ALBERT is an advanced language model developed to provide the same capabilities as BERT but with significantly reduced memory requirements and faster training times. It introduces novel parameter-reduction techniques such as splitting the embedding matrix and using repeating layers, which help in scaling the models efficiently. ALBERT also modifies the next sentence prediction with sentence ordering prediction, improving its effectiveness on downstream tasks.
