Deep learning is often considered a subset of machine learning. Machine learning itself being  a subset of the broader endeavour of artificial intelligence. Specifically, when we are talking about deep learning we are referring to multilayered artificial neural networks. A lot of the ideas behind general machine learning also apply to deep learning. However deep learning, perhaps, shows possibilities towards the development of stronger artificial intelligence. Artificial neural networks are after all based their more sophisticated biological counterpart.

It is important to remember that learning itself, either biological or machine, is component of intelligence. Intelligence is actually much more than simply learning. Qualities such as creativity, insight, knowledge, moving and interacting in the physical world as well as having a healthy range of emotions are all part of human intelligence. 

Some major advances have occurred in the non learning component of artificial intelligence that are directly relevant to artificial neural networks.  Some examples are;

• Robotics - Allowing real time decision making and interacting in three dimensional space
• Knowledge representation - Systems that allow reflection on past experiences.
• Generative models that evaluate an environment and generate a response