Right now language models can write exams, but embodied AI still fails in kitchens, warehouses, and hospitals. The adjective “robotic” brings a vision to mind that isn’t particularly smooth or capable. The issue isn’t how advanced the model is, but the quality of the data it’s trained on. AI that works in the real world needs real-world data: video, audio, movement, edge cases. The companies who build AI systems that work in the wild will be the ones who solve for data fidelity.