Long context AI no longer means using data centres thanks to Tether acting swiftly on groundbreaking research from Google.

Audiofile Engineering’s Fidelia plays your music collection with bit-perfect accuracy and lets you shape the sound through ...

Quantum computers located in a data center. Photo: Sven Hoppe/dpa (Photo by Sven Hoppe/picture alliance via Getty Images) To understand what quantum computers actually threaten, you first need to know ...

Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million document embeddings in float32 consumes 31 GB of RAM. For dev teams running ...

Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches by up to 6x. With 3.5-bit compression, near-zero accuracy loss, and no ...

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's new TurboQuant algorithm drastically cuts AI model memory needs, impacting memory chip stocks like SK Hynix and Kioxia. This innovation targets the AI's 'memory' cache, compressing it ...

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 ...

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 ...

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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As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...