Sample from a large weighted distribution in O(1) per draw (the alias method). Where do you need it?
Negative sampling in word2vec and recommendation pulls millions of weighted samples; running each at O(log n) becomes a bottleneck. The alias method turns each draw into O(1) after an O(n) setup. Here it is.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Negative sampling in word2vec and recommendation pulls millions of weighted samples; running each at O(log n) becomes a bottleneck. The alias method turns each draw into O(1) after an O(n) setup. Here it is.
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.
