👉 The RecFluid, or Recurrent Fluid, is a type of recurrent neural network (RNN) architecture specifically designed to handle sequential data, such as time series or natural language. Unlike traditional RNNs that process inputs sequentially but forget information over long sequences, RecFluid incorporates a mechanism to maintain and update a "fuel" or context vector that captures the essence of past inputs. This context vector is updated at each time step by integrating new information with the previous context, allowing the model to retain relevant historical data while adapting to current inputs. This design makes RecFluid particularly effective for tasks like speech recognition, language modeling, and time series prediction, where understanding the temporal dynamics of data is crucial.
