AI Prompt Refinement With Editable Response State Switching
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Solution Overview
Problem
Existing generative AI systems face inefficiencies in processing and saving prompts and responses, particularly in multi-user and multi-turn interactions, and lack effective mechanisms for managing AI-generated responses between read-only and editable states.
Innovation Solution
A system that iteratively refines prompts by appending subsequent prompts to a single instruction string for generative models, allowing efficient computation and storing responses in a first application as read-only, while enabling conversion to editable content in a collaboration application for further editing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If prompts are processed and saved individually in existing generative AI systems, then each prompt can be managed separately, but processing efficiency decreases and system complexity increases in multi-user and multi-turn interactions
Solution Approach 1:
The patent combines multiple individual prompts into a single consolidated prompt structure that captures the essence of multi-turn interactions. This merging approach processes multiple user inputs as one unified prompt, significantly improving processing efficiency while reducing system complexity in multi-user scenarios.
Solution Approach 2:
The consolidated prompt structure serves multiple functions simultaneously: it handles multi-turn interactions, manages multi-user inputs, maintains conversation context, and generates comprehensive responses. This multi-functionality eliminates the need for separate processing mechanisms for each prompt type.
2Reliability
If AI-generated responses are kept read-only for re-running prompts, then response integrity is maintained, but user ability to edit and collaborate on content is limited
Solution Approach 1:
The patent implements a dynamic response state system where AI-generated responses can transition between read-only and editable states. Users can selectively convert specific responses from read-only to editable based on their needs, allowing the system to adapt to different operational requirements while maintaining response integrity when needed.
Solution Approach 2:
The system changes the editability parameter of AI-generated responses, allowing transitions between read-only and editable states. This parameter change enables users to control whether responses can be modified, balancing response integrity with user editing capability based on specific needs.
3Productivity
If AI-generated responses are made editable for user collaboration, then user interaction and productivity improve, but response integrity and ability to re-run original prompts is compromised
Solution Approach 1:
The system dynamically adjusts response editability based on user actions and context. Responses start in read-only state to maintain integrity, but can be converted to editable state when users need to collaborate or modify content. This dynamic approach allows the system to provide both response integrity and user interaction benefits at different times.
Solution Approach 2:
The editability parameter of responses is changed based on user needs. When users require collaboration or content modification, the parameter shifts from read-only to editable, enabling productivity improvements without permanently compromising response integrity for all scenarios.
4Productivity
If multiple subsequent prompts are processed separately by the generative model, then each prompt can be handled individually, but computation time and processing resources increase
Solution Approach 1:
The patent merges multiple subsequent prompts into a single consolidated prompt structure that preserves the sequential logic and context of individual prompts. This consolidation allows the generative model to process multiple user inputs in one computation pass, significantly reducing processing time and improving computation efficiency while maintaining the ability to handle each prompt's specific requirements.
Data Source
AI summary
A data processing system implements iteratively receiving a first prompt requesting a generative model to generate digital content, and subsequent prompt(s) requesting the model to further process the digital content; constructing a system prompt including the first prompt, the subsequent prompt(s), and instructions to the model to iteratively update the first prompt based on the subsequent prompt(s), and subsequently to generate the digital content based on a single updated first prompt; providing the system prompt to the model and receive the digital content; and providing the digital content to a client device. The system implements storing a prompt and a response generated by the model in a first application; causing the client device to present the prompt and the response in a read-only view; receiving a user selection to convert the response to editable; and converting the response to editable and inserting the editable response in a collaboration application.