Recently, you may have been hearing a lot about “Big Data”, this refers to our growing ability to find patterns and process very  large amounts of data with or without structure. There are many reasons contributing to this but a recent set of algorithmic advances known as “Deep Learning” have led to a surge in accuracy in voice recognition and vision. This is relevant for scientists because Deep Learning is a particularly effective type of  ‘unsupervised learning’ which does not require you to specify a bias up front to speed up learning. Thus it only learns a pattern from the data if there is a statistical basis for it.

This recent article in Nature is causing some waves and explains the algorithms quite well, the discussion in Andrew Ng’s Google+ post is also good to add a bit more context about the wider progress in Artificial Intelligence research.