Overfitting

A failure mode in machine learning where a model learns the specific quirks and noise of its training data too closely, so it performs well on that data but poorly on new, unseen examples. Overfitting is one reason why an AI model that scores well in testing can still fail in real-world use. (See also: Training data, Machine learning)