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, ...

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Lightbits Labs Ltd. today is introducing a new architecture aimed at addressing one of the most stubborn bottlenecks in large-scale artificial intelligence inference: the growing mismatch between the ...

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 ...

As AI workloads extend across nearly every technology sector, systems must move more data, use memory more efficiently, and respond more predictably than traditional design methodologies allow. These ...

AMD recently published a new patent that reveals that the company is working on making its 3D V-cache tech even better. Back in early 2021, we started hearing the first whispers and murmurs of a new ...

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 ...

DRAM access latency is typically 50–100 ns, which at 3 GHz corresponds to 150–300 cycles. Latency arises from signal propagation, memory controller scheduling, row activation, and bus turnaround. Each ...