How We're Building the Next Generation of Search with Semantic Search Technology

What this post added

This post introduces the core infrastructure for Exa's next-generation search engine, detailing the crawling process, HTML parsing, S3 storage, and the critical step of preprocessing documents into neural embeddings using specialized transformer models. It highlights the "Bitter Lesson" philosophy by emphasizing the use of significant compute resources, including a 144 H200 GPU "Exacluster," for training these embedding models. The post also outlines two distinct product offerings, Exa Search (low-latency general search) and Exa Websets (high-compute, complex query search), with a future goal of unification. The architecture diagram illustrates the flow from crawling to serving queries via a custom vector database.