Austin, TX, United States of America

David Palframan


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2022

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2 patents (USPTO):

Title: David Palframan: Innovator in Neural Network Technology

Introduction

David Palframan is a prominent inventor based in Austin, Texas. With a keen focus on advancements in artificial intelligence, he holds two patents that reflect his innovative contributions to the field of neural networks. His expertise lies in compressing and formatting neural network parameters, which are pivotal for developing efficient computing devices.

Latest Patents

Palframan's latest patents include:

1. **Systems and devices for compressing neural network parameters** – This patent discloses technology related to the storage and processing of signals representative of neural network parameters, specifically focusing on techniques for compressing these signals within computing devices.

2. **Systems and devices for formatting neural network parameters** – This patent pertains to the storage of signals and states that represent neural network parameters, emphasizing the need for effective storage solutions in computing devices.

Career Highlights

Throughout his career, David Palframan has collaborated with notable organizations such as Arm Limited and the University of Michigan. His work at these institutions has allowed him to leverage his knowledge in cutting-edge technology and contribute significantly to the field of artificial intelligence and neural networks.

Collaborations

Palframan has shared his innovative journey with esteemed colleagues, including Jiecao Yu and Andrew Lukefahr. This collaborative environment has fostered creativity and advancement within the realms of technology and neural networks.

Conclusion

David Palframan's contributions to neural network technology through his patents illustrate the importance of innovation and collaboration in advancing artificial intelligence. His work continues to influence the development of efficient computing systems, paving the way for future advancements in this rapidly evolving field.

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