Quantum computing news usually picks up near the end of the year, as companies try to provide evidence that they are hitting ...

Tether successfully integrated Google’s TurboQuant into the inference engine of its local AI framework, QVAC. It is the ...

Bitcoin & Ethereum ETF outflows hit records—driven by deleveraging, not abandonment. Click here to read more about my analysis.

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

"Optimization demands understanding hardware constraints at the silicon level," reflects Shaibujan Thankappan Kamalamma, whose career spans video codec work, streaming systems, and enterprise security ...

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 ...

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 ...

A team of researchers led by California Institute of Technology computer scientist and mathematician Babak Hassibi says it has created a large language model that radically compresses its size without ...

In a blog post published last week, Google announced that its scientists had developed an AI memory-compression algorithm, dubbed TurboQuant. "We introduce a set of advanced, theoretically grounded ...

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 ...