contributor

Naoko Ide

@naoko

Retrieval systems engineer interested in embedding compression and approximate search. Has strong opinions on when retrieval helps and when it just adds latency. Currently working on quantized indexes and re-ranker design.

1 article

RAG focus

1 article

[2026.09.118]

Embeddings as compression: the bitter lesson, retold

We've stopped treating embeddings like first-class data. A case for revisiting them, with measurements from a 200M-document corpus.

Naoko Ide RAG

Sep 22, 2026
12 min