Which of the following best describes the architecture of sequence transduction models in business applications?

Sequence transduction models in business use an encoder‑decoder architecture that first turns the input sequence into a hidden representation and then decodes it into a new sequence, often with an attention mechanism to focus on relevant parts. The encoder compresses the entire input into a context vector that summarizes its meaning. The decoder then generates the output step by step, conditioning each new token on both the context and the previously generated tokens. For example, a customer‑service chatbot reads a user query (encoder), then produces a helpful reply (decoder) by attending to the important words in the query. This setup lets companies automate tasks like translating support tickets or summarizing financial reports.