Tech Xplore

Compression technique makes AI models leaner and faster while they're still learning

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
Hackaday

TurboQuant: Reducing LLM Memory Usage With Vector Quantization

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

Why Google’s TurboQuant Algorithm is Disrupting the AI Memory Chip Market

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...
Morning Overview on MSN

Google’s new AI compression could cut demand for NAND, pressuring Micron

A new compression technique from Google Research threatens to shrink the memory footprint of large AI models so dramatically ...
Digi Times

In-depth: Google TurboQuant cuts LLM memory 6x, resets AI inference cost curve

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 ...
24/7 Wall St

This AI Semi Equipment Maker Has Been Quietly Chewing Up the Competition

Lam Research (LRCX) delivered a 321% total return over three years by dominating AI chip production through etch and deposition tools for high-bandwidth memory and advanced logic, with advanced ...
Android

This Google AI Breakthrough Could End the Global RAM Crisis Sooner Than Expected

Google has unveiled TurboQuant, a new AI compression algorithm that can reduce the RAM requirements for large language models by 6x. By optimizing how AI stores data through a method called ...
Mashable

Google AI breakthrough shows why we don't need more data centers

We have seen the future of AI via Large Language Models. And it's smaller than you think. That much was clear in 2025, when we first saw China's DeepSeek — a slimmer, lighter LLM that required way ...
The Motley Fool

Why Shares of Sandisk Fell This Week

New Google technology reduces the memory requirements of AI models. Investors were worried about slowing memory demand, but it's too early to make that call. That sparked fears among Sandisk investors ...
TechSpot

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

The big picture: Google has developed three AI compression algorithms – TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss – designed to significantly reduce the memory footprint of large ...
Forbes

Google’s TurboQuant Compression Could Increase Demand For AI Memory

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. On March 24, 2026 Amir Zandieh and Vahab Mirrokni from Google Research published an article ...
The Verge

Google’s TurboQuant algorithm aims to slash AI memory usage.

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...