Like synapses, memristors learn from earlier impulses. In their case, these are electrical impulses that (as yet) do not come from nerve cells but from the electric circuits to which they are connected. The amount of current a memristor allows to pass depends on how strong the current was that flowed through it in the past and how long it was exposed to it.
Andy Thomas explains that because of their similarity to synapses, memristors are particularly suitable for building an artificial brain -- a new generation of computers. 'They allow us to construct extremely energy-efficient and robust processors that are able to learn by themselves.
'This is all possible because a memristor can store information more precisely than the bits on which previous computer processors have been based,' says Thomas. Both a memristor and a bit work with electrical impulses. However, a bit does not allow any fine adjustment -- it can only work with 'on' and 'off'. In contrast, a memristor can raise or lower its resistance continuously. 'This is how memristors deliver a basis for the gradual learning and forgetting of an artificial brain,' explains Thomas.
Image : A nanocomponent that is capable of learning: The Bielefeld memristor built into a chip here is 600 times thinner than a human hair.