Context-Aware Prompt Enhancement for Generative AI Personalization
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Solution Overview
Problem
Existing large generative AI models (LXMs) lack personalized interaction capabilities, failing to adapt effectively to user context and preferences, which limits their ability to provide tailored responses and enhance user experience.
Innovation Solution
A computing system that recognizes users, obtains user context information, and selects user profiles based on user context and prompts, generating enhanced prompts for LXMs to improve interaction relevance and personalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If LXMs are trained on extensive datasets to enhance their understanding and generation capabilities, then their functionality and applicability are improved, but they lack personalized interaction capabilities and cannot adapt to user context and preferences
Solution Approach 1:
The system segments the LXM interaction into multiple components: a profile selection module that identifies relevant user profiles based on context, an enhancement module that modifies prompts using profile information, and the LXM itself. This segmentation allows personalization without retraining the entire LXM, reducing complexity while improving adaptability.
Solution Approach 2:
The patent introduces user profiles as an intermediary layer between the user and the LXM. These profiles store contextual information and preferences, serving as a mediator that enables personalized interaction without requiring the LXM to directly process or remember all user-specific details, thus improving adaptability while managing system complexity.
2Measurement precision
If the system collects and processes user context information to generate enhanced prompts, then interaction relevance and personalization are improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing user context information into structured profiles before actual LXM interactions occur. User profiles are built and maintained in advance, containing contextual data and preferences that can be quickly retrieved and applied during prompt enhancement, reducing real-time processing requirements.
Solution Approach 2:
The system applies partial action by selectively enhancing prompts only when context information is available and relevant. Not all LXM interactions require full prompt enhancement - the system judiciously applies profile-based modifications based on the specific interaction context, balancing personalization benefits against processing overhead.
Data Source
AI summary
Various embodiments include systems and methods for generating a prompt for a generative artificial intelligence (AI) models. A processing system including at least one processor may be configured to recognize a user of the computing device, obtain user context information from a source of physical context information in the computing device, receive a user prompt for the large generative AI model (LXM), select a user profile from among a plurality of user profiles based on the user, the user context information and the user prompt, generate an enhanced prompt based on the user prompt and information included in the selected user profile, and submit the enhanced prompt to the LXM.