18406747. ARTIFICIAL INTELLIGENCE DEVICE FOR EVALUATION AND CONTROL METHOD THEREOF simplified abstract (LG Electronics Inc.)
Contents
ARTIFICIAL INTELLIGENCE DEVICE FOR EVALUATION AND CONTROL METHOD THEREOF
Organization Name
Inventor(s)
Harmanpreet Singh of Toronto (CA)
Royaldenzil Sequiera of Kitchener (CA)
ARTIFICIAL INTELLIGENCE DEVICE FOR EVALUATION AND CONTROL METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 18406747 titled 'ARTIFICIAL INTELLIGENCE DEVICE FOR EVALUATION AND CONTROL METHOD THEREOF
The abstract describes a method for controlling an artificial intelligence (AI) device by training a link prediction model on a knowledge graph, extracting logic rules from the model, generating evaluation metrics based on these rules, comparing the metrics to predetermined criteria, and outputting the evaluation results.
- Obtaining a knowledge graph and training a link prediction model on it
- Extracting logic rules from the trained model
- Generating evaluation metrics based on the logic rules
- Comparing the metrics to predetermined criteria to generate evaluation results
- Saving or transmitting the trained model based on the evaluation results
Potential Applications: - Enhancing the decision-making capabilities of AI devices - Improving the accuracy of predictions made by AI systems - Streamlining the deployment process of trained models
Problems Solved: - Enhancing the efficiency and effectiveness of AI devices - Providing a systematic approach to evaluating AI models - Facilitating the deployment of trained models in various applications
Benefits: - Increased accuracy and reliability of AI predictions - Streamlined deployment process for trained models - Enhanced decision-making capabilities of AI devices
Commercial Applications: Title: "Enhanced AI Model Control Method for Improved Predictions" This technology can be applied in various industries such as finance, healthcare, and e-commerce to optimize decision-making processes, improve customer recommendations, and enhance overall operational efficiency.
Questions about AI Model Control: 1. How does this method improve the performance of AI devices? - By training a link prediction model on a knowledge graph and extracting logic rules, the method enhances the decision-making capabilities of AI devices, leading to improved predictions and outcomes.
2. What are the potential implications of using this method in commercial applications? - The method can significantly impact various industries by optimizing decision-making processes, improving customer recommendations, and enhancing operational efficiency.
Original Abstract Submitted
A method for controlling an artificial intelligence (AI) device can include obtaining, via a processor in the AI device, a knowledge graph, training, via the processor, a link prediction model on the knowledge graph to generate a trained link prediction model, extracting, via the processor, logic rules from the trained link prediction model, generating, via the processor, at least one evaluation metric based on the logic rules, and generating, via the processor, evaluation results based on comparing the at least one evaluation metric to a predetermined criteria, and outputting, via an output unit in the AI device, the evaluation results. Also, the method can include saving the trained link prediction model in a memory of the AI device for deployment or transmitting the trained link prediction model to an external device for deployment, based on the evaluation results.
