Researchers led by Takaki Hatsui at the RIKEN SPring-8 Center (RSC) in Japan and collaborators have developed a new approach ...

You will be redirected to our submission process. In the field of neuroscience, imaging techniques are central for unraveling the structure and function of the nervous system at molecular, cellular, ...

Jason Fernando is a professional investor and writer who enjoys tackling and communicating complex business and financial problems. Khadija Khartit is a strategy, investment, and funding expert, and ...

Imaging is a critical technique in biology—from identifying cancerous cells in biopsies to observing how immune cells like macrophages hunt down and destroy pathogens. Traditionally, distinguishing ...

Google’s TurboQuant is making waves in the AI hardware sector by addressing long-standing challenges in memory usage and processing efficiency. Developed with components like the Quantized ...

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 ...

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 ...

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 ...

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.” ...

Google published a research blog post on Tuesday about a new compression algorithm for AI models. Within hours, memory stocks were falling. Micron dropped 3 per cent, Western Digital lost 4.7 per cent ...

Add Decrypt as your preferred source to see more of our stories on Google. Google said its TurboQuant algorithm can cut a major AI memory bottleneck by at least sixfold with no accuracy loss during ...