States that a Neural Network with at least one hidden layer containing a finite number of neurons can approximate any continuous function to any desired degree of accuracy.
Provides a mathematical justification for using neural networks, assuring researchers that a sufficiently large or deep network can model the complex, non-linear relationships often found in real-world data.
Guarantees that a network with the right structure exists, but does not provide a method for finding the network’s parameters (training it) or exactly how large the network must be for a given function.