If Machine Learning is cutting-edge, then Deep Learning is the bleeding edge. It’s the kind of AI that you would send to Jeopardy! It combines big data and analytics with unsupervised algorithms. The applications usually center around gigantic unlabeled data sets that need structuring into inter-connected clusters, inspired by nothing less than neural networks in our brains – therefore fittingly called artificial neural networks.
Deep Learning is the basis for many modern speech and image recognition approaches and benefits from a much higher accuracy over time than non-learning approaches offered in the past.
It is hoped that in the future Deep Learning AIs can autonomously answer customer enquiries and fulfills orders over chats or emails. Or they could assist marketing in suggesting new products and specifications based on their enormous data pool. Or maybe they can one day be Omni-present assistants at the workplace that entirely blur the line between robots and humans.
AIs live and improve through the scale of data that is thrown at them, which means that we see better AIs over time but also that their development will center around those organizations that can tap into the largest sets of data.