Sequence-to-Sequence Learning

Sequence-to-Sequence (Seq2Seq) learning is a method in artificial intelligence where a model is trained to convert one sequence of information into another. For example, it can take a sentence in one language and translate it into another, or convert spoken words into written text. The system processes the input sequence step-by-step, understands context, and then generates a corresponding output sequence. This approach is widely used in translation, speech recognition, and chatbots, enabling machines to handle complex, variable-length data by learning how parts of one sequence relate to parts of another.