A new class of embedded AI is emerging, where microcontrollers run vector search once reserved for servers. How can hybrid ...

Multiverse Computing published a technique on August 25, 2026 that inverts one of the most reliable tradeoffs in model ...

The latest release of qvac-fabric-llm.cpp, the inference engine of the QVAC Fabric LLM, features TurboQuant integration for resource management in long-running inference sessions. Tether adopts the ...

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 ...

Google Research has unveiled a suite of new quantization algorithms designed to improve the efficiency of artificial intelligence systems, particularly in vector search and large language models. The ...

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 ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

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 ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

Huawei’s Computing Systems Lab in Zurich has introduced a new open-source quantization method for large language models (LLMs) aimed at reducing memory demands without sacrificing output quality.