How Facebook encodes your videos

What this post added

This post details the evolution of Facebook's video encoding system, moving from a rule-based prioritization to a benefit-cost model integrated with machine learning. The new model prioritizes advanced codecs (like VP9) for videos predicted to be highly watched, balancing compression efficiency, predicted watch time, and compute cost. It introduces the MVHQ metric for comparing compression efficiency and explains how ML models predict watch time based on various video and uploader attributes, addressing challenges like high variance and long-tail distribution of watch time.