Deep neural networks are a key technology at the core of advanced audio and video applications.
As these applications begin to migrate from large servers executing in the cloud to mobile and embedded platforms, they place significant demands on the underlying hardware platform.
This talk will review the key properties of these models and how these properties are leveraged to deliver efficient inference on energy, compute, and space constrained platforms.
