18598592. COMMUNICATION METHOD AND APPARATUS simplified abstract (Huawei Technologies Co., Ltd.)
Contents
COMMUNICATION METHOD AND APPARATUS
Organization Name
Inventor(s)
Xiaomeng Chai of Shanghai (CN)
COMMUNICATION METHOD AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18598592 titled 'COMMUNICATION METHOD AND APPARATUS
Simplified Explanation: The patent application describes a method and apparatus for communication where a terminal autonomously performs model training based on training data received from a network device, reducing the need for separately configuring an AI model for the terminal.
- The terminal receives first information from a network device.
- Based on the first information, the terminal determines N pieces of training data, where N is an integer.
- The terminal performs model training based on the N pieces of training data to obtain a first AI model.
- The network device configures the first information used to determine the N pieces of training data for the terminal.
- The terminal autonomously performs model training based on the N pieces of training data, eliminating the need for separate AI model configuration and reducing air interface overheads.
Potential Applications: 1. Industrial automation 2. Healthcare diagnostics 3. Financial forecasting 4. Autonomous vehicles 5. Smart home systems
Problems Solved: 1. Streamlining AI model training processes 2. Reducing configuration complexity 3. Minimizing air interface overheads 4. Enhancing efficiency of data processing 5. Improving overall system performance
Benefits: 1. Increased automation 2. Faster model training 3. Reduced overhead costs 4. Enhanced data processing capabilities 5. Improved system reliability
Commercial Applications: Optimizing AI model training processes for various industries, potentially leading to cost savings and improved operational efficiency.
Questions about the Technology: 1. How does the terminal determine the N pieces of training data based on the first information? 2. What are the potential implications of reducing air interface overheads in communication systems?
Frequently Updated Research: Stay updated on advancements in autonomous model training and communication technologies to leverage the latest innovations in the field.
Original Abstract Submitted
A communication method and apparatus. A terminal receives first information from a network device. The terminal determines N pieces of training data based on the first information, and N is an integer. The terminal performs model training based on the N pieces of training data, to obtain a first AI model. The network device configures the first information used to determine the N pieces of training data for the terminal. The terminal performs model training based on the N pieces of training data autonomously. Separately configuring an AI model for the terminal is not necessary and air interface overheads are reduced.
