Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in ...

TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...

Google’s AI surprise puts Micron and Sandisk in focus.

Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression algorithm that’s going viral over ...

What Google's TurboQuant can and can't do for AI's spiraling cost ...

New capabilities deliver up to 5X faster filtered vector search, improved ranking quality, and lower infrastructure costs to unlock scalable, cost-efficient AI applications SAN FRANCISCO, July 30, ...

Vector quantisation and its associated learning algorithms form an essential framework within modern machine learning, providing interpretable and computationally efficient methods for data ...

A more efficient method for using memory in AI systems could increase overall memory demand, especially in the long term.

Learn why Google’s TurboQuant may mark a major shift in search, from indexing speed to AI-driven relevance and content discovery.