methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to perform a variety of machine learning tasks. Notably, the neural network can be configured as a generative neural network, such as an autoregressive generative neural network.

Career Highlights

Cheng is currently employed at Google Inc., where he continues to push the boundaries of technology and innovation. His work at Google has positioned him as a key player in the advancement of neural network methodologies.

Collaborations

Some of his notable coworkers include Slav Petrov and Yonghui Wu, who are also recognized for their contributions to the field of machine learning.

Conclusion

Yong Cheng's work in neural network training exemplifies the innovative spirit of modern technology. His contributions are paving the way for future advancements in artificial intelligence and machine learning.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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