View source for Shopify Inc. (20240160902). SIMILARITY-BASED GENERATIVE AI OUTPUT FILTERING simplified abstract

== Abstract Explanation ==
The patent describes methods and systems for creating content using a generative artificial intelligence (AI) model. It includes a similarity-assessment layer that evaluates the similarity of the generated content to existing items in a repository. If the content is too similar to existing items, the system adjusts the input or the AI model and re-generates the content.

* Methods and systems for generating content using a generative AI model.
* A similarity-assessment layer checks the output against existing items.
* If the output is too similar, adjustments are made to the input or AI model.
* The process is repeated to produce new, less similar content.

== Potential Applications ==
* Content creation for blogs, articles, and social media.
* Generating unique marketing materials.
* Producing original creative works like stories, poems, and songs.
* Enhancing automated customer service responses.

== Problems Solved ==
* Prevents plagiarism by ensuring generated content is unique.
* Reduces redundancy in content creation.
* Helps maintain originality and creativity in AI-generated outputs.
* Ensures compliance with intellectual property laws.

== Benefits ==
* Ensures originality of generated content.
* Reduces risk of legal issues related to plagiarism.
* Enhances creativity and diversity in content creation.
* Provides a reliable way to produce unique and engaging materials.

== Potential Commercial Applications of Similarity-Based Generative AI Output Filtering ==
* Automated content creation platforms for marketing and social media.
* AI-driven content generation tools for writers and creatives.
* Customizable AI solutions for businesses needing unique content.
* Educational tools for creating original instructional materials.

== Possible Prior Art ==
* Techniques for plagiarism detection in content.
* Existing AI models for content generation without similarity checks.



=== How Does the System Handle Ambiguities in Content Similarity? ===
The system uses a threshold value to determine excessive similarity. If the similarity measure is ambiguous, adjustments are made to either the input or the AI model to ensure the generated content is sufficiently unique.

=== What Are the Specific Parameters Used for Similarity Assessment? ===
The similarity-assessment layer uses specific metrics and thresholds to evaluate content similarity. These parameters can be adjusted based on the desired level of uniqueness and the nature of the content being generated.