https://en.wikipedia.org/wiki/Perceptrons_(book)

applied rigorous math (e.g. when computer science was new) to prove that a certain kind of single-layer neural network couldn't solve certain problems. (Can't learn XOR) It is like proving that it takes N log N comparisons to sort N items.

This dampened interest in neural networks for a long time but the "geometrical thinking in hyperdimensional space" is what the field is all about today.