US Patent Application 18339474. INFORMATION GENERATION METHOD AND RELATED APPARATUS simplified abstract

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INFORMATION GENERATION METHOD AND RELATED APPARATUS

Organization Name

HUAWEI TECHNOLOGIES CO., LTD.


Inventor(s)

Yourui Huangfu of Hangzhou (CN)


Jian Wang of Hangzhou (CN)


Rong Li of Hangzhou (CN)


Jun Wang of Hangzhou (CN)


Xiaoyan Bi of Ottawa (CA)


Jianglei Ma of Ottawa (CA)


INFORMATION GENERATION METHOD AND RELATED APPARATUS - A simplified explanation of the abstract

  • This abstract for appeared for US patent application number 18339474 Titled 'INFORMATION GENERATION METHOD AND RELATED APPARATUS'

Simplified Explanation

The abstract describes a method where a second device receives messages from a first and third device. The first message contains information about a first generator, the third message contains information about a third generator, and the second message is sent back to the first device. The first and third generators support different types of input information and are used to train a neural network corresponding to a second generator. The second generator supports both types of input information. The method aims to use real-world data to train a generation model and improve the intelligence and adaptability of a communication network.


Original Abstract Submitted

The method is provided, including: A second device receives a first message and a third message, and sends a second message to a first device. The first message indicates all or a part of a first generator, the third message indicates all or a part of a third generator, an input supported by the first generator includes first information of a first type, an input supported by the third generator includes fourth information of the first type, and the first generator and the third generator are configured to train a neural network corresponding to a second generator; and the second message indicates all or a part of the second generator, and an input supported by the second generator includes the first information and the fourth information. Information collected in a real scenario may be used to train a generation model, to make a communication network more intelligent and adaptive.