Hosted on MSN

AI method speeds detection of therapeutic viral vectors

Researchers at North Carolina State University have developed an AI-enhanced electrochemical sensing method to quickly and accurately quantify viral vectors used in gene therapies. The approach uses ...
TweakTown

Google's TurboQuant cuts AI working memory by 6x, but it won't fix the global RAM shortage

TL;DR: Google developed three AI compression algorithms-TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss-that reduce large language models' KV cache memory by at least six times without ...
Forbes

Google’s TurboQuant Compression Could Increase Demand For AI Memory

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. On March 24, 2026 Amir Zandieh and Vahab Mirrokni from Google Research published an article ...

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

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
marktechpost

Google Introduces TurboQuant: A New Compression Algorithm that Reduces LLM Key-Value Cache Memory by 6x and Delivers Up to 8x Speedup, All with Zero Accuracy Loss

The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...
Semiconductor Engineering

Outlier-aware Quantization Framework Co-designed With Heterogeneous NVM For SLM Deployment on Edge Platforms (UCSD et al.)

A new technical paper titled “QMC: Efficient SLM Edge Inference via Outlier-Aware Quantization and Emergent Memories Co-Design” was published by researchers at University of California San Diego and ...
IEEE

Diagnosing and Improving Vector-Quantization-Based Blind Image Restoration

Abstract: Vector-Quantization (VQ) based discrete generative models are widely used to learn powerful high-quality (HQ) priors for blind image restoration (BIR). In this paper, we diagnose the ...
IEEE

Conditional Entropy-Constrained Multi-Stage Vector Quantization for Semantic Communication

Abstract: This letter presents a conditional entropy-constrained multi-stage vector quantization (CEC-MSVQ) framework for semantic communication (SC). The proposed method integrates multi-stage VQ ...
Bleeping Computer

Google exposes BadAudio malware used in APT24 espionage campaigns

China-linked APT24 hackers have been using a previously undocumented malware called BadAudio in a three-year espionage campaign that recently switched to more sophisticated attack methods. Since 2022, ...
TechNode

Huawei Zurich Lab’s New Open-Source Tech Lets LLMs Run on Consumer GPUs

Huawei’s Zurich Computing Systems Laboratory has released SINQ (Sinkhorn Normalization Quantization), an open-source quantization method that reduces the memory requirements of large language models ...
VentureBeat

Huawei's new open source technique shrinks LLMs to make them run on less powerful, less expensive hardware

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.