Meridian, ID, United States of America

Daniel Skinner

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Natural Intelligence Systems, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Daniel Skinner. Retrieved from https://idiyas.com/inventor/daniel-skinner-e1101d4x

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Daniel Skinner and Neural Processing Unit Innovation.

Introduction

Daniel Skinner is an inventor based in Meridian, Idaho. His patent work concerns neural processing units (NPUs), specialized integrated circuits designed to support machine-learning computations.

Latest Patents

Skinner is associated with one patent, titled “Neural Processing Units (NPUs) and Computational Systems Employing the Same.” The invention describes chips with multiple computing components that can independently determine the overlap between encoded input data and values stored in memory. This architecture aims to deliver higher performance for machine-learning algorithms than conventional processing units.

Career Highlights

Skinner’s listed patent reflects work on specialized computing hardware and methods for processing data used in machine learning. He is associated with Natural Intelligence Systems, Inc.

Collaborations

The provided information lists Harold B. Noyes and David Roberts as Skinner’s coworkers. Their names appear alongside his professional and patent-related details.

Conclusion

Daniel Skinner’s patent focuses on an NPU architecture intended to improve machine-learning performance through parallel computing components and memory-based data comparisons.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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