What if your HNSW index stored 3-bit embeddings instead of float32? [R]

I've been experimenting with an approach to vector indexing where the HNSW graph nodes quantized embeddings (~388 bytes each at dim=1024) instead of float32 vectors (~4,096 bytes). The key insight: if you quantize embeddings using Lloyd-Max scalar quantization after a random orthogonal rotation (the PolarQuant approach from Zandieh, ICLR 2026), you can precompute a centroid-centroid inner product table (8x8 = 64 floats for 3-bit). During graph traversal, distance computation becomes 1024 table lookups instead of 1024 float multiplies + accumulate. No decompression needed during search.