What is transformer architecture in AI?

What is transformer architecture in AI?

Transformer architecture is a deep learning model designed for natural language processing tasks, introduced in the paper 'Attention is All You Need'.

How does the attention mechanism work in transformers?

The attention mechanism allows the model to weigh the importance of different words in a sentence, enabling it to focus on relevant parts when making predictions.

What are the advantages of using transformers over RNNs?

Transformers can process data in parallel, handle long-range dependencies better, and are generally more efficient than RNNs.

Can you explain the role of positional encoding in transformers?

Positional encoding helps the model understand the order of words in a sequence, as transformers do not have a built-in sense of order.