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 idea is to weigh the importance of different parts of the input sequence when processing it, allowing the model to focus on the most relevant information. This architecture has since become a foundational element in many large language models and generative AI systems.