  We are in the dawn of deep learning explosion for smartphones. To bridge the
gap between research and practice, we present the first empirical study on
16,500 the most popular Android apps, demystifying how smartphone apps exploit
deep learning in the wild. To this end, we build a new static tool that
dissects apps and analyzes their deep learning functions. Our study answers
threefold questions: what are the early adopter apps of deep learning, what do
they use deep learning for, and how do their deep learning models look like.
Our study has strong implications for app developers, smartphone vendors, and
deep learning R\&D. On one hand, our findings paint a promising picture of deep
learning for smartphones, showing the prosperity of mobile deep learning
frameworks as well as the prosperity of apps building their cores atop deep
learning. On the other hand, our findings urge optimizations on deep learning
models deployed on smartphones, the protection of these models, and validation
of research ideas on these models.
