View source for Unknown Organization (20240232937). SYSTEM AND METHODS UTILIZING GENERATIVE AI FOR OPTIMIZING TV ADS, ONLINE VIDEOS, AUGMENTED REALITY & VIRTUAL REALITY MARKETING, AND OTHER AUDIOVISUAL CONTENT simplified abstract

=SYSTEM AND METHODS UTILIZING GENERATIVE AI FOR OPTIMIZING TV ADS, ONLINE VIDEOS, AUGMENTED REALITY & VIRTUAL REALITY MARKETING, AND OTHER AUDIOVISUAL CONTENT=


==Organization Name==

[[:Category:Unknown Organization|Unknown Organization]]


[[Category:Unknown Organization]]

==Inventor(s)==

[[:Category:Timothy Christopher D'auria of Sharon MA (US)|Timothy Christopher D'auria of Sharon MA (US)]][[Category:Timothy Christopher D'auria of Sharon MA (US)]]

==SYSTEM AND METHODS UTILIZING GENERATIVE AI FOR OPTIMIZING TV ADS, ONLINE VIDEOS, AUGMENTED REALITY & VIRTUAL REALITY MARKETING, AND OTHER AUDIOVISUAL CONTENT - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240232937 titled 'SYSTEM AND METHODS UTILIZING GENERATIVE AI FOR OPTIMIZING TV ADS, ONLINE VIDEOS, AUGMENTED REALITY & VIRTUAL REALITY MARKETING, AND OTHER AUDIOVISUAL CONTENT

==Simplified Explanation==
This invention introduces a system and methods for optimizing audiovisual content using generative models. It analyzes various audiovisual data to create an intermediary output that captures key elements like color schemes, audio patterns, and narrative structures.

* Utilizes generative models to optimize audiovisual content
* Processes varied data to capture key elements like color schemes and audio patterns
* Incorporates attribute recognition and effectiveness measurement modules for comprehensive pattern recognition
* Adaptable for different performance metrics such as advertising effectiveness and ROI
* Reduces time and costs in audiovisual content development

==Key Features and Innovation==
- System and methods for optimizing audiovisual content using generative models
- Analyzes varied audiovisual data to capture key elements like color schemes, audio patterns, and narrative structures
- Incorporates attribute recognition and effectiveness measurement modules for comprehensive pattern recognition
- Utilizes AI models such as LLMS and GPTs, text mining, uncertainty measurement, and SHAP values
- Adaptable for different performance metrics such as advertising effectiveness and ROI

==Potential Applications==
- Television commercials
- Online video production
- Social media advertising
- AR/VR marketing

==Problems Solved==
- Streamlines the audiovisual content development process
- Enhances pattern recognition for optimized content creation
- Reduces time and costs in content development

==Benefits==
- Improved efficiency in audiovisual content development
- Enhanced pattern recognition for optimized content creation
- Adaptable for different performance metrics

==Commercial Applications==
Optimizing audiovisual content for various mediums such as television, online video production, social media advertising, and AR/VR marketing can lead to increased advertising effectiveness and ROI.

==Questions about the Technology==
1. How does this technology improve pattern recognition in audiovisual content?
2. What are the key benefits of using generative models in optimizing audiovisual content?


==Original Abstract Submitted==

this invention presents a system and methods for optimizing audiovisual content, including tv commercials, online videos, and ar/vr marketing, using generative models. it processes varied audiovisual data, generating an intermediary output that captures key elements like color schemes, audio patterns, entity interactions, and narrative structures. the system's attribute recognition module, combined with an effectiveness measurement module, enables comprehensive pattern recognition, enhancing the creation of optimized content across mediums. it incorporates various ai models, such as llms and gpts, and employs text mining, uncertainty measurement, and shap values. the system is adaptable for different performance metrics, such as advertising effectiveness and roi. this approach streamlines the audiovisual content development process, reducing time and costs, and is applicable in television, online video production, social media advertising, and ar/vr marketing.



[[Category:G06Q30/0242]]
[[Category:G06N3/0475]]
[[Category:CPC_G06Q30/0244]]