In simple terms, "Attention is All You Need" is a research paper written by Ashish Vaswani et al. It presents an architecture called Transformer that uses self-attention mechanisms to process input sequences without any recurrence or convolutions. The attention mechanism allows the model to focus on different parts of the sequence depending on what is relevant, rather than just processing sequentially. By only using this type of self-attention, the authors demonstrate that they achieve state-of-the-art results on several natural language processing tasks, making it a very influential work in modern AI.
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