18588053. INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM simplified abstract (CANON KABUSHIKI KAISHA)
Contents
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM
Organization Name
Inventor(s)
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18588053 titled 'INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND STORAGE MEDIUM
Simplified Explanation: The patent application describes an information processing apparatus that uses two machine learning models, with the second model having changes in its network structure compared to the first model.
- The performing unit conducts inference on input data using the first machine learning model.
- The selecting unit switches to the second machine learning model when certain conditions are met, with alterations in the network structure.
- The second model includes changes in parameters or connections between nodes in the components of the first model.
Key Features and Innovation:
- Utilization of two machine learning models with varying network structures.
- Dynamic selection of the second model based on predetermined conditions.
- Modification of parameters or paths in the second model for improved performance.
Potential Applications: The technology can be applied in various fields such as:
- Predictive analytics
- Image recognition
- Natural language processing
Problems Solved:
- Enhances the accuracy and efficiency of machine learning inference.
- Allows for adaptability to changing conditions or data patterns.
Benefits:
- Improved performance in processing and analyzing data.
- Flexibility in choosing the most suitable machine learning model.
- Enhanced decision-making capabilities based on changing requirements.
Commercial Applications: Potential commercial uses include:
- Developing advanced AI systems for various industries.
- Enhancing data analysis tools for businesses.
- Improving automation processes in manufacturing and logistics.
Questions about Machine Learning Models: 1. How do the changes in the network structure of the second machine learning model impact its performance compared to the first model? 2. What specific conditions trigger the selection of the second machine learning model over the first model?
Original Abstract Submitted
There is provided with an information processing apparatus. A performing unit performs inference on an input using a first machine learning model. A selecting unit selects a second machine learning model, in which at least some of components of a network structure of the first machine learning model have been changed, as a machine learning model used for the inference, in response to a predetermined condition being satisfied. The first machine learning model has a first component and a second component. The second machine learning model has at least a component in which a parameter or a path between nodes in the first component or the second component has been changed.
