Dynamic Targeting Prompts for On-Demand Digital Content
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Solution Overview
Problem
Campaign management platforms face inefficiencies in storing and serving digital content due to the vast number of targeting parameter combinations, leading to redundant content generation and storage, which consumes significant processing power and storage resources.
Innovation Solution
A system generates and stores prompts for AI models using a combination of base object descriptions and targeting parameters, allowing for efficient retrieval and reprocessing of prompts instead of redundant content generation, thereby reducing storage needs and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system stores and serves digital content for multiple targeting parameter combinations, then the content can be delivered to diverse audiences, but the storage requirements and processing power consumption increase significantly
Solution Approach 1:
The system stores prompts (text representations) instead of actual digital content (images, videos, audio). Prompts are much smaller in size and can be easily copied and stored efficiently. When content is needed, the stored prompt is used to regenerate the actual content, avoiding the need to store multiple versions of the same content for different targeting parameters.
Solution Approach 2:
The system changes the representation parameter from storing actual content to storing prompts. This parameter change allows the system to maintain adaptability for multiple targeting parameter combinations while dramatically reducing storage requirements. The prompts can be efficiently stored and retrieved based on targeting parameters, and content is regenerated only when needed.
2Adaptability or versatility
If the system generates digital content for each targeting parameter combination, then the content can be optimized for different audiences, but redundant content generation consumes excessive processing power
Solution Approach 1:
The system performs preliminary action by storing prompts in advance for different targeting parameter combinations. When content is needed, the pre-stored prompt is retrieved and used to regenerate content, avoiding the need to perform the full content generation process from scratch each time. This preliminary storage of prompts significantly reduces processing power consumption for subsequent content generation requests.
Solution Approach 2:
The system uses prompt copies instead of regenerating entire content pieces. By storing and reusing prompt representations, the system minimizes the processing power required for content generation. Only the prompt retrieval and regeneration process is needed, rather than performing complete content generation for each targeting parameter combination.
3Speed
If the system stores digital content for future use, then content can be retrieved quickly, but storage resources are consumed and content may become outdated
Solution Approach 1:
The system stores prompt copies instead of actual content. Prompts are much smaller and consume minimal storage resources. When content is needed, the stored prompt is quickly retrieved and used to regenerate the actual content, achieving fast retrieval speed without consuming significant storage resources for the content itself.
Solution Approach 2:
The system changes the storage parameter from storing content to storing prompts. This allows for quick retrieval of prompts while minimizing storage resource consumption. The prompts can be efficiently stored and retrieved based on targeting parameters, and content is regenerated only when needed, avoiding the issue of storing potentially outdated content.
4Adaptability or versatility
If the system creates unique content for each targeting parameter combination, then the content can be highly customized, but the complexity of content management increases
Solution Approach 1:
The system uses prompt copies that can be easily managed and retrieved. Prompts are simple text representations that can be stored, searched, and retrieved efficiently using standard indexing and search mechanisms. This simplifies content management complexity compared to managing actual content files, while still enabling highly customized content generation through prompt-based regeneration.
Solution Approach 2:
The system introduces prompts as an intermediary between the content generation system and the targeting parameters. Prompts serve as a manageable intermediate representation that links targeting parameters to content generation. This intermediary layer simplifies content management by providing a straightforward way to store, retrieve, and manage content specifications without dealing with the complexity of actual content files.
Data Source
AI summary
Methods, systems, and apparatus, including computer-readable storage media for generating model-generated digital content from prompts built using a combination of a base object description and targeting parameters for an intended audience. The digital content, once generated, can be served to a target audience indicated by the targeting parameters. A system implementing the methods described herein can generate content for various different audiences, indicated by different combinations of targeting parameters available on a campaign management platform serving the content. When the content is no longer being served the system can cause the digital content to be deleted or otherwise discarded. Instead of storing the content, the system can save the prompt and re-process the prompt through the model to re-generate the content. The system can further index prompts for later querying, so that the system can avoid generating new prompts over using stored prompts for content generation.