Maybe I'm misinterpreting, but if you've ever seen a cat freak out about a cucumber (an entire video genre, apparently), ostensibly real intelligences make simi

Maybe I'm misinterpreting, but if you've ever seen a cat freak out about a cucumber (an entire video genre, apparently), ostensibly real intelligences make similar errors. Beyond rote memorization, it looks like it could be explained by saying the model appears to have a found a concept of consonance and dissonance that is bounded within the field of its inputs, and a networked grammar for interacting with the up/down/left/right inputs. Some people might find that technically trivial, but as a layman I am impressed. The "magic" part is that the response of the network appears to be so complex relative to its inputs, but given the input is so limited from a controller, it's easy to attribute more meaning to it when it is working with a finitely bounded simulated model. Generally I'd wonder, if the behaviour appears more complex than the stimuli, do we tend to attribute intent to it?