A community woodshop co-op with 200 product blurbs wants a catalog helper. Which customization path should the team reject as usually the wrong application choice?
Select an answer to reveal the explanation.
Short Explanation
Think of 200 product blurbs. Do not pre-train a foundation model from scratch. Prompt, retrieve, or drop in a few examples. Random weights are the expensive wrong turn.
Full Explanation
Full pre-training is the most expensive customization and is rarely justified for a practitioner application with 200 blurbs. Prompting, retrieval, and in-context examples stay in budget and skill. Starting from random weights does not.