Abstract: In both resource-scarce and resource-abundant scenarios (i.e., in the scenarios where service demands exceed/do not exceed available resources), it is a critical challenge to design ...
Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...
Abstract: This study examines the application of Large Reasoning Model (LRM)-based artificial intelligence (AI) agents to accelerate scientific discovery, with a specific focus on the rapid ...
If countries turn to export controls to regulate AI algorithms, trading data and models, they should make sure to be clear about which types of end uses would be subject to restrictions and what types ...
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 ...
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 ...
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 ...
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 ...
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