👉 The Fluid is a feature in Liquid Foundation Models (LFMs) that enables dynamic composition of input signals, allowing the model to adaptively combine different signal types and weights during inference. Unlike traditional fixed architectures, Fluid lets the model learn how to best combine various input signals—such as text, images, or audio—in real-time, optimizing its output based on the specific context. This flexibility enhances performance across diverse tasks by dynamically adjusting signal processing, making LFMs more efficient and adaptable for complex applications like conversational agents or multimodal systems.
