How does ANN search trade accuracy for speed, and where's the knob?

What exactly is an embedding, and why does AI engineering need them?

Embeddings are numeric vectors that represent the meaning of data — text, images, audio — so that similar things end up close together in vector space.

Quantizing embeddings: how much can you compress before quality drops?

Product and scalar quantization can shrink vector memory footprint by 4–32x, but recall degrades gradually then falls off a cliff past a certain compression ratio.

Why can't you just use Postgres for vector search?

You often can, with pgvector — but it stops scaling gracefully well before purpose-built vector databases do, and knowing where that line is matters.