Artificial Neural Networks (ANNs) are computer systems inspired by the way the human brain works. They consist of interconnected layers of nodes, or "neurons," that process information. Each neuron receives input, applies a mathematical function, and passes the output to the next layer. This structure allows ANNs to learn from data, making them useful for tasks like image recognition and language translation. Training an ANN involves adjusting the connections between neurons based on the data it processes. This process, called backpropagation, helps the network improve its accuracy over time. As a result, ANNs can recognize patterns and make predictions, making them powerful tools in various fields, including artificial intelligence and machine learning.