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

Cleveland Clinic researchers are unlocking quantum computing's full potential through the creation of a new computing ...

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

At the architectural level, Command A+ represents a major evolution from Cohere’s previous dense models. It is a decoder-only Sparse Mixture-of-Experts (MoE) Transformer. While the model houses a ...

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 ...

Object-Centric Learning (OCL) aggregates image or video feature maps into object-level feature vectors, termed \textit{slots}. It's self-supervision of reconstructing the input from slots struggles ...

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 ...

A research team led by Associate Prof. Wang Anting from the University of Science and Technology of China (USTC) of the Chinese Academy of Sciences (CAS) proposed a method for multidimensional ...