Live Breaking News & Updates on Constant Depth Threshold Circuits

In 1969, Marvin Minsky and Seymour Papert published Perceptrons: An Introduction to Computational Geometry. In it, they showed that a single-layer perceptron cannot compute the XOR function. The main argument relies on linear separability: Perceptrons are linear classifiers, which essentially means drawing a line to separate input that would result in 1 versus 0. You can do it in the OR and AND case, but not XOR.
Of course, we’re way past that now, neural networks with one hidden layer can solve that problem. ....

Michael Hahn , Marvin Minsky , Seymour Papert , Cassian Andor , Neural Networks , Data Structures , Computational Complexity , Theoretical Limitations , Neural Sequence Models , Constant Depth Threshold Circuits , Chomsky Hierarchy , Recognize Formal Languages , Theoretical Limitation , Universal Turing , Universal Transformer ,