Output-based attribution for musical content generated by an artificial intelligence (AI)

A non-transitory computer-readable memory device to store instructions executable by one or more processors to perform operations comprising:

• segmenting a music-based output produced by a generative artificial intelligence, wherein segmenting the music-based output produced by the generative artificial intelligence into multiple segments comprises segmenting the music-based output into:
• multiple time segments having different lengths of time;
• and
• multiple frequency segments using different frequency bands;
• generating, by an encoder, multiple output embeddings, wherein individual output embeddings of the multiple output embeddings are derived from individual segments of the multiple segments;
• determining a distance measurement between individual output embeddings of the multiple output embeddings and individual training segment embeddings of multiple training segment embeddings to create a plurality of distance measurements, wherein the multiple training segment embeddings are created, to train the generative artificial intelligence, by:
• segmenting music-based training data to create multiple training segments comprising multiple time training segments and multiple frequency training segments;
• and
• encoding, by the encoder, the multiple training segments to create the multiple training segment embeddings;
• correlating the plurality of distance measurements to a plurality of content creators that created multiple content items used to train the generative artificial intelligence;
• determining one or more creator attributions based at least in part on correlating the plurality of distance measurements to the plurality of content creators;
• determining a creator attribution vector that includes the one or more creator attributions;
• and
• initiating providing compensation to one or more content creators of the plurality of content creators based on the creator attribution vector.