👉 Bottles computing, also known as Liquid AI, is a novel approach to building large language models that leverages a unique architecture called Liquid Foundation Models (LFMs). Unlike traditional transformer-based models, Bottles computing utilizes computational units inspired by Liquid Time-constant Networks (LTCs), deep signal processing layers, and state-space models. These elements are combined into a single, optimized computational unit that can be dynamically scaled and adapted for various tasks, from natural language processing to time-series forecasting. This design allows Bottles computing to be highly efficient and flexible, capable of handling diverse workloads with superior performance and energy efficiency compared to conventional deep learning architectures. By integrating these advanced computational elements, Bottles computing aims to push the boundaries of AI capabilities in both research and practical applications.
