This is news to me. I had been steeped in a different lore. I have read the original article (or perhaps it was an excerpt?). I don't recall this reference.
I see from the wikipedia article you linked to, that they did know about the multiple layers. I thought it was suspicious that they had somehow missed it since it is so simple (at least to us now), and these guys are so very smart.
I wonder if they also knew (or realized, rather), that a single layer neuron with a non-monotonic function could have also "solved" XOR.
Again, hindsight. Backpropagation was first applied to ANNs on the verge of 1980s. So we are slowly moving from Misnky wrongly criticizing perceptrons to Minsky not inventing sound backpropagation/multilayer ANN algorithm, which is perhaps taking it a bit too far.
Just to be clear, Minsky didn't need backprop, just the multiple layers. (In order for a perceptron to act like an XOR gate, or to "solve the XOR problem" in some parlance.)
Minsky assumed a trained percepton with the weights already set to act like an AND or an OR gate. He wasn't dealing with the learning problem.
Fair point, although without knowing that this approach is practically viable to begin with it was getting into speculations territory. Not that Minsky didn't like to speculate..
Anyway, IMO people overestimate Minsky influence to single-handedly shut down an avenue of research. The reason _Perceptrons_ conclusions caught up is because they were sound and reasonable to his peers at the time.
I also seem to remember his video interview from a few years back where he elaborates on perceptrons and how much of his original conclusions are applicable to the state of art ANNs. Can't quite find it though.
There are two ways that Minsky could have (mathematically) looked past the linear separability issue:
1. If you add another layer to the perceptron, it can solve the XOR problem.
2. If you add a non-monotonic threshold function, it can solve the XOR problem.
So these are two rather simple solutions to the issue he brought up.