Hybrid computing using a neural network with dynamic external memory

Here we introduce a machine learning model called to a differentiable neural computer (DNC), which consists of a nerual network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but , like a nerual network, it can learn to do so from data.

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