State Farm Mutual Automobile Insurance had six patents in cloud during Q1 2024. State Farm Mutual Automobile Insurance Co filed patents for systems and methods for predictive data analytics, including generating a guided user interface, training machine learning models, and implementing them on a cloud server for distribution. Another patent focuses on facilitating vehicular incident reenactment using 3D representations, including manipulating images to recreate the incident and generating a 3D reenactment. GlobalData’s report on State Farm Mutual Automobile Insurance gives a 360-degree view of the company including its patenting strategy. Buy the report here.

State Farm Mutual Automobile Insurance grant share with cloud as a theme is 66% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Simplistic machine learning model generation tool for predictive data analytics (Patent ID: US20240095599A1)

The patent filed by State Farm Mutual Automobile Insurance Co. describes systems and methods for predictive data analytics. The method involves generating a guided user interface (GUI) to guide user operations, obtaining a dataset from a database, determining characteristics of data objects, identifying a subset of the dataset, selecting a machine learning algorithm, training a machine learning model, and implementing the trained model in a cloud server for distribution to client devices. The claims detail the steps involved in generating the GUI, constructing machine learning model generation tools, visualizing correlations between data objects, selecting ML algorithms, generating ML models, implementing tools in a cloud server, and performing operations such as dimension reduction, null value treatment, outlier value treatment, and predicting target values. The system includes means for generating the GUI, receiving inputs, obtaining datasets, visualizing correlations, selecting algorithms, generating ML models, and implementing tools in a cloud server.

Overall, the patent outlines a comprehensive method and system for predictive data analytics using machine learning models. It focuses on guiding user operations through a GUI, training ML models, and implementing them in a cloud server for distribution to client devices. The claims provide detailed steps for constructing ML model generation tools, visualizing data correlations, performing dimension reduction, and predicting target values. The system described in the patent includes means for facilitating these operations, emphasizing the user-friendly and efficient nature of the predictive data analytics process.

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