Google's TurboQuant offers LLMs up to 6x compression
SMRTR summary
Google Research unveiled TurboQuant, a compression algorithm that shrinks large language models' memory requirements by up to 6x while delivering 8x faster performance without sacrificing accuracy. The technology compresses the key-value cache that stores important computational information by converting traditional vector coordinates into polar coordinates, reducing complex data into just radius and direction components.
SMRTR provides this summary for quick context. The original article belongs to Hacker News.
Read the original article