Independent analysis of economics, technology, business, and public policy. Original essays informed by academic research, historical evidence, and data-driven reasoning.
Information Systems
Precision is easy to report; recall requires counting every relevant document that exists, which nobody has done since the web outgrew ten blue links. The AI search industry hasn't solved that problem — it has stopped mentioning it.
Vector search misses exact strings; keyword search misses meaning. The reason hybrid retrieval works isn't that it's smarter — it's that it refuses to trust either retriever's confidence, and hands the decision to a score-blind referee.
The trick behind billion-scale AI retrieval isn't reading everything faster. It's learning what to ignore—and accepting a system that misses one match in twenty by design.
Semantic search didn't just make search smarter. It converted language into geometry, gaining a genuinely new ability while losing the razor-sharp precision of the old index — which is why the best systems now run both.