Which two resources typically grow during large-model training compared with serving a small fixed model? Select 2 answers.

1. A mandatory public address for every training worker
2. An exclusive requirement for a separate physical GPU per output class
3. Compute for backward propagation
4. Memory for gradients and optimizer state
5. A requirement to keep every training example in GPU memory simultaneously