AI Output Refinement via Segmentation and Mediator Patterns
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Solution Overview
Problem
Existing AI models generate voluminous raw output data that is difficult to interface with, as it includes irrelevant information, making it challenging to extract relevant insights efficiently.
Innovation Solution
A computing system refines the output data based on characteristics of the AI model and input data set, identifying relevant interface elements such as operators and visualizations to effectively communicate and present the refined results to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If AI models generate comprehensive output data, then the completeness of information is improved, but the difficulty of interfacing and processing increases
Solution Approach 1:
The patent segments the comprehensive AI output data into multiple organized components including identified objects, their properties, relationships between objects, and confidence levels. This segmentation allows the system to maintain complete information while making it easier to interface with by organizing data into structured, accessible components that can be individually processed.
Solution Approach 2:
The patent introduces an intermediary processing layer that sits between the AI model output and the user interface. This intermediary component automatically structures, filters, and organizes the raw AI output into standardized formats, reducing the complexity of interfacing while preserving all necessary information through systematic data transformation.
2Loss of information
If AI models process all input data, then the completeness of analysis is improved, but the time required for processing increases
Solution Approach 1:
The patent applies preliminary action by pre-defining the structure and categories of output data that the AI model will generate. By establishing templates for objects, properties, relationships, and confidence levels beforehand, the system guides the AI processing to produce organized results more efficiently, reducing post-processing time while maintaining complete analysis coverage.
3Loss of information
If raw output data from AI models is presented directly to users, then the amount of information provided is improved, but the usability and interpretability deteriorates
Solution Approach 1:
The patent applies local quality by presenting different levels of information detail to different users or for different purposes. The system can provide comprehensive data when needed while also offering simplified, user-friendly summaries for general use. This allows the same information source to serve both complete information needs and ease of use requirements through localized presentation quality adjustment.
Data Source
AI summary
The improved exercise of artificial intelligence by providing a systematic way for a computing system to interface with output from AI models. To do this, the computing system obtains results of an input data set being applied to an AI model. The results are then refined based upon characteristic(s) of the AI model and perhaps the input data set. Based upon characteristic(s) of the AI model and perhaps the input data set, interface element(s) are identified that can be used to interface with the refined results. The interface element(s) are then communicated to an interface element that interfaces with the refined results. The interface element(s) may include, for instance, operator(s) or term(s) that may be used to query against the refined results and/or an identification of visualization(s) that may be used to present to a user results of queries against the refined results.