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.