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by sriku
2154 days ago
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The reality is likely neither here nor there - i.e. computing may have more to offer to the creative endeavor than creators would like to admit, but still leave an obvious gap which technologists might be loathe to admit. It may be instructive to look at David Cope's [1] work (what he calls "recombinant music" [2]). Cope's been writing algorithms to compose in the styles of the masters (Mozart/Chopin/et al) for about 3 decades now, well before the recent surge in "AI". His techniques are much less sexy for the "deep learning" enthusiasts, and yet he managed to outrage an audience of connoisseurs who assembled to listen to a "lost Chopin piece" only to be told, after they shared their applause, that it was composed by a computer taught to mimic Chopin's style (the composition was performed by a musician). The response, in my opinion, also points to music as a social constructed experience and not purely attributable to the sound signal itself. i.e. if I give you a romantic background story for a lost composition of a master, you may be inclined to experience the piece in a more favorable light than if I told you it was generated by an algorithm (or the converse). You're absolutely right that the musical output of the current crop of "AI" projects (especially the ones using deep learning / neural networks) are crappy to even a modestly trained listener .. or even a lay untrained listener for that matter. However, more involved modeling (such as Cope's) has produced some very compelling results decades ago, so it would be a mistake to assume that the current crop won't get close enough [3]. The fact that DL systems don't need to be instructed in the way Cope has had to encode his musical understanding is also something to be considered in the evaluation as well as in scoping their capabilities going forward. [1]: https://en.wikipedia.org/wiki/David_Cope
[2]: https://www.recombinantinc.com
[3]: https://deepmind.com/blog/article/wavenet-generative-model-r... (see "Making Music" section and examples there) |
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However, we have to make a clear distinction between creative and recreative methods. David Cope's work is impressive, but it focusses on the recreation of existing musical styles. This is interesting from a musicologist perspective, but not very interesting artistically.
I would certainly say that deep learning generates lots of interesting “material“ (like many other methods of algorithmic composition), but we still need a human being to curate, edit and assemble the material into a meaningful piece of art.
Finally, I think the current AI debate can be very fruitful for the arts. In a way, it raises similar questions as the concept of the “readymade“ and the pop art movement did in the 20th century.
Btw, I'm currently working on an opera which uses AI generated lyrics :-)