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To solve this drawback, a brand new sort of RNN has been developed; LSTM (long-term memory). Because of this, the RNN retains the state up to date or âremembersâ what was realized over time. Memory standing has its advantages, but it additionally has its drawbacks. In recurrent neural networks, the activation impact continues to be distributed in both directions, e.g.