What 2018 holds for AI and deep learning

We have taken a look at some of the challenges to overcome and predictions for its implementation from experts in the field who envision it becoming more practical and useful, automating some jobs and augmenting many others, combining machine learning and big data for fresh actionable insights. A deep learning system is, in short, a multi-layered neural network that learns representations of the world and stores them as a nested hierarchy of concepts many layers deep. For example, when processing thousands of images of human faces, it recognises objects based on a hierarchy of simpler building blocks: straight lines and curved lines at the basic level; then eyes, mouths, and noses; entire faces; and finally, specific facial features. Besides image recognition, deep learning offers the potential to approach complex challenges such as speech comprehension, human-machine conversation, language translation, and vehicle navigation, amongst others. How can we expect this technology to be implemented in the coming year?