Huawei technologies co., ltd. (20240267762). COMMUNICATION METHOD AND APPARATUS simplified abstract
Contents
COMMUNICATION METHOD AND APPARATUS
Organization Name
Inventor(s)
Xiaomeng Chai of Shanghai (CN)
Yiqun Wu of Boulogne Billancourt (FR)
COMMUNICATION METHOD AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240267762 titled 'COMMUNICATION METHOD AND APPARATUS
Simplified Explanation:
The patent application describes a method and apparatus for communication that involves training data and artificial intelligence models. The method includes obtaining training data with mark information, sending indication information to a terminal device about artificial intelligence models trained based on the training data, and using the training data to train scenario-based artificial intelligence models.
Key Features and Innovation:
- Obtaining training data with mark information
- Sending indication information to a terminal device about artificial intelligence models
- Training artificial intelligence models based on the mark information
- Implementing scenario-based artificial intelligence model training
Potential Applications: This technology can be applied in various industries such as healthcare, finance, marketing, and customer service for improving decision-making processes, predictive analytics, and personalized recommendations.
Problems Solved: This technology addresses the need for efficient training of artificial intelligence models based on specific attributes of training data, enabling scenario-based model training for better performance.
Benefits:
- Enhanced accuracy and efficiency in artificial intelligence model training
- Improved customization and adaptability of models to different scenarios
- Increased effectiveness in decision-making and predictive analytics
Commercial Applications: Title: Enhanced Artificial Intelligence Model Training for Various Industries This technology can be commercially used in sectors such as healthcare for personalized treatment recommendations, finance for risk assessment and fraud detection, marketing for targeted advertising, and customer service for chatbot automation.
Prior Art: Readers can explore prior art related to this technology by researching communication methods, artificial intelligence model training, and scenario-based training techniques.
Frequently Updated Research: Stay updated on the latest advancements in artificial intelligence model training, scenario-based learning, and communication technologies to enhance the application of this technology.
Questions about Artificial Intelligence Model Training: 1. How does the method of obtaining training data with mark information improve artificial intelligence model training? 2. What are the potential challenges in implementing scenario-based artificial intelligence model training?
Original Abstract Submitted
a communication method and apparatus are provided. the method includes: obtaining n pieces of training data, where for one of the n pieces of training data, the training data corresponds to one piece of mark information, and the mark information indicates an attribute of the training data; and sending indication information to a terminal device, where the indication information indicates information about m artificial intelligence models, the artificial intelligence model is trained based on x pieces of training data in the n pieces of training data, and the x pieces of training data are determined based on the mark information. when the n pieces of training data are obtained, the n pieces of training data may be used for constructing training data corresponding to different mark information, to train the m artificial intelligence models or more artificial intelligence models, so that scenario-based artificial intelligence model training can be implemented.
