Tether successfully integrated Google’s TurboQuant into the inference engine of its local AI framework, QVAC. It is the ...

Companies running large language models face a persistent bottleneck: the memory consumed by key-value caches during ...

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

Accurate and precise viral titers are critical in cell & gene therapy and vaccine manufacturing, where dosing, safety margins, and product comparability are tightly linked to reliable vector ...

The stock prices of Micron Technology Inc (Nasdaq: MU) and SanDisk Corp (Nasdaq: SNDK), two of the top publicly traded memory chip storage companies, are taking a beating this week, halting a stunning ...

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 ...

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

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 ...

Huawei’s Computing Systems Lab in Zurich has introduced a new open-source quantization method for large language models (LLMs) aimed at reducing memory demands without sacrificing output quality.

This is a feature request to add a new 8-bit quantization method called Product Quantization with Residuals (PQ-R) to the bitsandbytes library. What is PQ-R? PQ-R is a hybrid quantization algorithm ...