Abstract
Generative artificial intelligence models are capable of generating content in different modalities such as text, image, audio, video, and combinations. While user-driven content generation, where a user enters a prompt about a topic of interest and receives AI-generated content in response, is popular, this requires users to identify topics and seek content. This disclosure describes techniques for autonomously generating high-engagement content in various modalities. A continuous loop of input (identifying topics of interest), output (content generation based on the topics of interest), and metrics (engagement with the generated content) is used to generate new content that provides users engaging online experiences about topics that users are interested in. The techniques ensure that new content is automatically generated and made available on content platforms.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Dropsho, Steven and Bakshi, Dhruv, "AI-driven Autonomous Content Generation for Trending Topics", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/8930