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In my experience these models are very bad at describing electronic music beyond extremely clear features like drum and bass vs techno.

The best model is/was the Pandora's Music Genome Project - but likely due to the fact that it is heavily supplemented with human input.



Pandora was largely the first LLM/trained AI. They just used music "genes" (words) and tokenized on that and their relationship. The difference was that the success model it used was based on a variable/semi-arbitrary input (personal tastes) with weighting vs an objective model (dictionaries/documents; or, for things like game playing AI, a goal to reach).


> In my experience these models are very bad at [...]

Given the progress across many AI applications in the past year I certainly wouldn't bet on this continuing to be true.




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