👉 The Fluid module is a versatile and efficient component in Liquid Foundation Models (LFMs) that enables the seamless integration of various data types, including text, images, and time-series signals, into a unified, composable architecture. It operates by breaking down input data into smaller segments, known as "patches," which are then processed through a series of customizable Liquid operations. These operations can include arithmetic, logical, and attention mechanisms, allowing the model to dynamically adapt its behavior based on the input context. This modular design not only enhances flexibility and expressiveness but also ensures that the model can be optimized for specific tasks, making it highly effective for complex applications like natural language understanding and time-series forecasting.
