London, United Kingdom

Thomas Keisuke Hubert

This inventor holds 3 USPTO granted patents and 2 published patent applications. Top assignee: Gdm Holding LLC. Active years: 2026.

USPTO Granted Patents = 3 

% Patents Active = 66.7

Average Co-Inventor Count = 10.4

ph-index = 1


Company Filing History:


Years Active: 2026

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3 patents (USPTO):Explore Patents

Title: Innovations of Thomas Keisuke Hubert

Introduction

Thomas Keisuke Hubert is a notable inventor based in London, GB. He has made significant contributions to the field of computer science, particularly in the area of computer code generation. His innovative approach utilizes neural networks to enhance programming efficiency.

Latest Patents

Thomas holds a patent for "Computer code generation from task descriptions using neural networks." This patent encompasses methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating computer code using neural networks. One of the methods involves receiving description data that outlines a computer programming task. It also includes receiving a first set of inputs for the task and generating multiple candidate computer programs by sampling output sequences from one or more generative neural networks. The process further entails executing each candidate program on the inputs to generate outputs and selecting the most suitable programs based on these outputs.

Career Highlights

Thomas is currently employed at GDM Holding LLC, where he continues to develop innovative solutions in technology. His work focuses on improving the efficiency of programming through advanced neural network techniques.

Collaborations

Some of his notable coworkers include James Thomas Keeling and Rémi Leblond, who contribute to the collaborative environment that fosters innovation at GDM Holding LLC.

Conclusion

Thomas Keisuke Hubert's work exemplifies the intersection of technology and innovation, particularly in the realm of computer programming. His contributions are paving the way for more efficient coding practices through the use of neural networks.

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