Evolving Dataflow to process massive datasets for machine learning

Google created MapReduce more than 20 years ago to solve the scaling problems in data processing that the then young company was running into. The AI era that we are in now demands efficient, large-scale data processing for everything from training frontier models like Gemini by Google DeepMind to powering fully autonomous vehicles like Waymo. Many aspects of machine learning, including data ingestion, transformation, and feature extraction, rely heavily on processing massive datasets.