Crazy how far robot foundation models have come in terms of true fine motor skills: Without task-specific training, no sim-to-real transfer, and... fully autonomous ❗ The dual-arm robot places an O-ring onto a hydraulic rod and removes it again in a fully autonomous and repeatable manner, with frequent contact, precision, and without task-specific training. The model uses short physical prompts (a demonstration lasting just a few seconds) for one-shot learning and adapts to new manipulations in just a few gradient steps. No sim-to-real transfer is necessary; instead, pretraining is performed on real interaction data. It is precisely these types of tasks (O-rings, seals, small components) that are classic bottlenecks in assembly. If this can be reliably scaled up, the cost-effectiveness of robots in manufacturing will change significantly. Source: @GeneralistAI / Congrats to @peteflorence, @andyzengineer and the team on the GEN-1.5 demo!