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Artificial neural networks mimics the functioning of neurons in the human brain. They can learn from their original training and future runs, providing them with a wealth of new information about the world. In the ImageNet competition in 2012, a neural network outperformed humans in image recognition. Neural networks make decisions based on inputs from previous tiers by setting rules and making decisions — that is, the decision of each node on what to transmit there. In training systems that recognise patterns in patterns in data to find patterns in biassed data sets, such as neural networks, have their own biases.