FQL System for Media Query Translation and AI Model Selection
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Solution Overview
Problem
Existing technologies fail to efficiently manage and analyze large media repositories, particularly in identifying synthetic media and integrating media information with programmatic functions, leading to difficulties in recognizing synthetic content and providing reliable information about stored videos.
Innovation Solution
A Face-based Query Language (FQL) system that enables efficient querying and analysis of media by transforming natural language queries into structured FQL queries, selecting appropriate artificial intelligence models for image or video analysis, and providing responses in natural language, thereby improving media management and integration with programmatic operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large media repositories are stored and managed using previous technology, then media storage capacity is improved, but the ability to efficiently query and identify specific media (such as videos containing particular individuals) deteriorates
Solution Approach 1:
The patent introduces a query translation system that acts as an intermediary between natural language queries and the media repository. This system translates high-level natural language queries into structured FQL queries that can be efficiently processed by the AI models, enabling efficient searching in large media repositories without requiring direct complex queries to the storage system.
Solution Approach 2:
The patent replaces traditional mechanical search methods with AI-based image and video analysis models. Instead of using conventional database search mechanisms, the system employs trained AI models to analyze media content and retrieve results based on visual and audio characteristics, significantly improving query efficiency in large repositories.
2Reliability
If AI models are used to detect synthetic media, then detection capability is improved, but computing resource consumption increases
Solution Approach 1:
The patent applies partial action by selectively executing AI models based on the specific query requirements. Instead of running all available AI models for every query, the system determines which models are necessary for the given query and executes only those, reducing unnecessary computing resource consumption while maintaining effective detection capability.
Solution Approach 2:
The patent changes the parameter of model selection dynamically based on query characteristics. The system adjusts which AI models are executed according to the specific detection task requirements, optimizing the balance between detection reliability and computing resource consumption by selecting appropriate models for each query scenario.
3Measurement precision
If comprehensive media analysis is performed, then information accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the media analysis process into distinct components, each handled by specialized AI models. The query translation system divides complex analysis tasks into specific sub-tasks (such as face detection, scene recognition, audio analysis), allowing each segment to be processed independently and efficiently, improving overall speed while maintaining comprehensive accuracy.
Data Source
AI summary
A computing device generates a call in a programming language of a computing application requesting a feature of videos stored in a media repository. A query system receive the call and determines a command associated with obtaining the feature requested by the call. The determined command corresponds to an image analysis to perform on at least a portion of the stored videos. The query system determines, based at least in part on the determined command, an artificial intelligence model to execute on at least the portion of the stored videos. The query system determine, by executing the determined artificial intelligence model, a model output that includes the requested feature. The query system provides, in the programming language of the computing application, an indication of the requested feature.