Machine Learning System Design Interview, issue 47, Jun 4, 2026
The EWC Rigidity Trap
Senior ML Engineer interview at Google DeepMind, and the interviewer asks:
“You deploy Elastic Weight Consolidation (EWC) to fix catastrophic forgetting during continual fine-tuning. The model successfully retains its historical accuracy, but its adaptation to the new domain completely stalls. Why?”
Don’t say: “The model is underfitting the new data. We just need to increase the learning rate or run it for a few more epochs.”
The hidden failure mode where retaining old accuracy quietly fires your network like clay in a kiln, leaving no room to sculpt anything new.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.