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How Neural Networks Think

September 11, 2017
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Researchers will present a new general-purpose technique for making sense of neural networks trained to perform natural-language-processing tasks, in which computers attempt to interpret freeform texts written in ordinary, or natural language (as opposed

Artificial-intelligence research has been transformed by machine-learning systems called neural networks, which learn how to perform tasks by analyzing huge volumes of training data.

During training, a neural net continually readjusts thousands of internal parameters until it can reliably perform some task, such as identifying objects in digital images or translating text from one language to another. But on their own, the final values of those parameters say very little about how the neural net does what it does.

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