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

A server comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable storage media to store instructions executable by the one or more processors to perform operations comprising:
• segmenting a music-based output produced by a generative artificial intelligence, into multiple segments by:
• segmenting the music-based output into a plurality of stems;
• identifying one or more melodies in individual stems of the plurality of stems;
• and
• identifying one or more melodies in combinations of two or more stems from the plurality of stems;
• 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;
• 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.

A non-transitory 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, into multiple segments, by:
• identifying, using multi-pitch melody extraction, one or more musical patterns in the music-based output;
• and
• determining one or more data abstractions, wherein individual data abstractions of the one or more data abstractions are abstractions of individual musical patterns of the one or more musical patterns;
• generating, by an encoder executed, 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;
• 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 a 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.