What's the difference between masked language modeling (BERT) and causal language modeling (GPT)?
BERT and GPT diverge on one decision made before a single weight is trained: what does each token get to see? That choice ripples into attention, use case, and why one family now dominates. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
BERT and GPT diverge on one decision made before a single weight is trained: what does each token get to see? That choice ripples into attention, use case, and why one family now dominates. Here is the answer.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
