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 architecture can be trained more quickly and achieve 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 for making predictions. This has since become a foundational architecture in various NLP tasks, including speech recognition and summarization, which are key components of Otter Assistant.