In this talk, I'll touch on the myriad ways that machine learning is being used to dramatically rethink how computer systems are approached. I'll highlight research work in domains covering a variety of problems in ASIC chip design, computer architecture, distributed systems, database systems, compilers, content delivery systems, and more. I'll also highlight how building simple interfaces that allow "learned choices" to be integrated into the middle of existing hand coded computer software can dramatically ease the breadth and ease with which machine learning can be applied to a variety of different kinds of decisions, including many decisions at the core of computer systems. This talk presents work by a great number of Google Research colleagues and is meant to be an overview of the exciting advances in applying ML to computer systems problems.