Seq2Seq is essentially an abstract deion of a class of problems, rather than a specific model architecture, just as the "classification problem" describes the mapping from inputs to category labels, ...

“The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for serving/training LLMs.