MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — without the hours of GPU training that prior methods required.
Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory ...
Accelerating memory-dependent AI processes, Penguin's MemoryAI KV cache server increases memory capacity by integrating 3 TB ...
GPU memory (VRAM) is the critical limiting factor that determines which AI models you can run, not GPU performance. Total VRAM requirements are typically 1.2-1.5x the model size due to weights, KV ...
Forbes contributors publish independent expert analyses and insights. Covering Digital Storage Technology & Market. IEEE President in 2024 At the 2025 Nvidia GPU Technology Conference the company ...
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