In the context of artificial intelligence (AI), particularly in machine learning and neural networks, weights are parameters that determine the strength of the connections between neurons or nodes in a network. They play a central role in learning and prediction.Weights are essentially what the model "learns" during training. They control the influence of input features on the output, and the process of training is about adjusting these weights to improve the accuracy of the model's predictions. In summary, weights in AI, particularly in neural networks, are the parameters that are learned during training and define how data moves and transforms through the network to make predictions.