Intelligence is a general attribute that allows animals to build world models — internal representations of how the world operates and how they can interact with it to achieve distant goals. Animals evolved to solve a variety of problems under strong pressure to be efficient, and this convergent evolution in problem-solving space is a powerful guide for building AI.
Our approach: by training digital twins of animal bodies in increasingly realistic physics simulations, we expect our models to learn control strategies and representations that parallel those found in real nervous systems. This makes embodied AI a tool for neuroscientific discovery — reverse-engineering intelligence by rebuilding it.
We work at Janelia Research Campus, HHMI, combining robotics, biomechanical modeling, machine learning, and behavioral observation.
Contact
Rob Johnson Group Leader, Mechanistic Cognitive Neuroscience Janelia Research Campus, HHMI 19700 Helix Drive, Ashburn, VA 20147
Bluesky · Google Scholar · GitHub · YouTube