London, United Kingdom

William Thomas Kay

USPTO Granted Patents = 1 

Average Co-Inventor Count = 7.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: William Thomas Kay: Innovator in Neural Networks

Introduction

William Thomas Kay is a prominent inventor based in London, GB. He has made significant contributions to the field of artificial intelligence, particularly in the area of reading comprehension through neural networks. His innovative work has the potential to enhance how machines understand and process human language.

Latest Patents

William Thomas Kay holds a patent for "Reading comprehension neural networks." This patent encompasses methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting answers to questions about documents. One of the methods described in the patent involves receiving a document comprising a plurality of document tokens and a question associated with the document. The question comprises a plurality of question tokens. The process includes using a reader neural network to generate a joint numeric representation of the document and the question, ultimately selecting an answer from the document tokens based on this representation. He has 1 patent to his name.

Career Highlights

William Thomas Kay is currently employed at DeepMind Technologies Limited, a leading company in artificial intelligence research and development. His work at DeepMind focuses on advancing the capabilities of neural networks and their applications in understanding complex documents.

Collaborations

Throughout his career, William has collaborated with notable colleagues, including Karl Moritz Hermann and Tomas Kocisky. These collaborations have further enriched his research and contributed to the development of innovative solutions in the field of AI.

Conclusion

William Thomas Kay is a key figure in the advancement of reading comprehension technologies through neural networks. His contributions are paving the way for more sophisticated AI systems that can better understand human language and context.

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