## Neural Networks

Neural Networks are a way for AI technologies to store and process information. This storage is modeled after the working of the human brain. In a neural network, there are layers of so-called ‘neurons’. In the first layer, the input given by a user is first broken up into smaller pieces of information. Each of these smaller pieces of information is then stored in a different neuron. A layer, consisting of multiple neurons, thus represents the full information the network has at that stage. Each neuron in a layer then sends its information to one or more neurons in the next layer of the network. Additionally, the information also gets altered when it is sent forward. It could become more important, less important, or could even be discarded. What happens with the information in the connection between two neurons is determined by a so-called parameter. During machine learning, the parameters that dictate how information is changed when sent forward through the neural network are determined based on the patterns the computer finds in the training data. Eventually, the neurons in the final layer of the network produce an output that is presented back to the user.

You can watch the animation below to see how a neural network fits within a Generative AI application.