Apple ML research tackles faster MIPS retrieval for more efficient RAG
Apple ML Research · rss · 2026-11-05
Apple ML Research published work on accelerating maximum inner product search (MIPS), the core of recommendation systems, search, and retrieval-augmented generation. Given a query vector, MIPS must find the best match among millions of candidate key vectors, then attach the associated data point (e.g., the best document for RAG).
- As key counts grow to millions and vector dimensions reach thousands, exhaustive search becomes computationally prohibitive
- The research focuses on making retrieval faster and more efficient to improve both quality and cost of RAG pipelines
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