Roboticists historically traded sci-fi ambitions for the narrow utility of auto plant arms. This gap between complex dreams and simple tools like the Roomba defined the field for decades. Modern MIT research now bridges this divide using neural networks. Practitioners can finally move beyond rigid programming toward flexible, generalized machine learning for physical agents.