Exploring In-Context Learning in Gemini Robotics

This chapter discusses in-context learning as analyzed in a recent paper on Google’s Gemini robotics, focusing on zero-shot performance and the effects of image shuffling on model accuracy. It further examines trends in model performance, training intricacies, and future improvements in dataset evaluation for enhancing learning in reinforcement strategies.