Part 2/11:
Liquid AI emerges from MIT's Computer Science and Artificial Intelligence Laboratory (CSIL), a prestigious hub for cutting-edge research. Unlike many industry players focused on scaling up transformers endlessly, Liquid AI prioritizes rethinking AI architecture itself. Their foundational approach revolves around "liquid foundation models" (LFMs)—lightweight, adaptable, and mathematically inspired models that challenge the prevailing paradigm of ever-larger neural networks.
At the core, their models leverage principles from mathematics and signal processing to offer advantages in speed, flexibility, and resource efficiency—crucial traits for deploying AI on devices with limited hardware capabilities.