WILLIAMSBURG, VA, United States of America

David Alberto Nader Palacio

USPTO Granted Patents = 1 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Innovations of David Alberto Nader Palacio

Introduction

David Alberto Nader Palacio is an accomplished inventor based in Williamsburg, VA (US). He has made significant contributions to the field of technology, particularly in the area of neural language models. His innovative work has led to the development of a unique debugging tool that enhances the understanding and performance of these models.

Latest Patents

David holds a patent for a debugging tool designed for code generation neural language models. This tool identifies the smallest subset of an input sequence or rationales that influenced a neural language model to generate an output sequence. By utilizing these rationales, the tool helps to understand the reasons behind the model's predictions, particularly focusing on the input tokens that had the most impact on the output. In cases of erroneous output, the rationales can be used to modify the input sequence to prevent errors or to create a new training dataset aimed at retraining the model for improved performance. He has 1 patent to his name.

Career Highlights

David is currently employed at Microsoft Technology Licensing, LLC, where he continues to innovate and contribute to advancements in technology. His work at Microsoft has positioned him at the forefront of research and development in neural language models.

Collaborations

David has collaborated with notable colleagues, including Colin Bruce Clement and Neelakantan Sundaresan. These partnerships have further enriched his work and expanded the impact of his inventions.

Conclusion

David Alberto Nader Palacio is a pioneering inventor whose work on debugging tools for neural language models showcases his expertise and commitment to technological advancement. His contributions are shaping the future of code generation and model performance.

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