Hyderabad Telangana, India

Kasanagottu Sai Ram

USPTO Granted Patents = 2 

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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2 patents (USPTO):Explore Patents

Title: Kasanagottu Sai Ram: Innovator in Deep Learning Technologies

Introduction

Kasanagottu Sai Ram is a prominent inventor based in Hyderabad, Telangana, India. He has made significant contributions to the field of artificial intelligence, particularly in the area of deep learning. With a total of 2 patents to his name, he is recognized for his innovative approaches to enhancing neural network efficiency.

Latest Patents

One of Kasanagottu Sai Ram's latest patents is a method for automatic hybrid quantization of deep artificial neural networks. This method involves several steps for each floating-point layer in a set of layers. It includes calculating input and output activations, converting the floating-point layer to a low-bit-width layer, and calculating low-bit-width output activations. Additionally, it calculates a per-layer deviation statistic and orders the low-bit-width layers based on this statistic. The method also addresses accuracy thresholds by converting low-bit-width layers back to high-bit-width layers when necessary, ensuring the quantized network maintains its performance.

Career Highlights

Kasanagottu Sai Ram is currently employed at Deep Vision, Inc., where he continues to push the boundaries of technology in deep learning. His work focuses on developing methods that improve the efficiency and accuracy of neural networks, making significant strides in the field.

Collaborations

He collaborates with talented individuals such as Wajahat Qadeer and Rehan Hameed, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Kasanagottu Sai Ram is a notable inventor whose work in deep learning technologies is paving the way for advancements in artificial intelligence. His contributions are essential in enhancing the capabilities of neural networks, and his innovative methods are set to influence the future of this field.

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