A reservoir computer—a type of artificial neural network—can use information about a system’s past to predict the system’s future. Reservoir computers are far easier to train than their more general counterpart, recurrent neural networks. However, researchers have yet to develop a way to determine the optimal reservoir-computer construction for memorizing and forecasting the behavior a given system. Recently, Seyedkamyar Tavakoli and André Longtin of the University of Ottawa, Canada, took a step toward solving that problem by demonstrating a way to enhance the memory and prediction capabilities of a reservoir computer [1]. Their demonstration could, for example, allow researchers to make a chatbot or virtual assistant, such as ChatGPT, using a reservoir computer, a possibility that so far has been largely unexplored.
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