WITHIN-CONTEXT SEMANTIC RELEVANCE INFERENCE OF MACHINE LEARNING MODEL GENERATED OUTPUT
WITHIN-CONTEXT SEMANTIC RELEVANCE INFERENCE OF MACHINE LEARNING MODEL GENERATED OUTPUT
Methods and systems provide content searching and retrieval using generative artificial intelligence (AI) Models. The system is configured to receive a user search for content, media or item listings. The system receives a natural language-based input associated with a client device of a user. The system generates a search criterion for the received natural language-based input. The system, via the generative AI-bases search and retrieval system, generates a relevancy-ranked output listing of content items. The relevancy-ranked output listing content items responsive to the generated search criterion content items having an associated content identifier and a content description. The system causes portions of the relevancy-ranked output listing to be rendered at the client device of the user.