Their insight is that not only are there images that are "high-quality", but also images that are positive. Positive images get more clicks, over just a decent image. I wonder if that information is encoded in the RNN in some way.
(This is where I'd normally rant about RNNs and other ML techniques hiding this information from their creators by locking it up inside the black box, but I'll save that for another day.)
Their insight is that not only are there images that are "high-quality", but also images that are positive. Positive images get more clicks, over just a decent image. I wonder if that information is encoded in the RNN in some way.
(This is where I'd normally rant about RNNs and other ML techniques hiding this information from their creators by locking it up inside the black box, but I'll save that for another day.)