Generative AI Digital Personas for Responsive SME Knowledge Sharing
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Solution Overview
Problem
Existing avatar or digital twin solutions provide static representations of intelligence, lacking responsiveness and are costly, time-consuming, and prone to user biases, while accessing subject matter experts (SMEs) is difficult and inefficient.
Innovation Solution
Utilizing generative AI models to create interactive digital personas that can evolve based on user interactions, providing 24/7 accessibility and reducing bias, with AI-driven search functionalities for SME knowledge, enabling scalable and accurate responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If avatar or digital twin models are used to represent persons, then graphical representation is provided, but responsiveness and interactivity are limited
Solution Approach 1:
The patent creates digital copies (avatars) of subject matter experts that can interact with users. These avatar representations copy the knowledge and communication style of real experts, enabling users to interact with the copied intelligence rather than the original person, thus improving accessibility while maintaining expert knowledge quality
Solution Approach 2:
The system introduces an intermediary layer between users and expert knowledge. The avatar acts as a mediator that translates complex expert knowledge into user-friendly responses, and the feedback loop serves as an intermediary mechanism to continuously improve the avatar's responsiveness based on user interactions
2Measurement precision
If subject matter experts are accessed directly, then accurate knowledge is provided, but accessibility and efficiency are reduced
Solution Approach 1:
Instead of requiring direct access to subject matter experts, the system creates digital copies (avatars) that encapsulate their knowledge. Users can interact with these copies anytime, eliminating the bottleneck of expert availability while preserving the accuracy of expert knowledge through the feedback-driven learning mechanism
Solution Approach 2:
The avatar system enables self-service access to expert knowledge. Users can independently query the avatar without needing to schedule or coordinate with actual experts. The avatar serves itself by learning from user feedback and continuously improving its knowledge base, reducing the need for human expert intervention
3Adaptability or versatility
If traditional persona methods are used, then user representation is achieved, but time consumption and cost increase
Solution Approach 1:
The system creates digital copies of personas based on user feedback and interactions rather than requiring manual creation from scratch. The avatar learns and adapts its persona characteristics through interaction, automatically generating customized representations without extensive manual setup time
Solution Approach 2:
The system performs preliminary actions by pre-training avatars with general knowledge and characteristics before user interaction. This preliminary preparation reduces the time needed for customization during actual use, as the avatar already possesses foundational knowledge that can be quickly adapted to specific users through feedback
Data Source
AI summary
Methods and systems are provided for using personas in conjunction with an artificial intelligence (AI) model to provide answers to user prompts. In an embodiment, a method includes selecting a persona for use in responding to a user prompt, and using the AI model to determine a data source best able to provide an answer to the user prompt, search one or more data sources based on the user prompt and the selected persona, and generate an answer to the user prompt based on search results obtained from the one or more data sources.