AI Answer Generation With Auction-Based Provider Selection
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Solution Overview
Problem
Existing large language models (LLMs) lack the ability to dynamically incorporate and project messages from multiple information providers, limiting the personalization and relevance of generated answers.
Innovation Solution
A method and system that selects an information provider through an auction process based on LLM results, dynamically generates answers using assets and prompts registered by the provider, and reflects user information to create personalized and relevant responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing large language models are used to generate answers, then the generation process is simple and fast, but the answers lack personalization and relevance to multiple information providers
Solution Approach 1:
The system segments the answer generation process into distinct modules: LLM-based answer generation, information provider selection through auction mechanism, and dynamic answer composition. This segmentation allows each component to specialize in specific tasks while maintaining overall system manageability.
Solution Approach 2:
The patent merges multiple functions into a unified system: combining LLM answer generation with information provider selection and answer composition. The auction mechanism integrates multiple information providers into a single coordinated system that dynamically selects and combines their contributions.
2Loss of information
If multiple information providers are incorporated into the answer generation, then the personalization and relevance improve, but the system complexity and computational resources increase
Solution Approach 1:
The auction mechanism serves as an intermediary layer between multiple information providers and the final answer generation. It coordinates provider selection and resource allocation without requiring direct complex interactions between all providers, simplifying the overall system architecture.
Solution Approach 2:
The system dynamically adjusts information provider selection and answer composition based on real-time auction outcomes and user needs. This dynamic approach allows the system to optimize information integration without permanent complex structures for handling all possible provider combinations.
3Measurement precision
If an auction mechanism is introduced to select information providers, then the selection accuracy and relevance improve, but the time and computational resources required increase
Solution Approach 1:
The auction mechanism operates partially by focusing computational resources on selecting a limited number of top-ranked information providers rather than evaluating all possible providers exhaustively. This partial action approach achieves sufficient selection accuracy while reducing overall computational time and resources.
Data Source
AI summary
A method for dynamically generating an artificial intelligence-based answer including a message of an information provider includes selecting a first information provider from among a plurality of information providers on the basis of a large language model (LLM) result generated based on an LLM with respect to a user's prompt; dynamically generating an answer reflecting information registered in association with the selected first information provider; and providing the generated answer.