来自MSN

Google says TurboQuant cuts LLM KV-cache memory use 6x, boosts speed

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...
Network World

Tether is shipping TurboQuant KV-cache quantization with Vulkan support into its QVAC SDK

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

AI hit the memory wall — now it needs a new context tier

As inference workloads evolve from discrete question-and-answer exchanges into persistent, multi-step agentic systems, GPU ...
InfoWorld

How to use HybridCache in ASP.NET Core

HybridCache is a new API in .NET 9 that brings additional features, benefits, and ease to caching in ASP.NET Core. Here’s how to take advantage of it. Caching is a proven strategy for improving ...
VentureBeat

How attention offloading reduces the costs of LLM inference at scale

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...