London, United Kingdom

Jose Marcos Rodríguez Fernández


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2019

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1 patent (USPTO):Explore Patents

Title: Innovations of Jose Marcos Rodríguez Fernández

Introduction

Jose Marcos Rodríguez Fernández is an accomplished inventor based in London, GB. He has made significant contributions to the field of conversational agents, particularly through his innovative patent. His work focuses on enhancing the interaction between users and technology, making it more intuitive and effective.

Latest Patents

Jose holds a patent for "Template generation for a conversational agent." This patent describes methods and systems for generating templates that enable a natural language interface. The technology clusters user and agent messages from a corpus of text data, allowing for the generation of response templates that consider the context of the conversation. By embedding messages as numeric arrays based on a neural sequence-to-sequence model, the patent utilizes clustering routines to group dialogue encodings into response clusters. These clusters are then employed to prepare responses for user messages, enhancing the overall user experience.

Career Highlights

Jose is currently associated with Digital Genius Limited, where he applies his expertise in conversational agents. His innovative approach has positioned him as a key player in the development of advanced communication technologies. His work not only contributes to the field but also sets a standard for future innovations in conversational interfaces.

Collaborations

Jose has collaborated with notable professionals in his field, including Yoram Bachrach and Andrej Zukov Gregoric. These collaborations have further enriched his work and expanded the impact of his innovations.

Conclusion

Jose Marcos Rodríguez Fernández exemplifies the spirit of innovation in the realm of conversational technology. His patent and contributions are paving the way for more effective and natural interactions between users and conversational agents.

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