Attention is all you need

This paper introduces the Transformer, a novel neural network architecture based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. It demonstrates that this model can be trained much faster and achieves state-of-the-art results in machine translation tasks. The core innovation is the self-attention mechanism, which allows the model to weigh the importance of different parts of the input sequence when processing each element, leading to better understanding and representation of the relationships within the data.