Google says its new algorithm reduces AI memory overhead by 6x which could be good news for the RAMpocalypse but bad news for Micron and co

Stock prices for the big three memory makers have already slid. When you purchase through links on our site, we may earn an ...

Google's TurboQuant compression tech cuts LLM memory use by 6x with no accuracy loss

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
GovInfoSecurity

Why Vector Databases Put Enterprise AI Data at Risk

Cyborg CEO Nicolas Dupont describes how vector databases concentrate sensitive enterprise data in a structurally unencrypted layer, and conventional encryption ...

Google develops TurboQuant compression technology for AI models

Google LLC has unveiled a technology called TurboQuant that can speed up artificial intelligence models and lower their ...

Google targets AI inference bottlenecks with TurboQuant

The technique aims to ease GPU memory constraints that limit how enterprises scale AI inference and long-context applications ...

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
WinBuzzer

Google’s TurboQuant Algorithm Slashes LLM Memory Use by 6x

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...
IEEE

BK-Index: A Multi-attribute Index algorithm for Network Traffic

Abstract: Archiving raw network traffic is fundamental for network forensics and troubleshooting. In order to efficiently retrieve specific entries from large-scale archives, multi-attribute queries ...