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Liquid AI
MIT spinout building Liquid Foundation Models (LFMs), a non-transformer architecture combining gated short convolutions and grouped-query attention, unified under a linear input-varying (LIV) operator framework. Architecture search is hardware-in-the-loop via the STAR engine. LFM2 models (350M to 2.6B parameters) target CPU, GPU, and NPU inference on-device, trained on 10T tokens.
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