Scientists have long been
dreaming about building a computer that would work like a brain. This is
because a brain is far more energy-saving than a computer, it can learn by
itself, and it doesn’t need any programming. Researchers from Bielefeld
University’s Faculty of Physics are experimenting with memristors – electronic
microcomponents that imitate natural nerves. They proved that they could do
this a year ago. They constructed a memristor that is capable of learning.
Memristors are made of fine nanolayers and can be used to connect electric
circuits. For several years now, the memristor has been considered to be the
electronic equivalent of the synapse. Synapses are the bridges across which
nerve cells (neurons) contact each other. Their connections increase in
strength the more often they are used. Usually, one nerve cell is connected to
other nerve cells across thousands of synapses.
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. 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.
Researchers take the classic psychological experiment with Pavlov’s dog as an
example. The experiment shows how you can link the natural reaction to a
stimulus that elicits a reflex response with what is initially a neutral
stimulus – this is how learning takes place.
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