So I’ll start by saying that I don’t know that much about machine learning so I don’t know how plausible this idea is; that’s why I’m asking.

Essentially, start by downloading the entirety of some hentai site, with artist names and tags. Then feed it into a neural network of some description. Set it up so that you can feed in an artist name and tags and it’ll try to make a manga/doujin in the style of that artist with those tags. (Presumably it would have better results if you stick to tags that actually appear in that artist’s work?)

One question is, would it be best to stick to material in one language so it won’t make speech bubbles in a sort of English-Japanese-Chinese mishmash? (I realize it will have no way of actually knowing the meanings of the words or how they sound out loud but given enough data it should at least be able to correlate written words and phrases to pictures/situations, right?) Similarly, would it be best to stick to material in black and white (or in color)? There are at least 200,000 available mangas/doujins in Japanese in black and white; would that be anywhere close to enough data?

Would it be able to get more out of the training data if the dialogue was all transcribed in text and the pages were panel-by-panel tagged with who’s where, doing what? I realize this would take many man-hours.

How much processing power would I expect this to take? I’m assuming my 2.2 gigahertz, 4 gigabyte RAM laptop would be entirely inadequate.

And finally, if it didn’t end up producing anything coherent, would the results at least be funny?