5 Principles for Applied Machine Learning Research

Over the past three years, I’ve spent >50% of my time thinking about what the applied research teams I’ve been part of should be building, and how. This post is about some of the challenges I’ve faced helping to organize applied machine learning research in a hyper-growth setting.

These observations are subjective and overfit to my personal experience; if you’re leading teams at Google Brain, this blogpost is probably not for you. If you’re in a startup which is pre product market fit and seems to be spending a lot of money on GPUs, listen up…