Deep learning is used broadly at the forefront of research, achieving state-of-the-art results across a variety of domains. However, that doesn't mean it's a fit for all tasksespecially when the constraints of production are considered. Stephen Merity investigates what tasks deep learning excels at, what tasks trigger a failure mode, and where current research is looking to remedy the situation.