InfoQ

Google’s TurboQuant Compression May Support Faster Inference, Same Accuracy on Less Capable Hardware

Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...
IEEE

A Comparative Study of the Performance of Spark-based k-Means Algorithm Based on Euclidean Distance and Manhattan Distance

Abstract: Currently, with the widespread use of distributed information, traditional clustering algorithms can no longer meet the processing needs of massive information both in terms of accuracy and ...
IEEE

A Distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization

Abstract: This paper proposes a distributed algorithm for multiple agents to perform the Nonnegative Matrix Factorization (NMF) based on the Euclidean distance. The matrix to be factorized is ...
Ars Technica

Google’s TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x

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 ...
Endocrinology Advisor

AACE Releases 2026 Update to Type 2 Diabetes Management Algorithm

The American Association of Clinical Endocrinology (AACE) has released the 2026 update to its consensus statement algorithm for the management of adults with type 2 diabetes (T2D). The statement was ...