Google DeepMind ‘learns’ the London Underground map to find best route

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…


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