Did Minsky and Papert know that multi-layer perceptrons could solve XOR? In their famous book entitled Perceptrons: An Introduction to Computational Geometry, Minsky and Papert show that a perceptron can't solve the XOR problem. This contributed to the first AI winter, resulting in funding cuts for neural networks. However, now we know that a multilayer perceptron can solve the XOR problem easily.

Backprop wasn't known at the time, but did they know about manually building multilayer perceptrons? Did Minsky &amp; Papert know that multilayer perceptrons could solve XOR at the time they wrote the book, albeit not knowing how to train it?
There does not appear to be a historical consensus on this.
The Wikipedia page on the Perceptrons book (which does not come down on either side) gives an argument that the ability of MLPs to compute any Boolean function was widely known at the time (at the very least to McCulloch and Pitts).
However, this page gives an account by someone present at the MIT AI lab in 1974, claiming that this was not common knowledge there, alluding to documentation in &quot;Artificial Intelligence Progress Report: Research at the Laboratory in Vision, Language, and other problems of Intelligence&quot; (p31-32) which is claimed to support this.