Vienna startup Ora Computing raised €3.5M and proved a 70-billion-parameter large language model can be compressed for under ...

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

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 ...

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 ...

Abstract: For uniform scalar quantization, the error distribution is approximately a uniform distribution over an interval (which is also a 1-dimensional ball ...

I encountered a runtime error related to NaNs during quantization and would like to ask whether this is a known issue.

Abstract: We construct a randomized vector quantizer which has a smaller maximum error compared to all known lattice quantizers with the same entropy for dimensions 5 ...

In the world of analog-to-digital conversion, precision is everything. Whether you're designing a medical-grade ECG device, an industrial sensor interface, or a high-fidelity audio codec, one silent ...

Specifications such as gain error, offset error, and differential nonlinearity help define an analog-to-digital converter’s performance. In part 1 of this series, we discussed an ideal ...

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced Better Binary Quantization (BBQ) in Elasticsearch. BBQ is a new quantization approach developed from insights ...

cmake -DMNN_USE_OPENCV=ON -DMNN_IMGCODECS=ON -DMNN_BUILD_TOOL=ON -DMNN_BUILD_BENCHMARK=ON -DMNN_BUILD_CONVERTER=ON -DMNN_BUILD_QUANTOOLS=ON .. [10:30:33] /home/nvidia ...