Hien Pham

Title: Hien Pham: Revolutionizing Deep Learning Artificial Neural Networks with Innovative Patents

Introduction:

In the rapidly evolving world of deep learning artificial neural networks, inventors like Hien Pham are making groundbreaking contributions. Hien Pham, based in Ho Chi Minh, Vietnam, has left a remarkable imprint on the field with six patents to his name. His revolutionary inventions focus on efficient memory access and physical layout designs for analog neural memory systems used in deep learning artificial neural networks. Let's delve into some of his notable patents and explore his contributions.

Patent 1: Redundant Memory Access for Analog Neural Memory in Deep Learning Artificial Neural Network:

This patent explores various embodiments for accessing redundant non-volatile memory cells as substitutes for rows or columns containing faulty memory cells during program, erase, read, or neural read operations. Hien Pham's innovation ensures uninterrupted functionality in analog neural memory systems, facilitating the smooth operation of deep learning artificial neural networks.

Patent 2: Decoding System and Physical Layout for Analog Neural Memory in Deep Learning Artificial Neural Network:

This patent introduces diverse embodiments of decoders such as word line decoders, control gate decoders, bit line decoders, low voltage row decoders, and high voltage row decoders. Additionally, Hien Pham presents different physical layout designs for non-volatile flash memory arrays in analog neural systems. He also discloses shared and segmented embodiments of high voltage row decoders. These advancements enhance the performance and efficiency of deep learning artificial neural networks.

Company Affiliation:

Hien Pham is an esteemed individual who currently works at Silicon Storage Technology, Inc. (SST), a leading technology company. SST is known for its expertise in memory solutions and innovative technologies, making it a fitting workplace for an inventive mind like Hien Pham.

Collaborators:

Hien Pham has had the privilege of working alongside accomplished individuals in his field. Two of his noteworthy coworkers are Hieu Van Tran and Stanley Hong. Their combined expertise and collaborative efforts could have further augmented the impact of their innovations in the realm of deep learning artificial neural networks.

Conclusion:

Hien Pham's impact on the field of deep learning artificial neural networks cannot be understated. His patents focusing on memory access and physical layout designs have paved the way for enhanced performance and efficiency in such systems. With his continued dedication and inventive mindset, Hien Pham is set to make even more remarkable contributions to this rapidly advancing field.