Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run

Induction Labs has introduced an architecture called imagination models that learns from raw video data without requiring action labels. This approach addresses a common limitation in AI development, as most existing agents depend on precise metadata to connect specific actions to visual outcomes. By removing the need for labeled inputs, this foundation model can simulate diverse tasks, including desktop interactions and physics-based movements, after a single pretraining run.