The computer architecture is facing an important and exciting challenge. The slowing of Moore's law (at the same time demand continues to grow) has led to new approaches to thinking about future system design including accelerators and software-defined hardware. In this talk we will discuss how machine learning has the potential to amplify these opportunities. We will discuss some specific case studies and end with some key insights specific to applying machine learning to improve computer architecture.