Generalist - GEN-1.5: Embodied Foundation Models are One-Shot Learners
GEN-1.5 can in-context learn a new task from as little as 3 to 12 seconds of demonstration data — or adapt with 1 to 10 gradient steps on minutes of data. These capabilities emerge from pretraining on large-scale physical experience.
Table of Contents Introduction Introducing GEN-1.5 Scaling Pretraining for Robotics One-Shot Learning In-Context Compositional Generalization Zero-Shot Sim-to-Real Transfer Human-to-Robot In-Context Learning Few Gradient Step Adaptation Physical Generalization Looking Ahead Citation GEN-1.5 Embodied Foundation Models are One-Shot Learners Humans have a remarkable ability to perform new physical skills from only one or a few examples. Our latest robot foundation model, GEN-1.5, exhibits the beginnings of that same ability: it can learn a new task in seconds, from a single…
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