AI Cognitive Cloud Service for Multi-Format Data Processing
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Solution Overview
Problem
Current machine learning and AI solutions are limited to isolated and specialized domains, failing to effectively integrate and analyze vast volumes of text, audio, picture, and video data in real-time, lacking the ability to provide comprehensive, human-like cognitive analysis.
Innovation Solution
A cloud-based AI cognitive service system that integrates AI and ML modules for automatic format detection and processing of text, audio, and video data, performing tasks like translation, recognition, and content analysis, generating enriched outputs through a unified platform that resembles human cognitive processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple AI modules are integrated to process diverse data types (text, audio, picture, video), then the comprehensiveness of cognitive analysis is improved, but the system complexity increases
Solution Approach 1:
The patent implements a universal cognitive service system that can process multiple data types (text, audio, picture, video) through a single integrated platform. The system uses a common architecture with format detection capabilities that automatically identify and route different data types to appropriate processing modules, allowing one system to perform multiple functions without requiring separate specialized systems for each data type.
Solution Approach 2:
The patent introduces intermediary components including a format detection module and data collection modules that act as mediators between the diverse input data types and the processing AI modules. These intermediaries standardize the data flow and interface between different data formats and the underlying AI processing engines, simplifying the integration complexity by providing a unified access layer.
2Speed
If real-time processing of vast volumes of data is implemented, then the responsiveness of the system is improved, but the computational resources required increase
Solution Approach 1:
The patent divides the data processing task into segmented operations: format detection first, then routing to specific AI modules based on data type, and finally collecting results through dedicated data collection modules. This segmentation allows the system to process data in manageable stages rather than requiring all computational resources simultaneously, improving real-time responsiveness while optimizing resource utilization through staged processing.
3Measurement precision
If human-like cognitive analysis is provided through integrated AI modules, then the quality of insights is improved, but the difficulty of system integration increases
Solution Approach 1:
The patent employs intermediary data collection modules that serve as mediators between the various AI processing modules and the final output generation. These intermediaries aggregate results from multiple AI modules (natural language processing, speech recognition, object recognition, etc.) and synthesize them into coherent human-like insights, maintaining high analysis quality while managing integration complexity through a standardized collection interface.
Data Source
AI summary
Embodiments provide cognitive cloud services. Embodiments receive, via an input Application Programming Interface (“API”), input data, the input data including one or more of text data, picture data, audio data and video data. Embodiments determine one or more formats of the input data and, based on the determined formats, select one or more of artificial intelligence based modules for processing of the input data. Embodiments collect an output resulting from the processing of the input data and enrich the output. Embodiments then provide the enriched output via an output API.