Block-Based Compression of Neural Network Data
Summary
The USPTO published patent application US20260093964A1 by inventor Navin Patel describing a method for compressing neural network data blocks. The system converts trained neural network weights into 2D blocks and treats them as color data (monochrome or RGB) for block-level compression, reducing memory and bandwidth requirements while maintaining data fidelity during inference operations.
What changed
The patent application discloses a processing system that converts trained neural network weights into 2D blocks and color data format (monochrome or RGB) before applying block compression algorithms. The compressed data is stored with header information identifying the compression method used. When accessed, the processor decompresses and converts the data back to the original neural network format for inference operations.
This document is a patent application publication and does not create any compliance obligations, regulatory requirements, or deadlines for any parties. Technology companies and AI developers may review the filing as prior art but no action is required.
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Apr 2, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
BLOCK-BASED COMPRESSION OF NEURAL NETWORK DATA
Application US20260093964A1 Kind: A1 Apr 02, 2026
Inventors
Navin Patel
Abstract
A processing system reduces the amount of memory and bandwidth needed to store and access trained neural network data (e.g., trained weights) while maintaining fidelity to the original data by patterning the data into two-dimensional (2D) blocks, converting the data into color data (e.g., monochrome or red, blue, green (RGB) data), and applying block compression to the color data. The compressed data is stored with header information indicating the conversion to color data and block compression algorithm that was used to compress the color data. When a processor subsequently accesses the compressed color data, the processor decompresses the color data and converts the color data back into the original format of the neural network data for application to new inputs during the inference phase.
CPC Classifications
G06N 3/0495
Filing Date
2024-09-30
Application No.
18901476
Named provisions
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