17988601. METHOD AND APPARATUS FOR SUPPORTING AUTOMATED RE-LEARNING IN MACHINE TO MACHINE SYSTEM simplified abstract (Kia Corporation)
METHOD AND APPARATUS FOR SUPPORTING AUTOMATED RE-LEARNING IN MACHINE TO MACHINE SYSTEM
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METHOD AND APPARATUS FOR SUPPORTING AUTOMATED RE-LEARNING IN MACHINE TO MACHINE SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 17988601 titled 'METHOD AND APPARATUS FOR SUPPORTING AUTOMATED RE-LEARNING IN MACHINE TO MACHINE SYSTEM
Simplified Explanation
The present disclosure describes a method for automated re-learning in a machine-to-machine (M2M) system. This method involves training an artificial intelligence (AI) model, performing initial learning of the AI model, collecting learning data for re-learning, and performing re-learning of the AI model using the collected data.
- The method involves generating a resource for training an AI model.
- The AI model undergoes initial learning to acquire knowledge and skills.
- Learning data is collected to improve the AI model's performance.
- The collected data is used to re-learn the AI model, enhancing its capabilities.
Potential Applications
- This technology can be applied in various M2M systems, such as autonomous vehicles, industrial automation, and smart home devices.
- It can be used to improve the performance and adaptability of AI models in real-time applications.
Problems Solved
- Traditional AI models often require manual intervention for re-learning, which can be time-consuming and inefficient.
- This method automates the re-learning process, allowing AI models to continuously improve without human intervention.
- It addresses the challenge of keeping AI models up-to-date and adaptable in dynamic environments.
Benefits
- The automated re-learning process saves time and effort by eliminating the need for manual intervention.
- It enables AI models to adapt and improve their performance based on real-time data.
- This technology enhances the overall efficiency and effectiveness of M2M systems by continuously updating and refining AI models.
Original Abstract Submitted
The present disclosure may support automated re-learning in a machine-to-machine (M2M) system. A method for operating a device may include: generating a resource for training an artificial intelligence (AI) model; controlling to perform initial learning of the AI model; collecting learning data for re-learning for the AI model; and controlling to perform re-learning of the AI model by using the learning data.