New Google TurboQuant algorithm improves vector search speed

Google says a new compression algorithm, called TurboQuant, can compress and search massive AI data sets with near-zero indexing time, potentially removing one of the biggest speed limits in modern search systems.

What it is. TurboQuant is a way to shrink and organize the data that powers AI and search without losing accuracy. It reduces memory use while keeping results precise and cuts the time to build searchable AI indexes to “virtually zero,” according to the research paper.

How it works. Modern search converts content into vectors (lists of numbers that represent meaning). Similar ideas sit close together in this numeric space, and search finds the closest matches.

However, these vectors are large and expensive to store and search. TurboQuant addresses this by using much smaller data that behaves almost exactly like the original, through:

• Smart compression. It rotates the data mathematically to compress it cleanly, like organizing messy items into…