General-Purpose Pre-Trained Models in Robotics

The impressive generalization capabilities of large neural network models hinge on the ability to integrate enormous quantities of training data. This presents a major challenge for most downstream tasks where data is scarce. As a result, we have seen a transformation over the years away from training large models entirely from scratch, and toward methods that utilize finetuning or few-shot learning. Classically, models might be pre-trained on a large-scale supervised or self-supervised task (e....