Fujitsu had 171 patents in artificial intelligence during Q1 2024. Fujitsu Ltd filed patents in Q1 2024 for processes involving machine learning techniques such as predicting value distributions, integrating user transaction tendencies, calculating latent variables, and predicting the influence of target objects. These processes aim to improve model creation and updating, data encoding, and impact analysis using innovative algorithms and data manipulation methods. GlobalData’s report on Fujitsu gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Fujitsu grant share with artificial intelligence as a theme is 37% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Information processing apparatus and prediction method (Patent ID: US20240104107A1)
The patent filed by Fujitsu Ltd. describes a computer program stored on a non-transitory computer-readable medium that executes a process involving identifying similar feature information among time-series data, obtaining predicted value distributions based on this information, combining these distributions, and determining a range of predicted values for the target time-series data. The process involves comparing feature information of different time-series data to the processing target data, using machine learning to generate prediction models, and considering data at specific time periods to predict future values accurately.
Furthermore, the patent includes claims for an information processing apparatus and a prediction method that follow the same steps as the described process. These claims detail the identification of feature information, obtaining predicted value distributions, combining them, and determining a range of predicted values based on the combined distribution. The method involves comparing feature information, considering data at specific time periods, and using machine learning to generate prediction models for accurate forecasting. The patent aims to provide a systematic approach to predicting future values of time-series data by leveraging similar feature information and combining predicted value distributions 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.
