Vienna startup Ora Computing raised €3.5M and proved a 70-billion-parameter large language model can be compressed for under ...

Sandisk remains investable after a 10x rally, driven by robust demand and a shift to long-term contractual revenues. Read why ...

At a time of heavy automation and job losses, enterprises must also consider how useful individuals with real, practical experience might be ...

Tether AI just released TurboQuant as open-source software, delivering a tool that compresses the memory footprint of large language model inference by up to five times. The technology targets a ...

LOS ALTOS, Calif., May 19, 2026 /PRNewswire/ -- Verkor, Inc., an Enterprise Agentic AI startup, unveiled Industry's first TurboQuant silicon IP, VerTQ. VerTQ is an ...

It’s hard to ignore the seismic shifts brought about by algorithm-driven content. Every time you scroll through your social media feed or check your favorite news app, algorithms are diligently at ...

Google AI has introduced a major breakthrough with TurboQuant, a system that reduces KV cache memory usage by up to 6x while improving chatbot efficiency during real-time conversations. This allows AI ...

Alphabet's Google has unveiled its KV cache quantization compression technology, TurboQuant, promising dramatic reductions in memory usage for AI inference. While the innovation has captured global ...

Gothenburg promised to optimise school admissions with a piece of code. The resulting chaos showed how unaccountable systems are ruining lives We like to imagine that injustice announces itself loudly ...

In March 2026, Google Research announced ' TurboQuant ' as one of a new suite of compression technologies for large-scale language models and vector search engines. To visually understand what ...

It's been a tough past couple of weeks for Micron Technology and Sandisk shareholders. Both computer memory chipmakers have been outright upended. Blame Google parent Alphabet (NASDAQ: GOOG)(NASDAQ: ...

TurboQuant (arXiv 2504.19874, ICLR 2026) compresses the key-value cache that transformer models maintain during inference. It does not touch model weights. Its purpose is to reduce memory consumption ...