HBM has become one of the most successful and widely adopted examples of chiplet-based integration in AI systems.
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in which the probabilities of tokens occurring in a specific order is ...
At 100 billion lookups/year, a server tied to Elasticache would spend more than 390 days of time in wasted cache time.
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 ...
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 ...
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, ...
Less than a week after the United States and Israel launched military strikes on Iran, the conflict has sharply expanded, roping in several Middle Eastern nations and prompting some European countries ...
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 ...
In this video, I will show you how to use direct variation to help determine the missing variable, as well as how to determine if an equation is an example of direct variation or not. For an equation ...
Nabsys and the Research Lab of Dr. Martin Taylor, Brown University, Present Data Using the OhmX™ Platform at AGBT 2026 EGM enables the direct detection of endonuclease activity at the genome scale by ...