Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.
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Google unveiled TurboQuant, a method that cuts the memory bottleneck slowing large AI models

Companies running large language models face a persistent bottleneck: the memory consumed by key-value caches during ...