NVIDIA搞了个ENPIRE，让AI自己操控机器人反复试错，真实任务成功率干到99%，连GPU都能自己插。
NVIDIA联合CMU和伯克利推出ENPIRE系统，让AI智能体完全自主控制真实机器人循环，包括重置环境、搜索文献、实现想法、训练部署、自我验证等步骤。该系统在整理别针、安装GPU、绑扎带等灵巧任务上达到99%成功率。机器人通过自提出启发式成功信号进行爬坡优化，无需人类介入。
Project site: https://t.co/0j2Vo0IyJg Wenli has written an excellent technical thread, please check...
Project site: research.nvidia.com/labs/gear/enpi… Wenli has written an excellent technical thread, please check it out! x.com/_wenlixiao/sta… Wenli Xiao @_wenlixiao Autoresearch just left the sandbox and entered the embodied world. We are excited to introduce 𝐄𝐍𝐏𝐈𝐑𝐄: a system that drops frontier coding agents onto a fleet of real robots and hands them the entire loop: reset the environment → search the literature → implement ideas and build the infra → train and deploy → self-verify → analyze the logs and rewrite the code → repeat, until the policy is reliable in the real world. No human in the loop. Guided only by the robot's self-proposed, heuristic-based success signal, the agents hill-climb to 99% on dexterous real-world tasks: organizing pins into a box, seating GPUs, tying zip-ties. We envision the bottleneck in robotics shifting — from building smarter algorithms to building the closed physical feedback loops an agent can finally turn on its ow research.nvidia.com/labs/gear/enpi… 2ArGo3v From @NVIDIA @CMU_Robotics @Berkeley_AI 🧵 Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 0 🔄 1 ❤️ 17 👀 5297 📊 3 ⚡