Timothy Paul Lillicrap

USPTO Granted Patents = 26 (Patent Applications = 10)

CIPO Patents = 2 (Patent Applications = 1)

EPO Patents = 8 (Patent Applications = 16)

Average Co-Inventor Count = 4.3

ph-index = 3

Forward Citations = 30(Granted Patents)

Company Filing History:

21 out of 308

Deepmind Technologies Limited

Years Active: 2020-2025

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26 patents (USPTO):Sort by Forward Citations

Abstract keywords

1. 12482464 - Controlling interactive agents using multi-modal inputs (2025-11-25),

2. 12455636 - Learned computer control using pointing device and keyboard actions (2025-10-28),

3. 12443851 - Augmenting attention-based neural networks to selectively attend to past inputs (2025-10-14),

4. 12367391 - Selecting reinforcement learning actions using a low-level controller (2025-07-22),

5. 12346786 - Data-efficient reinforcement learning for continuous control tasks (2025-07-01),

6. 12277487 - Energy-based associative memory neural networks (2025-04-14),

7. 12240113 - Deep reinforcement learning for robotic manipulation (2025-03-04),

8. 12189870 - Learned computer control using pointing device and keyboard actions (2025-01-07),

9. 12159221 - Training an unsupervised memory-based prediction system to learn compressed representations of an environment (2024-12-03),

10. 12032523 - Compressed sensing using neural networks (2024-07-09),

11. 11983617 - Scalable and compressive neural network data storage system (2024-05-14),

12. 11897133 - Deep reinforcement learning for robotic manipulation (2024-02-13),

13. 11875258 - Selecting reinforcement learning actions using a low-level controller (2024-01-16),

14. 11829884 - Augmenting attentioned-based neural networks to selectively attend to past inputs (2023-11-28),

15. 11803750 - Continuous control with deep reinforcement learning (2023-10-31),

Title: Innovator Spotlight - Timothy Paul Lillicrap

Introduction:

Timothy Paul Lillicrap, a skilled inventor based in London, GB, is renowned for his groundbreaking work in the field of neural networks and compressed data storage. With an impressive portfolio of 17 patents, Timothy's innovative approach has pushed the boundaries of technology and paved the way for new advancements in the industry.

Latest Patents:

Among his latest patents is the "Compressed sensing using neural networks" method, which involves leveraging neural networks to facilitate compressed sensing processes. This patent showcases Timothy's expertise in optimizing data reconstruction through innovative neural network techniques.

Another notable invention is the "Scalable and compressive neural network data storage system," a sophisticated system designed for efficient data storage utilizing neural networks. This patent reflects Timothy's commitment to developing cutting-edge solutions for data management in the digital age.

Career Highlights:

Throughout his career, Timothy has made significant contributions to renowned companies such as DeepMind Technologies Limited and Google Inc. His expertise in neural networks and data storage systems has positioned him as a key figure in the tech industry. Timothy's relentless pursuit of innovation has led to the development of transformative technologies that have reshaped the way we approach data processing and storage.

Collaborations:

Timothy has collaborated with esteemed professionals in the field, including Nicolas Manfred Otto Heess and Gregory Duncan Wayne. Together, they have worked on revolutionary projects that have garnered recognition within the industry. Timothy's ability to collaborate effectively with top talent underscores his status as a respected innovator in the field of neural networks.

Conclusion:

In conclusion, Timothy Paul Lillicrap stands as a pioneering inventor whose contributions have significantly impacted the realm of neural networks and data storage systems. His dedication to innovation and expertise in developing cutting-edge technologies have solidified his reputation as a leading figure in the industry. Timothy's relentless pursuit of excellence continues to inspire future generations of inventors and innovators in the ever-evolving tech landscape.

This text is generated by artificial intelligence and may not be accurate.