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 ...

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 ...

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 ...

The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...

Abstract: The rapid growth of model parameters presents a significant challenge when deploying large generative models on GPU. Existing LLM runtime memory management solutions tend to maximize batch ...

Brianna Tobritzhofer is a nationally credentialed Registered Dietitian and experienced health writer with over a decade of leadership in nutrition program development, policy compliance, and public ...

Memory-augmented Large Language Models (LLMs) have demonstrated remarkable capability for complex and long-horizon embodied planning. By keeping track of past experiences and environmental states, ...

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 ...

Shawn Shen believes that AI will need to remember what it sees in order to succeed in the physical world. Shen’s company Memories.ai is using Nvidia AI tools to build the infrastructure for wearables ...

Video gamers were among the first to grumble when supplies of random access memory (RAM) chips began to run short last year, causing prices to soar. But the ongoing crisis — which has been dubbed ...