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This doesn't sound like it would be unrealistic. I think this can be partially solved by two systems: one that paints and one that finds the best painting to match a current event (in the form of a topic). The latter system could be trained on a set of paintings and corresponding topics or meanings, and then uses this training to match newly generated paintings to topics/meanings.


There are definitely people working on this sort of thing. I recently read this conf paper on generating modified flags based on a topics (e.g. Cyprus + peace):

https://cdv.dei.uc.pt/ever-changing-flags/

Maybe not as technically exciting, as a super generic NN, but I think projects scoped like this are useful to think about.


Correct. This is actually quite doable with word embedding or image classification of a topic, semantic analysis, and then providing those as input to a network like the one I used for 1SecondPainting. I love the future.




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