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. The algorithms introduced by Google ...

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 ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

The shift in sentiment appears linked to Google's TurboQuant algorithm, which the company said can reduce the memory required to run large language models by at least a factor of six, potentially ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

Google's TurboQuant shrinks AI memory use by up to 6x. The new technique could enhance AI speed by 8x with no accuracy loss. Cheaper devices may run advanced AI tools without high-end hardware. Google ...

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

Google has unveiled a new memory-optimization algorithm for AI inferencing that researchers claim could reduce the amount of "working memory" an AI model requires by at least 6x. As TechCrunch reports ...

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...