Abstract: Cache memory has been introduced to accelerate embedded system performance and is automatically managed without programmer intervention through hardware-based cache controllers. However, ...

Google AI has introduced a major breakthrough with TurboQuant, a system that reduces KV cache memory usage by up to 6x while improving chatbot efficiency during real-time conversations. This allows AI ...

The new MemoryAI KV cache server from Penguin Solutions leverages CXL technology to expand memory capacity, enabling faster inference, higher throughput, and improved efficiency for complex AI ...

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...

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, ...

FREMONT, Calif.--(BUSINESS WIRE)--Penguin Solutions, Inc. (Nasdaq: PENG), the AI factory platform company, today announced the industry's first production-ready KV cache server that utilizes CXL ...

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 ...

Paper: Agent Memory Below the Prompt: Persistent Q4 KV Cache for Multi-Agent LLM Inference on Edge Devices (PDF) When multiple LLM agents share one local model, every new request re-computes the full ...

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 ...