AI Reports · MIT FutureTech · 2026-10-17 · Research paper
Compute Trends Across Three Eras of Machine Learning Compute and data advances drive ML progress. Training compute doubled every 20 months before 2010, accelerated to every 6 months with Deep Learning
Training compute for machine learning doubled roughly every 20 months before 2010, then accelerated to about every 6 months after deep learning emerged in the early 2010s. Based on these trends, the authors divide the history of ML compute into three eras: Pre Deep Learning, Deep Learning, and Large-Scale. The work highlights how fast the compute needed to train advanced ML systems is growing.