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Google DeepMind 'learns' the London Underground map to find best route

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James Woodson
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New research combines neural networks with external memory

Google's DeepMind has beefed up machine learning capability by coupling a neural network with external memory, using it to find the shortest path between stations on the London underground.

Neural networks - a system modelled on how neurons are connected and work in the brain - are good at processing data but bad at taking on more algorithms to tackle more tasks because of a lack of memory.

The researchers from DeepMind, however, have taken steps to solve this problem by creating a differentiable neural computer DNC .

Results published in a paper in Nature show that a DNC can read and write from an external memory and outperforms DeepMind s neural Turing machine, a system with short-term memory.

The information is stored in a memory matrix, and is operated on by read and write functions.

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