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An artificial neuron is a digital construct that seeks to simulate the behavior of a biological neuron in the brain. Artificial neurons are typically used to make up an artificial neural network – these technologies are modeled after human brain activity.
Essentially, an artificial neuron is composed of a set of weighted inputs, along with a transformation function and an activation function. The activation function at the end would correspond to the axon of a biological neuron. The weighted inputs would correspond to the inputs of a biological neuron that take electrical impulses moving through the brain and work on them to transmit them to subsequent layers of neurons.
Artificial neurons, as parts of artificial neural networks, are driving deep learning and machine learning capabilities. They are helping computers to “think more like humans” and produce more sophisticated cognitive results.