Deep learning is a specialized set of machine learning that uses representation learning and artificial neutral network systems. It is based analog inputs and outputs composed of multiple processing layers that are used to learn representations of data. Because it is based in analog, it uses images of pixel data; audio files and messages; text data documents; and so on—as opposed to quantity inputs in tabular format. We already see deep learning at work in features such as speech recognition, genomics, chatbots, and translations. It works by feeding the system with large data sets using algorithm that allow the machine to automatically identify the needed representation. Deep learning continues to be a major AI breakthrough in analyzing complex audio, video, speech, pixel files and then coming to relevant solutions from this data.