18183429. Markup Language for Generative Model Prompting simplified abstract (Google LLC)
Contents
Markup Language for Generative Model Prompting
Organization Name
Inventor(s)
Chinmay Kulkarni of Atlanta GA (US)
Alexander John Fiannaca of Seattle WA (US)
Michael Andrew Terry of Cambridge MA (US)
Markup Language for Generative Model Prompting - A simplified explanation of the abstract
This abstract first appeared for US patent application 18183429 titled 'Markup Language for Generative Model Prompting
Simplified Explanation: The patent application describes systems and methods for prompt generation using a specialized markup language to enhance user input data for generative models.
Key Features and Innovation:
- Utilization of a specialized markup language for prompt generation.
- Transformation of user input data to create prompts that aid in generating generative outputs reflecting user intent.
- Integration of an integrated development environment interface to inform users of prompt parts and provide editing options.
Potential Applications: The technology can be applied in various fields such as natural language processing, artificial intelligence, and content generation.
Problems Solved: The technology addresses the challenge of generating prompts that accurately reflect user intent and facilitate the creation of generative outputs.
Benefits:
- Improved accuracy in generating generative outputs.
- Enhanced user experience through structured prompts.
- Increased efficiency in content generation processes.
Commercial Applications: The technology can be utilized in chatbots, content creation tools, and automated writing platforms to streamline content generation processes and improve user interaction.
Prior Art: For prior art related to this technology, researchers can explore existing patents and publications in the fields of natural language processing and generative models.
Frequently Updated Research: Researchers can stay updated on advancements in natural language processing, generative models, and content generation technologies to enhance the capabilities of the described prompt generation systems.
Questions about Prompt Generation Technology: 1. How does the specialized markup language enhance prompt generation for generative models? 2. What are the potential implications of integrating an integrated development environment interface in prompt generation systems?
Original Abstract Submitted
Systems and methods for prompt generation for generative models can include utilizing a specialized markup language. A markup language transform can be utilized to augment user input data to generate a prompt that includes structure and/or wording that facilitates the generation of a generative output that reflects a user's intent. The systems and methods can leverage the specialized markup language and/or an integrated development environment interface to inform a user of the prompt parts and provide editing options.
