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Deep Learning

transformer-architecture

A neural network architecture designed for sequence-to-sequence tasks.

Expanded definition

Introduced in the paper 'Attention is All You Need', the transformer architecture uses self-attention mechanisms to weigh the influence of different words in a sentence on each other. This approach allows it to process sequences in parallel, in contrast to RNNs which process data sequentially. Misconceptions often arise regarding its requirement for vast amounts of data and compute power, which can be mitigated with proper techniques like transfer learning.

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transformer-architecture FAQ

What is transformer-architecture?

A neural network architecture designed for sequence-to-sequence tasks.

How is transformer-architecture used in AI systems?

Introduced in the paper 'Attention is All You Need', the transformer architecture uses self-attention mechanisms to weigh the influence of different words in a sentence on each other. This approach allows it to process sequences in parallel, in contrast to RNNs which process data sequentially. Misconceptions often arise regarding its requirement for vast amounts of data and compute power, which c...

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