Google llc (20240311652). Markup Language for Generative Model Prompting simplified abstract
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 20240311652 titled 'Markup Language for Generative Model Prompting
The abstract describes systems and methods for prompt generation for generative models using a specialized markup language. This language helps create prompts that guide the generative output to reflect the user's intent accurately.
- Specialized markup language used for prompt generation in generative models
- Markup language transform augments user input data to create structured prompts
- Integrated development environment interface informs users of prompt parts and provides editing options
- Prompts facilitate generative output that aligns with user intent
- Systems and methods leverage markup language for effective prompt generation
Potential Applications: - Natural language processing systems - Chatbots and virtual assistants - Content generation tools - Automated writing assistants
Problems Solved: - Improving the accuracy of generative models - Enhancing user interaction with AI systems - Streamlining content creation processes
Benefits: - Increased efficiency in generating content - Enhanced user experience with AI systems - Improved alignment between user input and generative output
Commercial Applications: Title: Enhanced Content Generation with Specialized Markup Language This technology can be used in various commercial applications such as: - Content marketing platforms - E-commerce product description generation - Social media content creation tools
Prior Art: Researchers can explore prior art related to specialized markup languages in natural language processing and content generation technologies.
Frequently Updated Research: Stay updated on advancements in natural language processing, AI-driven content generation, and user interaction with generative models.
Questions about the technology: 1. How does the specialized markup language improve the accuracy of generative models? 2. What are the potential limitations of using markup language for prompt generation in AI 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.
