Google engineers have developed a method to compress artificial intelligence (AI) data so that it requires up to six times less working memory to function. With the new system, called TurboQuant, AI ...

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 ...

Memory prices are falling, and stock prices of memory companies took a hit, following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing ...

Forbes contributors publish independent expert analyses and insights. Tim Bajarin covers the tech industry’s impact on PC and CE markets. This voice experience is generated by AI. Learn more. This ...

Google developed a new compression algorithm that will reduce the memory needed for AI models. If this breakthrough performs as advertised, it could drastically reduce the amount of memory chips ...

Micron Technology (MU) shares fell to $339 Monday as fears over Alphabet’s (GOOGL) TurboQuant AI memory-compression algorithm raised concerns about long-term demand for high-bandwidth memory across ...

TurboQuant is a compression algorithm introduced by Google Research (Zandieh et al.) at ICLR 2026 that solves the primary memory bottleneck in large language model inference: the key-value (KV) cache.

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 ...

Lam Research (LRCX) delivered a 321% total return over three years by dominating AI chip production through etch and deposition tools for high-bandwidth memory and advanced logic, with advanced ...

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 ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...