AGI Is Not Multimodal

The Gradient · 1 year ago

An AI researcher argues that multimodal AI models will fail to achieve artificial general intelligence because they lack embodied physical understanding of the world, relying instead on learned syntactic patterns rather than genuine world models. Large language models achieve language proficiency through statistical rules and heuristic memorization of training data rather than understanding physical reality, as evidenced by their inability to solve sensorimotor tasks like sweeping a floor or repairing a car. Achieving true AGI requires systems grounded in physical interaction with environments rather than scaling multimodal networks that treat modalities as separate components to be combined.