Perplexity Describes Its Vector Embedding Approach

Perplexity's official account stated that the company embeds queries and documents into one vector space and searches by nearest vectors. This approach leads to two distinct workloads according to the post: bulk batch embedding focused on throughput for indexing and scoring, along with per-query online embedding aimed at low latency for live search. The message comes from the verified company account on the platform.