With the price of RAM getting out of control, it might be a good idea to remind Linux users to enable ZRAM so they can get ...
Service providers must optimize three compression variables simultaneously: video quality, bitrate efficiency/processing power and latency ...
Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...
Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...
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 ...
We have seen the future of AI via Large Language Models. And it's smaller than you think. That much was clear in 2025, when we first saw China's DeepSeek — a slimmer, lighter LLM that required way ...
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 ...
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 ...
The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.
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 ...
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