I get that, but what I’m saying is that calling deep learning “just fancy comparison engine” frames the concept in an unnecessarily pessimistic and sneery way. It’s more illuminating to look at the considerable mileage that “just pattern matching” yields, not only for the practical engineering applications, but for the cognitive scientist and theoretician.

Furthermore, what constitutes being “actually creative”? Consider DeepMind’s AlphaGo Zero model:

Mok Jin-seok, who directs the South Korean national Go team, said the Go world has already been imitating the playing styles of previous versions of AlphaGo and creating new ideas from them, and he is hopeful that new ideas will come out from AlphaGo Zero. Mok also added that general trends in the Go world are now being influenced by AlphaGo’s playing style.

Professional Go players and champions concede that the model developed novel styles and strategies that now influence how humans approach the game. If that can’t be considered a true spark of creativity, what can?