Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. Shares of major memory and storage ...
Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...
The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...
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