I've been experimenting with an approach to vector indexing where the HNSW graph nodes store 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 rotatio
