For the Inventor, By the Inventor

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Redwood City, CA, United States of America

Numenta, Inc.

USPTO Granted Patents = 62

% Expired Patents = 17.7

EPO Patents = 1

Trademarks = 4

Forward Citations = 915

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22 inventors (with patents filed for the assignee):

Jeffrey Charles Hawkins (45 out of 148 patents)

Subutai Ahmad (27 out of 67 patents)

Dileep George (27 out of 44 patents)

4. Ronald Marianetti, Ii (12 out of 31 patents)

5. Robert Gilchrist Jaros (10 out of 13 patents)

6. Anosh Raj (9 out of 9 patents)

7. Frank Emmanuel Astier (9 out of 23 patents)

8. Yuwei Cui (6 out of 6 patents)

9. Marcus Anthony Lewis (6 out of 6 patents)

10. Jeffrey L Edwards (5 out of 21 patents)

11. William Cooper Saphir (4 out of 4 patents)

12. Chetan Surpur (3 out of 3 patents)

13. Ronald Marianetti (3 out of 3 patents)

14. Rahul Kumar Agarwal (2 out of 91 patents)

15. Luiz Scheinkman (2 out of 10 patents)

Core Competencies:

Hierarchical Temporal Memory

Sparse Neural Networks

Sensorimotor Processing

Temporal Memory

Anomaly Detection

Pattern Recognition

Feedback Mechanisms

Machine Intelligence

Spatio-Temporal Learning

Sequence Learning

Activation Sparsity

Displacement Processor

62 patents: Sort by Forward Citations

1. 12688605 - Communication protocol for inference system (2026-07-21),

2. 12585928 - Hardware architecture for introducing activation sparsity in neural network (2026-03-24),

3. 12443835 - Hardware architecture for processing data in sparse neural network (2025-10-14),

4. 12361303 - Displacement processor for inferencing and learning based on sensorimotor input data (2025-07-15),

5. 12260337 - Performing inference and training using sparse neural network (2025-03-25),

6. 12254409 - Location processor for inferencing and learning based on sensorimotor input data (2025-03-18),

7. 12094192 - Inferencing and learning based on sensorimotor input data (2024-09-17),

8. 12093847 - Temporal processing scheme and sensorimotor information processing (2024-09-17),

9. 12093843 - Inferencing and learning based on sensorimotor input data (2024-09-17),

10. 11966831 - Feedback mechanisms in sequence learning systems with temporal processing capability (2024-04-23),

11. 11681922 - Performing inference and training using sparse neural network (2023-06-20),

12. 11657278 - Location processor for inferencing and learning based on sensorimotor input data (2023-05-23),

13. 11651277 - Sparse distributed representation for networked processing in predictive system (2023-05-16),

14. 11537922 - Temporal processing scheme and sensorimotor information processing (2022-12-27),

15. 11270202 - Temporal memory using sparse distributed representation (2022-03-08),

Company Overview

Numenta, Inc., based in Redwood City, California, specializes in advanced machine intelligence technologies, particularly focusing on Hierarchical Temporal Memory (HTM). This innovative approach mimics the structure and function of the human brain, enabling capabilities in anomaly detection, pattern recognition, and sensorimotor processing. Numenta's research emphasizes the development of sparse neural networks and feedback mechanisms, contributing to the broader field of artificial intelligence and enhancing machine learning applications across various industries.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 20 2026

62 Patents

#36 in Redwood City, CA

#1,369 in California

#5,848 in US

#11,779 in the World

Redwood City, CA, United States of America

Numenta, Inc.

Forward Citations = 915

22 inventors:

Jeffrey Charles Hawkins (45 out of 148 patents)

Subutai Ahmad (27 out of 67 patents)

Dileep George (27 out of 44 patents)

4. Ronald Marianetti, Ii (12 out of 31 patents)

5. Robert Gilchrist Jaros (10 out of 13 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Numenta, Inc.. Retrieved from https://idiyas.com/company/numenta

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

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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