Information Processing With Prompt-Based AI Selection for Accurate Responses
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Solution Overview
Problem
Conventional AI technologies face challenges in generating appropriate responses due to varying training circumstances, leading to inconsistent and suboptimal outputs.
Innovation Solution
An information processing apparatus that selects the most suitable generative AI from a plurality of options based on information extracted from user prompts, utilizing slot filtering, extraction models, and context analysis to generate precise responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single generative AI is used to process all prompts, then the system complexity is reduced, but the response accuracy and appropriateness deteriorate due to varying training circumstances of different AI models
Solution Approach 1:
The system segments the generative AI resources into multiple specialized models (e.g., text-generation AI, image-generation AI, translation AI) with different training circumstances and capabilities. Instead of using a single general-purpose AI for all tasks, the system divides the AI processing function into multiple specialized components that can be selectively applied based on the prompt requirements, thereby improving response accuracy without requiring the user to manage the complexity of selecting and configuring individual AI models.
Solution Approach 2:
The system introduces an intermediary management layer that automatically selects and coordinates multiple generative AI models based on the prompt characteristics. This intermediary component handles the complexity of AI model selection, configuration, and switching, allowing users to benefit from multiple specialized AI models without directly dealing with their individual complexities. The intermediary translates user prompts into appropriate AI model selections and manages the integration of different AI outputs.
2Adaptability or versatility
If multiple generative AI models are maintained with different training circumstances, then the adaptability to various prompt types improves, but the resource consumption and system complexity increase
Solution Approach 1:
The system implements a universal AI management platform that can handle multiple types of generative AI models through a common interface and selection mechanism. This universal platform provides multi-functional capabilities by automatically routing different prompt types to appropriate specialized AI models (text, image, translation, etc.), allowing the system to maintain adaptability to various prompt types while avoiding the need for users to directly manage multiple AI model resources. The universal platform abstracts the complexity of resource management from the user.
Solution Approach 2:
The system dynamically changes parameters such as AI model selection, processing mode, and resource allocation based on the characteristics of the input prompt. By analyzing prompt parameters (type, complexity, required output format), the system automatically adjusts which AI models are activated and how resources are distributed, thereby maintaining high adaptability to different prompt types while optimizing resource consumption by only activating necessary AI models on demand rather than maintaining all models in constant operation.
3Ease of operation
If AI selection is performed manually by users, then the ease of operation is reduced, but the transparency and user control over the AI selection process improves
Solution Approach 1:
The system implements feedback mechanisms that provide users with information about which AI model is being used and why it was selected for their prompt. This feedback can include details about the AI model's specialization, expected performance characteristics, and confidence levels. By providing this feedback, the system maintains ease of operation (automatic selection) while reducing information loss (user awareness), allowing users to understand and trust the AI selection process without needing to manually intervene in the selection process.
Data Source
AI summary
An information processing apparatus according to the present application includes a reception unit, a selection unit, and a providing unit. The reception unit receives a query including a prompt sent from a user or a query for obtaining the prompt. The selection unit selects, based on information on a plurality of items included in the prompt, AI that is used to generate response information indicating a response to the prompt from among a plurality of pieces of AI. The providing unit provides the response information that has been generated by using the AI selected by the selection unit to the user.