Roboticists historically traded science fiction ambitions for the narrow utility of auto plant arms and Roomba vacuum cleaners. This gap between aspiration and execution defined the field for decades. Now, researchers leverage large-scale data to bridge that divide. Practitioners must now balance complex physical hardware with the rapid iteration of neural networks.