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Frontier coding agents operating ENPIRE's autonomous feedback loop can develop real-world robot manipulation policies that hit up to 99% success rates on tasks like PushT, pin organizing, and zip-tie cutting.

NVIDIA's ENPIRE harness lets coding agents autonomously iterate on real-world robot policies, achieving up to 99% success on dexterous manipulation tasks like PushT and zip-tie cutting. ✦ AI generated

NVIDIA researchers · Import AI · 2026-06-29 · original ↗

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Frontier coding agents can autonomously develop a policy to achieve a 99% success rate on challenging, dexterous manipulation tasks in the real world, such as PushT, organizing pins into a pin box, and using a cutter to cut a zip tie,

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▦ Nvidia ✳ ENPIRE ✳ PushT

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There will be a collapse of sentiment around robotics companies in 2026 because early humanoid deployments will fail to meet unrealistic timelines, triggering a hype backlash.Sarah Guo · No Priors · conf 80%

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gives example → Every research organization is described by its program.md — and once that's code, you can meta-optimize the program.md itself, creating recursive self-improvement.Andrej Karpathy · No Priors