Large-scale applications, such as generative AI, recommendation systems, big data, and HPC systems, require large-capacity ...

I’m already loving this device, and I haven’t even touched one. Arduino announced it has collaborated with M5Stack to develop the new compact and powerful Nesso N1 IoT development kit. This system ...

Micron is expected to report 148% revenue growth for the February quarter as average selling prices surge 32% quarter over quarter. The memory provider's stock has soared thanks to a shortage brought ...

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

Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...

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 rush to boost production of memory chips to meet fast accelerating demand from artificial intelligence will add to the semiconductor sector’s climate footprint and risks lifting costs of managing ...

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 ...

Alzheimer’s has long been considered irreversible, but new research challenges that assumption. Scientists discovered that severe drops in the brain’s energy supply help drive the disease—and ...

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 ...

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 ...