Google AI compression technology saves data center energy
Key summary
TurboQuant Google unveiled the TurboQuant algorithm, google published a research paper this week describing TurboQuant.
The algorithm can make LLMs' memory usage six times smaller, turboQuant reduces memory used by large language models by a reported factor.
The method reduces key-value pair size and uses random rotation of data vectors, turboQuant reduces the size of key-value pairs and applies random rotation to data vectors.
LLMs smaller memory footprints can decrease energy and RAM usage for LLMs, reducing LLM memory usage can lower energy and RAM requirements for running models.
TurboQuant the compression could enable running powerful LLMs on smartphones, the article compares TurboQuant's potential impact to enabling powerful models to run on smartphones.
