[D] Can someone describe how the SSM in Mamba is much different than the concepts in a GRU / LSTM Cell?

They state in the paper:

We highlight the most important connection: the classical gating mechanism of RNNs is an instance of our selection mechanism for SSMs.

Is it mainly the discretization step and different set of parameters in A,B, and C that are different?

Otherwise it feels like the same mental model to me. Encode information into a hidden space, use a gating or "selection" mechanism to figure out what to remember and forget, then unroll it over time to …

concepts gru highlight instance lstm machinelearning mamba paper parameters set state