MICROSOFT TECHNOLOGY LICENSING, LLC (20240354503). GENERATIVE THOUGHT STARTERS simplified abstract
Contents
GENERATIVE THOUGHT STARTERS
Organization Name
MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor(s)
Keren Kochava Baruch of West Orange NJ (US)
Kevin Michael Arcara of Brooklyn NY (US)
Adam Jason Kaplan of Brooklyn NY (US)
Emilie Marie, Andréa De Longueau Saint Michel of Paris (FR)
Faizaan Shafiq Charania of Mountain View CA (US)
GENERATIVE THOUGHT STARTERS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240354503 titled 'GENERATIVE THOUGHT STARTERS
The described technology involves using input signals specific to a user, which are then processed by artificial intelligence models to generate AI-derived signals.
- Input signals are personalized to each user within a user network.
- AI models analyze the input signals and produce AI-derived signals related to the inputs.
- Prompt templates are applied to the AI-derived signals to create prompts for the user.
- Generative AI models then generate thought starters based on the prompts.
- The thought starters consist of machine-generated digital content for distribution within the user network.
Potential Applications: - Personalized content creation for users within a network. - Automated generation of ideas and content based on user input. - Enhancing user engagement and interaction within a digital platform.
Problems Solved: - Streamlining content creation processes for personalized user experiences. - Increasing user engagement through tailored content suggestions. - Automating the generation of creative ideas for users.
Benefits: - Improved user satisfaction through personalized content recommendations. - Time-saving for content creators by automating idea generation processes. - Enhanced user interaction and engagement within a digital environment.
Commercial Applications: Title: Personalized Content Generation Technology This technology can be utilized in social media platforms, content creation tools, and digital marketing strategies to enhance user experiences and increase user engagement. Companies can leverage this innovation to create targeted content for their audiences, leading to higher conversion rates and improved brand loyalty.
Questions about Personalized Content Generation Technology: 1. How does this technology impact user engagement within a digital platform? This technology enhances user engagement by providing personalized content suggestions based on individual preferences, leading to increased interaction and satisfaction.
2. What are the potential challenges in implementing this technology in existing digital platforms? Integrating this technology may require adjustments to existing systems and workflows to accommodate the personalized content generation process effectively.
Original Abstract Submitted
embodiments of the described technologies determine input signals, where the input signals are specific to a user of the user network. the input signals are input to a set of artificial intelligence (ai) models. in response to the input signals, the first set of ai models output a first set of ai-derived signals relating to the input signals. at least one prompt template is applied to the first set of ai-derived signals to create at least one prompt. the at least one prompt is input to at least one generative ai model. in response to the at least one prompt, the at least one generative ai model outputs at least one thought starter machine-generated by the at least one generative ai model. the at least one thought starter includes digital content configured to be distributed via the user network.
