Zuora had five patents in artificial intelligence during Q1 2024. Zuora Inc’s patent filed in Q1 2024 focuses on unsupervised data drift detection for classification neural networks. The method involves analyzing images through a neural network, storing class wise probabilities, comparing artifacts of images over time, and generating informative communications based on these comparisons. GlobalData’s report on Zuora gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Zuora grant share with artificial intelligence as a theme is 80% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Unsupervised data drift detection for classification neural networks (Patent ID: US20240037923A1)
The patent filed by Zuora Inc. discloses methods, systems, and apparatuses for unsupervised data drift detection for classification neural networks. The method involves providing a data stream of images to a neural network, generating class-wise probabilities, storing images and probabilities in databases, comparing artifacts and probabilities at different times, and generating informative communications based on these comparisons. The system includes an image sensor, a neural network, and a processor that performs the data drift detection process by comparing artifacts and probabilities at different times and generating informative communications based on these comparisons.
The method and system are designed to detect data drift in neural networks by comparing artifacts and probabilities over time, allowing for the generation of alerts to system operators when models need updating. The process involves adaptive adjustment of weights based on the comparison values, as well as the ability to compare outputs of retired neural network models with current outputs to further enhance the detection of data drift. Overall, the patent aims to improve the performance and reliability of classification neural networks by detecting and addressing data drift effectively.
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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.
