Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in which the probabilities of tokens occurring in a specific order is ...

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Kubernetes wasn't built for GPUs, but new tools like Kueue and MIG are finally helping companies stop wasting money on ...

A paper from Google could make local LLMs even easier to run.

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 ...

SanDisk (SNDK) stock fell to $623 as the company commits $1B to acquire a ~4% stake in Nanya Technology, with quarterly free cash flow of $980M raising investor concerns about timing amid trade policy ...

Major memory chipmakers took a significant hit on Thursday after Google researchers introduced a groundbreaking compression algorithm that threatens to reduce artificial intelligence demand for memory ...

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 ...

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 ...

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 ...

The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...