Liquid Neural Networks: A Leaner AI for Physical World Tasks

Liquid Neural Networks (LNNs) use continuous-time differential equations to process data, unlike LLMs which handle discrete tokens. LNNs keep fixed weights but adapt hidden states and time constants dynamically, enabling complex physics tasks with far less compute. This makes them promising for robotics and sensor applications where LLMs are overkill.