DeepMind's blog post frames this as a major advance, but the industry should temper expectations. While enabling a single model to control diverse robot bodies is a notable technical feat, the practical path from lab demonstrations to reliable, cost-effective deployment is long and fraught. The harder problems—like achieving robust, human-level dexterity and safe, long-horizon reasoning in unpredictable settings—are only partially addressed here, as the source itself notes multifinger manipulation remains 'challenging.' The move to offer these models to early-access partners signals a push toward commercialization, but the success of this approach may hinge less on raw model capability and more on solving the immense integration and safety challenges inherent in physical AI.