Unfortunately AI doesn’t work like that. Any way to explain it would be an oversimplification but I can try.
The training data (songs) are used to create the weights. This is a bunch of numbers that are on their own meaningless - they don’t map to specific songs, but to attributes such as “tone” “rhythm”… And like that but many (millions of) abstract attributes that don’t make sense as people, but make sense to computers.
So if the thing makes a song that is very “rhythmic” but also “tonal”, there’s no specific training song that contributed to that - all did, and it’s a mess to decypher how much each contributed to each attribute. Except the resulting song doesn’t use two parameters, uses many millions, so it’s essentially impossible to know.
Unfortunately AI doesn’t work like that. Any way to explain it would be an oversimplification but I can try.
The training data (songs) are used to create the weights. This is a bunch of numbers that are on their own meaningless - they don’t map to specific songs, but to attributes such as “tone” “rhythm”… And like that but many (millions of) abstract attributes that don’t make sense as people, but make sense to computers.
So if the thing makes a song that is very “rhythmic” but also “tonal”, there’s no specific training song that contributed to that - all did, and it’s a mess to decypher how much each contributed to each attribute. Except the resulting song doesn’t use two parameters, uses many millions, so it’s essentially impossible to know.