A Worm With 302 Neurons Inspired Their Architecture — Ramin Hasani, Liquid AI

Liquid AI began by drawing inspiration from the C. elegans worm to develop Liquid Neural Networks, focusing on continuous-time, differentiable systems for efficient intelligence. Facing scaling challenges, they developed STAR, a meta-AI system for architectural search, optimizing hybrid models for quality, memory, latency, and speed, leading to their Liquid Foundation Models (LFMs). Their core focus is on bringing AI to the edge (on-device, in-car) for cost reduction, privacy, and offline capabilities, with successful deployments at Mercedes-Benz and Shopify. Liquid is also building a platform for 'sovereign AI,' enabling enterprises to customize and own their intelligence end-to-end, and researching massively multimodal systems, efficiency across the AI stack, and novel data types like DNA.