On second thought, about this paper:

"Parsing Natural Scenes and Natural  Language with Recursive Neural
Networks" Socher, Lin, Ng, Manning (2011)


They have pre-processed the image scenes so that each image contains less
than 100 features.  That is really "small data" and a logic engine would
have no problem constructing a parse tree of the image using a bunch of
first-order rules.  I guess the research code's speed would be comparable
to that of a logic engine's, if not slower...  but that is regarding
*recognition* task.  What is special about their method is that it can
learn from data efficiently.  The learning can also be done by a logic
engine, but that would be much slower...



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AGI
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