AI Model Registration with Global IDs for Cross-Device Compatibility
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Solution Overview
Problem
Inconsistent model management and understanding between network-side devices and terminals leads to improper usage of AI/ML models, resulting in incompatibility issues.
Innovation Solution
A model registration method that assigns a globally unique identifier to models, allowing for unified management and conversion of models to ensure compatibility across different devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different devices use different model formats and management methods, then each device can optimize its own model processing, but model incompatibility and consistency issues arise between devices
Solution Approach 1:
The patent introduces a universal model management mechanism where a globally unique model identifier serves as a common interface between network-side devices and terminals. This identifier enables different devices with different model formats to communicate and exchange models effectively, achieving universality in model management while preserving device-specific optimizations
Solution Approach 2:
The model identifier acts as an intermediary element between the model file and the devices. Instead of devices directly interacting with model files in different formats, they use the standardized identifier to reference, request, and exchange models, simplifying the interaction while ensuring compatibility
2Reliability
If a globally unique model identifier system is implemented, then model compatibility and consistency improve, but system complexity and overhead increase
Solution Approach 1:
The system performs preliminary model registration with globally unique identifier assignment before actual model usage. This advance preparation ensures that models are properly cataloged and identifiable, preventing compatibility issues during execution while keeping the runtime overhead minimal
Solution Approach 2:
The model identifier system provides feedback mechanisms where devices can query model information, check compatibility, and receive appropriate models based on their capabilities. This feedback loop ensures reliable model execution while allowing devices to manage their model inventory efficiently
Data Source
AI summary
A model processing method includes sending, by a first device, a first message to at least one second device. The first message includes a first model file corresponding to a first model, and receiving, by the first device, a second message returned by the second device. The second message includes at least one of the following; processing result information used for indicating a result obtained by processing the first model file, or a second model file, where the second model file is obtained by converting the first model file.


