ASUSTeK Computer had three patents in future of work during Q4 2023. ASUSTeK Computer Inc filed patents for an artificial intelligence model control system, a controller for a power conversion circuit, and a sensing data accessing method/system. The AI model control system includes multiple modules controlled by a single controller, the power conversion circuit controller uses a smart power stage to convert voltage and monitor current, and the sensing data accessing method/system involves storing and accessing sensor data in a shared memory for performing operations. GlobalData’s report on ASUSTeK Computer gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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ASUSTeK Computer grant share with future of work as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Artificial intelligence model control system (Patent ID: US20230408987A1)
The patent filed by ASUSTeK Computer Inc. describes an artificial intelligence model control system that includes multiple artificial intelligence model service modules, corresponding model plugins, and a model controller. Each model plugin communicates with a specific artificial intelligence model service module, allowing the model controller to control all modules to perform tasks efficiently. The system operates by generating requests from the model plugins based on instructions from the model controller, with responses transmitted back to the controller through the plugins.
Furthermore, the artificial intelligence model control system can include a user interface for data input, and the model plugins can be independent dynamic link libraries. Tasks that can be performed by the system include training, verification, deployment, and inference. The system can be deployed on the same computer mainframe or across different computers, with the ability to disable specific modules directly in the model controller when needed. Overall, the system provides a centralized and efficient way to control multiple artificial intelligence model service modules through a single model controller, enhancing the overall performance and management of AI tasks.
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