GitHub

LZHAM - Lossless Data Compression Codec

LZHAM is a lossless data compression codec written in C/C++ (specifically C++03), with a compression ratio similar to LZMA but with 1.5x-8x faster decompression speed. It officially supports Linux x86 ...
techtimes

How Streaming Platforms Use Algorithms and Recommendation Engine Systems to Personalize Content

Explore how streaming algorithms, personalization, and the content pipeline work together to power recommendation engine systems and shape what viewers see on streaming platforms. Pixabay, SunnyMuneko ...
Geeky Gadgets

Why Google’s TurboQuant Algorithm is Disrupting the AI Memory Chip Market

Google’s TurboQuant is making waves in the AI hardware sector by addressing long-standing challenges in memory usage and processing efficiency. Developed with components like the Quantized ...
PC Magazine

Nvidia, Intel Texture Compression Techs Cut VRAM Use Dramatically

Intel and Nvidia showed off their respective AI-powered texture-compression technologies over the weekend, demonstrating impressive reductions in VRAM use while maintaining texture quality, or even ...
Tom's Guide

Stop getting tricked by airline algorithms — how to use ChatGPT to find the real deals

For the fastest way to join Tom's Guide Club enter your email below. We'll send you a confirmation and sign you up to our newsletter to keep you updated on all the latest news. Join the Tom's Guide ...
Android

This Google AI Breakthrough Could End the Global RAM Crisis Sooner Than Expected

Google has unveiled TurboQuant, a new AI compression algorithm that can reduce the RAM requirements for large language models by 6x. By optimizing how AI stores data through a method called ...
TechSpot

Google's TurboQuant compression tech cuts LLM memory use by 6x with no accuracy loss

The big picture: Google has developed three AI compression algorithms – TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss – designed to significantly reduce the memory footprint of large ...
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 ...
winbuzzer.com

Google’s TurboQuant Algorithm Slashes LLM Memory Use by 6x

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...
The Next Web

Google’s new compression algorithm cut memory stocks within hours of publication

Google published a research blog post on Tuesday about a new compression algorithm for AI models. Within hours, memory stocks were falling. Micron dropped 3 per cent, Western Digital lost 4.7 per cent ...
TechCrunch

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

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 ...
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 ...