What happens when you give AI coding agents a lab full of robotic arms, some compute resources, and a “generous token budget” for teaching the robots various tasks? The agents can apparently figure out a training regimen that teaches the robots to successfully cut zip ties and even insert GPUs into thin sockets on motherboards.

That glimpse into how AI can act in a fully autonomous way to automate robot training was made possible by a new agent harness framework—software that wraps around AI models to enable their use of various tools while also providing capabilities such as memory, context, constraint, and feedback loops. That agentic harness, called ENPIRE, was developed by robotics researchers at the Nvidia GEAR (Generalist Embodied Agent Research) lab alongside collaborators from Carnegie Mellon University in Pittsburgh and the University of California, Berkeley.

“A part of our NVIDIA GEAR lab now self-improves tirelessly overnight,” wrote Jim Fan, director of AI at NVIDIA, in a LinkedIn post. “We just read the reports in the morning.”

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It may appear that humanoid robots capable of handling any task have almost arrived—especially when tech companies showcase them performing acrobatic feats or handling household chores. But there is still a significant gap between these robot demonstrations and proving that the same robots can reliably and repeatedly manage such tasks in the real world.

The latest wave of robot videos can be particularly tricky, given the human tendency to anthropomorphize objects with a humanoid figure. A robot arm doing a dance move may simply seem “cool,” but a humanoid robot doing the same dance move can trigger more misleading assumptions, said Jonathan Hurst, cofounder of Agility Robotics and a robotics researcher at Oregon State University.

“People automatically extrapolate and assume that the robot that looks like a person can do all the things that a person who can dance could do—which is not true,” Hurst told Ars. “But a lot of the startup companies do kind of prey on that for being able to raise a lot of money.”

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