AI Model Interface Translation for Format Change Compatibility
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Solution Overview
Problem
Existing artificial intelligence models face issues such as model drift and changes in input/output formats, which can impact applications using them, necessitating costly and time-consuming updates to these applications.
Innovation Solution
A computer-implemented method and system, including an information manager, detects changes in the format of information exchanged between AI models and applications, converting it into an expected format to maintain seamless interaction without requiring updates to the applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If AI models are updated to address model drift and accuracy issues, then model performance is improved, but application compatibility deteriorates due to format changes
Solution Approach 1:
The patent introduces a format translation layer as an intermediary between the AI model and the application. This layer automatically translates between the model's internal format and the application's expected format, allowing model updates without application modifications. The translator acts as a mediator that absorbs format changes in the model while presenting a stable interface to the application.
Solution Approach 2:
The system is segmented into distinct components: the AI model, the format translator, and the application. By separating the format translation functionality from both the model and application, the patent enables independent evolution of the model while maintaining application stability. The translator segment handles format differences without requiring changes to either endpoint.
2Manufacturing precision
If format changes are made in AI models, then model accuracy is improved, but implementation complexity increases due to required application updates
Solution Approach 1:
The format translator serves as an intermediary that handles the complexity of format conversions. Instead of requiring applications to directly adapt to model format changes, the translator absorbs this complexity and manages the translation between different formats, significantly reducing implementation complexity.
Solution Approach 2:
The system performs preliminary format translation when data flows from the model to the application. The translator proactively converts formats before the application receives the data, preventing format mismatch issues and eliminating the need for applications to implement complex format adaptation logic.
3Adaptability or versatility
If applications are updated to match new model formats, then format compatibility is improved, but time and cost increase due to modification requirements
Solution Approach 1:
The format translator is an intermediary component that enables format compatibility without requiring application updates. The translator handles all format conversion logic, allowing applications to continue operating with minimal changes while the model evolves its formats independently.
Solution Approach 2:
The patent creates a virtual copy of the format interface through the translator layer. This virtual interface presents a stable, consistent format to the application while the actual model uses different formats. The translator copies and transforms the data as needed, eliminating the need for applications to directly copy or adapt to model format changes.
Data Source
AI summary
A computer implemented method manages an artificial intelligence model. A number of processor units detect a change in a format used to exchange information between the artificial intelligence model and an application using the artificial intelligence model. The number of processor units changes the format of the information into an expected format used by the artificial intelligence model and the application. The number of processor units exchanges the information between the artificial intelligence model and the application using the expected format.