In part 1 of this article we discussed the industry trend of companies wanting to brand themselves as "AI first" and often positioning themselves as deep learning. We highlighted some of the problems building and deploying a deep learning solution presents and suggest that often other machine learning approaches could provide a solution in a simpler and more cost effective way. In this second part we want to outline our own experience building an AI application and reflect on why we chose not to utilise deep learning as the core technology used. At Aiqudo we have built a personal digital assistant for smart phones. Our goal is to understand what users are saying, figure out their intent and execute the correct action for them on their devices..

It is still unclear what metacognition is. Two main theories about metacognition are reviewed, each of which claims to provide a better explanation of the phenomenon, while discrediting the other theory as inappropriate. My claim is that in order to do justice to the complex phenomenon of metacognition, we must distinguish two levels of this capacity. It can be shown that each of these theories has been trying to explain only one of the two levels and that, consequently, the conflict between them can be dissolved. Finally, I characterize each level and explain some of their interactions.