18442355. METHOD AND INFORMATION PROCESSING APPARATUS simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)
Contents
METHOD AND INFORMATION PROCESSING APPARATUS
Organization Name
TOYOTA JIDOSHA KABUSHIKI KAISHA
Inventor(s)
METHOD AND INFORMATION PROCESSING APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18442355 titled 'METHOD AND INFORMATION PROCESSING APPARATUS
Simplified Explanation: The patent application describes a system where an information processing apparatus transmits information to multiple other apparatuses to evaluate a machine learning model. The evaluation results are aggregated and used to update the model.
Key Features and Innovation:
- Information processing apparatus transmits parameters to multiple other apparatuses for evaluation.
- Evaluation results are aggregated and used to update the machine learning model.
Potential Applications: This technology can be applied in various fields such as healthcare, finance, marketing, and more where machine learning models are utilized for decision-making processes.
Problems Solved:
- Efficient evaluation of machine learning models.
- Streamlined updating process for machine learning models.
Benefits:
- Improved accuracy of machine learning models.
- Faster model updates based on evaluation results.
Commercial Applications: The technology can be used in industries such as healthcare for predictive analytics, finance for risk assessment, and marketing for customer segmentation, leading to more accurate and efficient decision-making processes.
Prior Art: Prior research in the field of machine learning model evaluation and updating methods can provide insights into similar technologies and approaches.
Frequently Updated Research: Stay updated on advancements in machine learning model evaluation techniques and methodologies to enhance the efficiency and accuracy of the technology.
Questions about Machine Learning Model Evaluation: 1. How does this technology improve the efficiency of evaluating machine learning models? 2. What are the potential applications of this technology in different industries?
Original Abstract Submitted
A first information processing apparatus transmits first information used for acquiring values of parameters of a machine learning model to a plurality of second information processing apparatuses. The plurality of the second information processing apparatuses acquire an evaluation value of the machine learning model when the value of the parameters acquired based on the first information is applied to the machine learning model, and transmit the evaluation value to the first information processing apparatus. The first information processing apparatus aggregates a plurality of evaluation values received from the plurality of the second information processing apparatuses, and transmits the aggregate result of the evaluation values to the plurality of the second information processing apparatuses. The first information processing apparatus and the plurality of the second information processing apparatuses update the machine learning model based on the aggregate result of the evaluation values.
