TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...

On March 25, 2026, Google Research published a paper on a new compression algorithm called TurboQuant. Within hours, memory ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...

The dynamic interplay between processor speed and memory access times has rendered cache performance a critical determinant of computing efficiency. As modern systems increasingly rely on hierarchical ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...

Google introduces TurboQuant, a compression method that reduces memory usage and increases speed ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.

Modern multicore systems demand sophisticated strategies to manage shared cache resources. As multiple cores execute diverse workloads concurrently, cache interference can lead to significant ...

AMD's 7800X3D and 7950X3D CPUs reign supreme in the gaming realm, not solely due to their core count or clock speeds, but primarily owing to their abundant cache. CPU cache refers to a small yet ...