Video Summary

The paper proposes a new method for training language models. The method is based on the idea of self-supervised learning, where the model is trained to predict its own output. This is done by masking some of the tokens in the input and then having the model predict the masked tokens. The authors show that their method results in better performance than previous methods on a variety of language tasks.