AI parameters are the adjustable elements in a model that are learned from training data. These include weights in neural networks and settings in machine learning algorithms. Parameters influence the behavior of AI models and determine how they make predictions or decisions.

Parameters are internal variables that machine learning models adjust during their training process to improve their ability to make accurate predictions. They act as the model's "knobs" that are fine-tuned based on the provided data.

Parameters in AI refer to the variables that are used to define and manipulate the input and output of machine learning models. These variables can include weights, biases, and other factors that are used to adjust the behavior of the model.