Your question is Transformers vs RNNs for Sequences. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do transformer-based architectures handle sequential data differently than traditional Recurrent Neural Networks (RNNs)?
Answer at a high level, then compare how each model processes order, long-range dependencies, and training efficiency. Keep the explanation focused on architecture and practical tradeoffs.