Robots Need To Reduce, Reuse, and Recycle | Embodied AI Lecture series at AI2

Despite numerous successes in deep robotic learning over the past decade, the generalization and versatility of robots across environments and tasks has remained a major challenge. This is because much of reinforcement and imitation learning research trains agents from scratch in a single or a few environments, training special-purpose policies from special-purpose datasets. In contrast, the rest of machine learning has drawn considerable success from repeatedly reusing broad datasets and recycling pre-trained models for a variety of purposes. Replicating this …

ai ai2 reduce robots