What exactly is an Artificial Neural Network or ANN? Explain in simple terms.

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For the last few years, researchers have been trying to make machines more "intelligent". Keeping this is mind, it is only natural that they would want to replicate the human brain which is the source of human intelligence and capabilities into a machine. This attempt to replicate the capabilities of the brain finds form in what is called an "Artificial Neural Network" (abbreviated to ANN). Simply put, ANN is an imitation of a BNN (Biological Neural Network).


Brain
Brain: Photo by Robina Weermeijer on Unsplash


What is Biological Neural Network or BNN?

In simple terms, BNN refers to the complex interconnected network of billions of neurons that make up any human's nervous system (including the brain). In fact, the human brain contains some 86 billion neurons, which communicate through electric impulses. ANN is humanity's attempt to mathematically model what goes around in the human brain. Presently, there are multiple ANN architectures and processes deployed that have evolved over decades of hard work and research. 

The journey to understanding ANN generally starts with the model of a single neuron, sometimes referred to as the perceptron. This further evolves to using multiple artificial neurons in multiple layers using multiple techniques to give out multiple outputs and choosing the most reasonable one. If this was not enough, multiple techniques have been created before and after this basic process as well, all designed to improve the accuracy of the final model.

This is as far as the introduction to ANN goes. Stay tuned for further blog posts.


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