>long term memory, short term memory Doesn't that mean the architecture isn't settled? The current mechanism of appending the output of the model back into the

>long term memory, short term memory Doesn't that mean the architecture isn't settled? The current mechanism of appending the output of the model back into the prompt feels like a bit of a hack. I'm only a layman here but it seems transformer models can only propagate information layer-wise, adding some ability to propagate information across time like RNNs do might be useful for achieving longer-term coherence.