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Artificial Neural Networks, often abbreviated as ANNs, are computing systems inspired by the biological neural networks that constitute animal brains. They are designed to simulate the way in which neurons process information and learn from experience. ANNs consist of interconnected layers of nodes or artificial neurons, each of which takes in a set of inputs, applies a weight to them, and passes the result through an activation function to produce an output. The weights are adjusted during training, allowing the network to learn from data and improve its performance over time. ANNs have found applications in various fields such as image and speech recognition, natural language processing, and predictive analytics. They are a key component of artificial intelligence and contribute significantly to the advancement of technology in this area.