AI Model Training

AI model training turns examples, labels, or other training signals into model parameters that can generalize to new inputs. The process typically includes data preparation, model selection, optimization, validation, and evaluation against held-out data. Depending on the use case, teams may train a model from scratch, fine-tune an existing foundation model, or continuously retrain models as new data and performance signals become available.