COMPRESSING AI VECTORS TO 2–4 BITS PER NUMBER WITHOUT LOSING ACCURACY

Summary from the TLDR AI newsletter

TurboQuant compresses each coordinate in large tables of high-dimensional vectors to 2-4 bits with provably near-optimal distortion, no memory overhead for scale factors, and no training or calibration. It is between four and six orders of magnitude faster than the alternatives at 4-bit indexing, with higher recall as well. This page explains how TurboQuant works.