# Are RNNs inherently flawed? Supervised Learning assumes IID data but sequential data is not IID

From what I understand, Supervised Learning operates under the assumption that the data is I.I.D. It seems to me that the training procedure for RNNs is flawed. We receive observations in a sequential format -- this condradicts the assumption of IID -- that is, observations are temporally dependent on one another. Therefore, it seems to me that RNNs are flawed learning procedures. Am I correct in my reasoning?