  In Hopfield neural networks with up to 10^8 nodes we store two patterns
through Hebb couplings. Then we start with a third random pattern which is
supposed to evolve into one of the two stored patterns, simulating the
cognitive process of associative memory leading to one of two possible
opinions. With probability p each neuron independently, instead of following
the Hopfield rule, takes over the corresponding value of another network, thus
simulating how different people can convince each other. A consensus is
achieved for high p.
