Figure AI Achieves New Milestone in Humanoid Skill Adaptation
For the first time, a humanoid robot can fold laundry using a neural net.
Yesterday, Figure Robotics showcased a humanoid robot folding towels using its Helix foundation model—a neural network architecture built for rapid skill transfer. Unlike traditional telerobotics or purely simulated training, the system blends teleoperation with minimal data requirements, enabling the robot to acquire new tasks after mastering others, such as those in logistics.
Notable capabilities include real-time self-correction and movement adaptation based on proprioceptive feedback—conceptually similar to Neuralink’s approach to integrating brain signals for prosthetic control. This convergence of robotics and neurotechnology suggests a future where industrial and domestic robots move beyond rigid programming, developing more human-like motor learning.
For industry and logistics, the potential is significant: as foundation models in robotics advance, we could see faster deployment of robots into new task domains without extensive retraining—reducing integration costs and expanding practical applications across warehouses, distribution centers, and factories worldwide.
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