Alibaba Group has been granted a patent for methods and devices involving neural network models. The technology classifies matrix sections based on distribution patterns of non-zero elements and loads them into vector registers using specific orders. GlobalData’s report on Alibaba Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Alibaba Group, Blockchain-based property authentication was a key innovation area identified from patents. Alibaba Group's grant share as of February 2024 was 44%. Grant share is based on the ratio of number of grants to total number of patents.

Efficient loading of non-zero elements in neural network models

Source: United States Patent and Trademark Office (USPTO). Credit: Alibaba Group Holding Ltd

A recently granted patent (Publication Number: US11921814B2) outlines a method for efficiently processing neural network models. The method involves receiving a matrix of the neural network model and classifying different portions of the matrix based on distribution patterns of non-zero elements. By identifying memory addresses of these elements and loading them into vector registers in a specific order determined by the distribution pattern, the method aims to optimize the processing of the neural network model.

Furthermore, the patent details the classification of matrix sections, generation of instruction sets based on memory addresses, and the execution of matrix multiplication operations between weight matrices and input matrices. The method also addresses the handling of pruned matrices and the association of distribution patterns with the number of rows or columns occupied by non-zero elements. By efficiently organizing and processing data in neural network models, this patented method offers potential improvements in computational efficiency and performance for various applications in the field of artificial intelligence and machine learning.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.