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

Abstract: With the popularity of cloud services, Cloud Block Storage (CBS) systems have been widely deployed by cloud providers. Cloud cache plays a vital role in maintaining high and stable ...

Cloudflare's CEO called this "Google's DeepSeek moment"- referring to China's disruptive AI model. The internet called it "Pied Piper," after the fictional compression algorithm in HBO's "Silicon ...

At 100 billion lookups/year, a server tied to Elasticache would spend more than 390 days of time in wasted cache time. Cachee reduces that to 48 minutes. Everyone pays for faster internet. For ...

Nvidia stock tests a head-and-shoulders neckline after a 9% AI memory sell-off, with an 11% breakdown target in play.

Seagate Technology Holdings plc is downgraded to hold due to near-term risks from energy prices & potential AI CapEx ...

Bernstein upgrades Western Digital and raises targets on Seagate and Sandisk after Google's TurboQuant algorithm sparked a ...

Google researchers have proposed TurboQuant, a method for compressing the key-value caches that large language models rely on during inference. In a preprint, the team reports up to six times lower KV ...

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...

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 ...

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.