Virtual Representative Conditioning for Accurate Multi-User Participation
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Solution Overview
Problem
Existing systems face challenges in efficiently representing individuals in multi-user experiences, particularly when they cannot personally attend, due to lack of relevant background knowledge, human resource constraints, privacy concerns, and latency issues with virtual representatives.
Innovation Solution
A virtual representative conditioning system that utilizes a conditioning engine to generate a conditioned model for a virtual representative by leveraging a baseline model and conditioning inputs, including knowledge base data and user directives, to ensure accurate representation in multi-user experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a virtual representative is used to represent an individual in multi-user experiences, then participation capability is improved, but representation accuracy deteriorates due to lack of relevant background knowledge
Solution Approach 1:
The system performs preliminary conditioning of the virtual representative by integrating background knowledge from knowledge bases and user directives before the virtual representative participates in multi-user experiences. This advance preparation ensures the virtual representative has necessary context and information to accurately represent the user's intentions and preferences.
Solution Approach 2:
The patent introduces a conditioning engine as an intermediary component that processes and integrates multiple sources of information (knowledge bases, user directives, baseline models) to enhance the virtual representative's representation accuracy. This mediator bridges the gap between the basic virtual representative and the user's specific context.
2Measurement precision
If a comprehensive baseline model is used for the virtual representative, then representation quality is improved, but computational effort and memory use increase
Solution Approach 1:
The system segments the virtual representative model into a baseline model and conditioned components. The baseline model contains general capabilities, while specific knowledge and directives are added only when needed through conditioning. This segmentation allows the system to maintain high representation quality without permanently loading all possible data, reducing computational effort and memory usage.
Solution Approach 2:
The virtual representative model is made dynamic through conditioning, allowing it to adapt its complexity and knowledge base size based on specific tasks and contexts. The model can be lightweight for simple tasks and expanded for complex scenarios, optimizing the balance between representation quality and computational resources.
3Loss of information
If conditioning data is integrated for the virtual representative, then data relevance is improved, but processing time increases
Solution Approach 1:
Relevant conditioning data is pre-processed and organized in knowledge bases before being needed by the virtual representative. This preliminary organization of information allows for faster retrieval and integration during actual interactions, reducing processing time while maintaining high data relevance.
4Adaptability or versatility
If a virtual representative is deployed for multi-user experiences, then user participation is improved, but latency in representation occurs
Solution Approach 1:
The virtual representative is pre-conditioned with essential user information, preferences, and context before deployment in multi-user experiences. This advance preparation reduces the need for real-time processing and information retrieval during interactions, thereby minimizing response latency while maintaining high user participation capability.
Data Source
AI summary
Systems and techniques are provided for conditioning virtual representatives. For example, a method can include obtaining, by a conditioning engine, a baseline model for a virtual representative; obtaining, by the conditioning engine, one or more conditioning inputs configured to condition an action in one or more multi-user experiences of the virtual representative; generating, based on the baseline model and the one or more conditioning inputs configured to condition an action in one or more multi-user experiences of the virtual representative, a conditioned model for the virtual representative; and outputting the conditioned model for the virtual representative.


