Vector quantization, stock dips & RAMageddon – the real story behind how a memory compression algorithm went viral ...

Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to ...

RDVQ is a VQ-based generative image compression framework for efficient and controllable ultra-low-bitrate image compression. Conventional VQ-VAE learns powerful discrete representations, but its ...

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 ...

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.

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced new performance and cost-efficiency breakthroughs with two significant enhancements to its vector search. Users ...

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...