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Scientists managed to shrink AI context 16× without major loss of accuracy. It paves the way for cheaper models
Researchers from Princeton, Harvard, and Columbia University have introduced LCLM — a model that compresses the input context of language models by up to 16× while maintaining surprisingly high accuracy. The result is up to 8.8× faster inference and lower costs.