Your question is L1 vs L2 Regularization. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are comparing regularized linear models for a supervised learning task and want to explain what changes when you use an L1 penalty versus an L2 penalty.
Explain the difference between L1 and L2 regularization from both a geometric and a Bayesian perspective.