The answer
No. Attention mechanisms existed before the Transformer. The paper’s contribution was a particular architecture that made attention central while dispensing with recurrent and convolutional sequence layers.
Why was the “Attention Is All You Need” paper important for AI?
Did the paper invent the attention mechanism itself?
More FAQs in Why was the “Attention Is All You Need” paper important for AI?
No. The original paper presented an encoder-decoder architecture for sequence transduction, including machine translation. Decoder-only language models are later uses of related transformer components.
No. Causal masks preserve which positions a prediction may use, even when many positions are computed together. Parallel computation must still respect the learning objective.
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