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Introduction to
artificial neural networks (ANNs)


The world today

Maybe you have heard here and there about some technological wonders based on artificial neural networks -- about intelligent robots, smart weapons or even stock trading advisory systems? What's going on? Are we really living at the turning point of history where machines are taking over and mankind will be doomed? To be honest, it is not completely impossible, but artificial neural networks in their current state of evolution are hardly the right target for accusations of that kind. The most complex neural networks of our time are not working in the dark corners of high-tech labs. No, they are in our heads.

Start thinking!

How much do we know about the inner mechanisms of our brain? How often do we think about how exactly we think about the things we think about? The fact that this sentence looks a bit weird should be considered alarming as it shows the lack of discussions on the topic. Think about it!


Human brain is an extremely complex structure. Its workings can be discussed on a huge number of different levels -- starting from the low end of atoms and molecules and going up to the social interactions of global scale. All these levels are remarkably interesting, but as our current concern is artificial neural networks, we will go to the cellular level.

The main component of our biological neural net is a cell called neuron. Many different types of neurons are present in brain, but their general structure is mostly the same:

On the drawing you can see the main parts of a neural cell:

The main principle of neuron's work is already visible from the description of its structure -- neuron collects signals, processes them and feeds into other neurons. In reality, however, everything is very complex. First of all, signals are far from simplicity. They are passed via electrochemical processes based on different ions (mainly sodium (Na), potassium (K) and chloride (Cl)). Even worse, the information is coded not into the amplitude of signals, but instead into frequency of these electrochemical pulsations (although that doesn't automatically mean we could just forget about the amplitude). Secondly, although the scales are microscopic, the numbers are macroscopic. Each neuron has up to 10,000 input connections via dendrites, all passing signals into the soma. And the number of such neurons in a brain is estimated to be somewhere between 10 and 100 billion (thats 10,000,000,000 and 100,000,000,000)! Finally, all this unimaginably huge system is in constant change --  new connections are being formed, some cells stop functioning due to aging, etc.


Artificial neuron

Artificial neural network

Training a network

What can be done with ANNs?


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