Ryan M Dailey

Title: Ryan M. Dailey and Neural Network Optimization

Introduction

Ryan M. Dailey is an inventor associated with New Brunswick, New Jersey. His patent work addresses ways to make neural networks more efficient when deployed on different types of computing hardware.

Latest Patents

Dailey is named on 1 patent, titled “Neural Network Optimization Using Knowledge Representations.” The invention describes systems, tools, and methods for optimizing neural networks to run efficiently on target hardware, including central processing units, graphics processing units, and digital signal processors. Integrated into a machine-learning operations workflow, the software tools use optimization algorithms, such as quantization and pruning, alongside compiler processes to reduce memory requirements and processing latency.

Career Highlights

Dailey is associated with Latent AI, Inc. His patent reflects work on practical neural-network optimization, with an emphasis on adapting models to hardware constraints and improving deployment efficiency.

Collaborations

The supplied information identifies Sek Meng Chai and Jan Ernst as Dailey’s coworkers. Their names are associated with his professional context, though specific roles in the patent are not provided.

Conclusion

Ryan M. Dailey’s patent focuses on optimizing neural networks for efficient execution across varied hardware, highlighting his connection to applied machine-learning tools and deployment technologies.