IEEE

Finite Word-Length Effects for Symmetric Matrix Inversion with Vector-Based Algorithms

Abstract: In this work, we present an investigation of the numerical properties of different symmetric matrix inversion algorithms, with a focus on two vector-based algorithms: Block LDLT and Tile ...
Barron's

Why TurboQuant Hammered Memory Stocks—and Why ‘Jevons’ Paradox’ Means the Market Might Be Wrong

Highflying memory stocks like Micron and SanDisk have been dented this week and it might have something to do with TurboQuant, a compression algorithm detailed by Google in a research paper this week.
VentureBeat

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

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 ...
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 ...
IEEE

High-Speed Privacy Amplification Algorithm Based on Two-Dimensional Cellular Automata in Quantum Key Distribution

Abstract: Privacy amplification is a critical component in quantum key distribution (QKD) to eliminate eavesdropper information and distill unconditionally secure ...