Alibaba Group had 132 patents in artificial intelligence during Q1 2024. Alibaba Group Holding Ltd filed patents for near memory processing systems for graph neural network processing, data processing method for machine learning models, memory bandwidth allocation for multiple CPU cores, training and executing multi-density neural networks in video processing, and a configurable processing unit with core and assist processing elements. These patents focus on optimizing data processing, memory allocation, and neural network training for improved performance and efficiency. 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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Alibaba Group grant share with artificial intelligence as a theme is 70% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Neural network near memory processing (Patent ID: US20240104360A1)
The patent filed by Alibaba Group Holding Ltd. describes a near memory processing system for graph neural network processing, where a central core is connected to memory units with controllers and memory devices. The system offloads aggregation operations from the central core to the memory unit controllers, allowing for efficient data processing. The central core schedules memory accesses and operations, while the controllers execute aggregation tasks and provide data back to the central core for further computations. This system aims to enhance the processing efficiency of graph neural networks by distributing tasks between the central core and memory unit controllers.
The patent also includes claims detailing the components and operations of the neural network processing system, such as different compute modes for controllers, memory access requests, aggregation operations, and data output processes. The method involves receiving memory accesses, computing aggregation operations, and outputting result data efficiently. Additionally, the patent outlines the role of the central core in scheduling memory accesses, performing further aggregation operations, and managing data associated with graph nodes and their neighbor nodes. Overall, the patent focuses on optimizing the processing of graph neural networks by utilizing a near memory processing system with central core and memory unit controllers to enhance data processing and computation efficiency.
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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.
