Dreamer’s creator wants robots to rehearse the unknown
A robot in your home cannot rely on a familiar map. Danijar Hafner’s stealth startup is bringing his model-based reinforcement learning work into humanoids, letting agents simulate possible futures inside learned world models before acting. That could replace some costly real-world trial and error with “dreamed” practice, a crucial shift if robots are to handle unfamiliar rooms, furniture, and failure modes.