AI Model Data Block Transmission for Flexible Communication
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Solution Overview
Problem
The transmission efficiency and flexibility of information related to artificial intelligence (AI)/machine learning (ML) models in communication systems are insufficient in existing technologies.
Innovation Solution
The implementation of block-wise transmission of AI/ML model information, allowing operations on data blocks obtained by dividing the AI information, enhances transmission efficiency and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI information is transmitted as a whole, then transmission simplicity is maintained, but transmission efficiency is low
Solution Approach 1:
The patent divides AI information into multiple data blocks, each with a unique identifier. This segmentation allows parallel transmission of multiple blocks, improving overall transmission efficiency while maintaining manageable complexity through systematic block identification and assembly protocols
2Adaptability or versatility
If AI information is transmitted as a whole, then transmission process is simple, but transmission flexibility is insufficient
Solution Approach 1:
By segmenting AI information into independent data blocks with identifiers, the system enables selective transmission, retransmission, and parallel processing of different blocks, significantly enhancing transmission flexibility while managing complexity through structured block management
Solution Approach 2:
The patent implements dynamic transmission strategies where data blocks can be transmitted, acknowledged, and retransmitted independently based on reception status. This dynamic approach allows adaptive resource allocation and error recovery, improving flexibility without overwhelming system complexity
3Productivity
If AI information is divided into data blocks, then transmission efficiency is improved, but system complexity increases
Solution Approach 1:
The segmentation of AI information into numbered data blocks enables efficient parallel transmission and processing. The systematic numbering and identification scheme allows receivers to process blocks independently and reassemble them in correct order, achieving high transmission efficiency while controlling complexity through standardized block management protocols
Data Source
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AI summary
The disclosure discloses an information transmission method and apparatus, a device, a medium, and a program product, which belongs to the field of communication. The method is performed by a first device and includes the following. The first device performs a transmission-related operation on artificial intelligence (AI) information and/or at least one data block associated with the AI information and/or an AI information data packet associated with the at least one data block associated with the AI information. The at least one data block is obtained by dividing the AI information. The AI information is information related to an AI/machine learning (ML) model. According to the method, the first device performs the transmission-related operation on the AI information and/or the at least one data block associated with the AI information and/or the AI information data packet associated with the at least one data block associated with the AI information. In this way, transmission of a part of AI/ML model data is realized, thereby improving the transmission efficiency and the transmission flexibility of the information related to the AI/ML model.