👉 Fluid, often used in the context of Liquid Foundation Models (LFMs), serves as a versatile and expressive computational framework that combines the strengths of various neural network architectures. Unlike traditional models, fluid is designed to be both expressive and efficient, allowing it to handle a wide range of tasks from reasoning and decision-making to natural language processing with fewer parameters and more adaptable computation. This flexibility enables fluid models to achieve high performance while being more scalable and easier to fine-tune for specific applications, making it a powerful tool in the rapidly evolving field of AI.
