Inference

Inference in AI refers to the process of using a trained model to make predictions or decisions based on new data. It involves applying the learned patterns from the training phase to unseen inputs to generate outputs. Inference can be performed in real-time or batch modes, depending on the application requirements. Common use cases include image recognition, natural language processing, and recommendation systems, where the model interprets input data and provides meaningful results. Overall, inference is a critical step in deploying AI models in practical applications, enabling them to function in dynamic environments.