STMicroelectronics had 33 patents in artificial intelligence during Q1 2024. STMicroelectronics NV filed patents in Q1 2024 for an artificial neural network unit cell, a device for efficient multiplication and accumulation, a device for detecting if it is inside a bag, a memory array with low and high voltage cells, and a convolutional accelerator for efficient convolution operations. GlobalData’s report on STMicroelectronics gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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STMicroelectronics grant share with artificial intelligence as a theme is 57% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Artificial neuron network having at least one unit cell quantified in binary (Patent ID: US20240095502A1)
The patent filed by STMicroelectronics NV describes an artificial neural network architecture that includes a unit cell with specific components such as binary two-dimensional convolution layers, batch normalization layers, and concatenation layers. The unit cell processes input tensors to generate output tensors through a series of operations involving convolution, normalization, and concatenation. The network architecture can include multiple unit cells arranged in succession to perform complex data processing tasks efficiently.
The claims associated with the patent detail the specific configurations and functionalities of the components within the artificial neural network, such as depthwise and pointwise convolutions, attribute extraction layers, classification layers, and detection layers. The network architecture can be implemented in various forms, including as a computer program product or a device with processing circuitry. The method outlined in the patent involves a step-by-step process of generating tensors within the unit cell using convolution, normalization, and concatenation operations, highlighting the innovative approach to neural network design presented in the patent.
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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.
