Cross-relevant refinement of generative artificial intelligence models for creative content across multiple platforms

A computer-implemented method comprising:

• receiving a file comprising source content;
• determining a plurality of sharing contexts associated with destination platforms or interfaces for the file;
• generating, using one or more generative models and based on the plurality of sharing contexts, a plurality of representations derived from the source content for presentation in accordance with the plurality of sharing contexts, the plurality of representations differing from one another based on the respective sharing contexts;
• causing the plurality of representations to be presented within the destination platforms or interfaces;
• receiving engagement data corresponding to interactions with the plurality of representations;
• and
• refining the one or more generative models based on the engagement data, including using engagement data associated with presentation of a first representation in a first sharing context to refine generation of a second representation for presentation in a second sharing context different from the first sharing context.

A system comprising:

• at least one processor;
• and
• a non-transitory computer readable medium storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising:
• determining a plurality of sharing contexts associated with destination platforms or interfaces for a file comprising source content;
• generating, using one or more generative models and based on the plurality of sharing contexts, a plurality of representations derived from the source content for presentation in accordance with the plurality of sharing contexts, the plurality of representations differing from one another based on the respective sharing contexts;
• causing the plurality of representations to be presented within the destination platforms or interfaces;
• receiving engagement data corresponding to interactions with the plurality of representations;
• and
• refining the one or more generative models based on the engagement data, including using engagement data associated with presentation of a first representation in a first sharing context to refine generation of a second representation for presentation in a second sharing context different from the first sharing context.

A non-transitory computer readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:

• receiving a file comprising source content;
• determining a plurality of sharing contexts associated with destination platforms or interfaces for the file;
• generating, using one or more generative models and based on the plurality of sharing contexts, a plurality of representations derived from the source content for presentation in accordance with the plurality of sharing contexts, the plurality of representations differing from one another based on the respective sharing contexts;
• causing the plurality of representations to be presented within the destination platforms or interfaces;
• receiving engagement data corresponding to interactions with the plurality of representations, the engagement data including a downstream interaction with the file following presentation of at least one of the plurality of representations;
• and
• refining the one or more generative models based on the engagement data, including using engagement data associated with presentation of a first representation in a first sharing context to refine generation of a second representation for presentation in a second sharing context different from the first sharing context.