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Analysts suggest the distinction may stem from how TurboQuant impacts different layers of the AI stack. The technique is said to improve inference efficiency by reducing memory usage and data movement ...

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 ...

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 ...

RWIF turns semantic memory into compact, portable files that can stay on disk instead of forcing a heavyweight vector database to stay resident in RAM or VRAM. This repository exposes that disk-native ...

Decentralized exchange Hyperliquid’s permissionless platform, which lets anyone create perpetual futures tied to any asset, is more popular than ever. Since its debut on Oct. 13, the so-called HIP-3 ...

PCWorld highlights that soaring RAM prices driven by data center demand are reshaping the PC building market and threatening smaller memory manufacturers. New Z-Angle stacked DDR memory technology ...

Recap: The last memory industry boom of comparable scale occurred between 2017 and 2019, when cloud data center expansions pushed RAM prices to record highs and widened the gap between memory and ...

UNITED KINGDOM (WKRC) - A new study suggests that cannabis use among middle-aged and older adults is associated with larger brain volumes and better cognitive performance, though researchers caution ...

Feb 5 (Reuters) - PC makers HP, ‌Dell, Acer and Asus are ‌considering sourcing memory chips from Chinese chipmakers for the first time amid a global supply crunch that is ‍threatening product launches ...

I used to spend a lot of time troubleshooting large Docker images, waiting for builds to complete, and worrying about wasted storage. It felt like no matter how carefully I structured my Dockerfiles, ...

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...