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

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 ...

Google researchers have proposed TurboQuant, a two-stage quantization method that, according to a recent arXiv preprint, can ...

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 ...

Why it matters: A RAM drive is traditionally conceived as a block of volatile memory "formatted" to be used as a secondary storage disk drive. RAM disks are extremely fast compared to HDDs or even ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

A Cache-Only Memory Architecture design (COMA) may be a sort of Cache-Coherent Non-Uniform Memory Access (CC- NUMA) design. not like in a very typical CC-NUMA design, in a COMA, each shared-memory ...

Magneto-resistive random access memory (MRAM) is a non-volatile memory technology that relies on the (relative) magnetization state of two ferromagnetic layers to store binary information. Throughout ...

Shimon Ben-David, CTO, WEKA and Matt Marshall, Founder & CEO, VentureBeat As agentic AI moves from experiments to real production workloads, a quiet but serious infrastructure problem is coming into ...