NVIDIA's AI agents taught robots to install GPUs into motherboards without any human help

# NVIDIA's AI agents taught robots to install GPUs into motherboards without any human help Source: [https://www.tweaktown.com/news/112292/nvidias-ai-agents-taught-robots-to-install-gpus-into-motherboards-without-any-human-help/index.html](https://www.tweaktown.com/news/112292/nvidias-ai-agents-taught-robots-to-install-gpus-into-motherboards-without-any-human-help/index.html) 1. [TweakTown](https://www.tweaktown.com/) 2. [News](https://www.tweaktown.com/news/index.html) 3. [Artificial Intelligence](https://www.tweaktown.com/news/artificial_intelligence_ai/index.html) Three AI coding agents, including Claude Code and Codex, trained on real hardware, achieving 99% success on tasks like GPU installation and pin sorting\. [](https://www.tweaktown.com/news/112292/nvidias-ai-agents-taught-robots-to-install-gpus-into-motherboards-without-any-human-help/index.html#easyComment_Content) [](https://www.tweaktown.com/author/Hassam-Nasir/index.html) PublishedJun 21, 2026 11:08 PM CDT 2\-minute read time **TL;DR:**NVIDIA's ENPIRE framework enables AI coding agents to autonomously train robots for precise physical tasks like GPU installation, achieving a 99% success rate\. Developed with Carnegie Mellon and UC Berkeley, it uses a closed feedback loop and multiple AI agents collaborating to improve performance on real hardware\. 0:00 / 3:19 Use left and right arrow keys to seek audio\. NVIDIA has unveiled a framework that enables AI coding agents to train robots to perform high\-precision physical tasks without human supervision\. Developed alongside Carnegie Mellon University and UC Berkeley at NVIDIA's Generalist Embodied Agent Research lab, the system, called[**ENPIRE**](https://research.nvidia.com/labs/gear/enpire/), closes the loop between writing robot training code, testing it on real hardware, and refining it until it learns the desired behavior\. The demo that caught everyone's attention shows a robot arm selecting a graphics card, passing it to a second arm, and carefully seating it into a PCIe slot on a motherboard\. The test included a few other tasks, such as sorting metal pins into a box, cutting zip ties with real cutters, and the classic Push\-T benchmark\. [Popular Now:Enthusiast attempts to install second 12V\-2x6 connector on RTX 5090, is rewarded with a hole punched through the PCB](https://www.tweaktown.com/news/112274/enthusiast-attempts-to-install-second-12v-2x6-connector-on-rtx-5090-is-rewarded-with-a-hole-punched-through-the-pcb/index.html)Across these contact\-heavy tasks, the system achieved a 99% success rate under a pass@8 metric, which allows up to eight attempts per subtask with each retry informed by the previous failure\. - **Read more**:[**AI Agents like OpenAI's 'Operator' have a long way to go before replacing humans**](https://www.tweaktown.com/news/102985/ai-agents-like-openais-operator-have-a-long-way-to-go-before-replacing-humans/index.html)  VIEW GALLERY \- 3 IMAGES ENPIRE works as a closed feedback loop with four parts\. The environment module resets scenes and verifies results\. Policy Improvement module writes and refines control code using reward signals, camera footage, and failure data\. Rollout module runs physical trials on multiple robots simultaneously\. An Evolution module then compares agent branches, keeping what works and dropping what does not\. Three AI coding agents were tested inside the framework: Codex on GPT\-5\.5, Claude Code on Opus 4\.7, and Kimi Code on Kimi K2\.6\. Each developed its own algorithmic approaches, tested them on real hardware, and retained whatever improved the success rate\. The agents share work through Git, which gives the whole system a practical research workflow feel rather than a polished demo\.  A single agent took close to five hours to solve a task, whereas eight agents working in parallel cut that time to around two hours\. However, larger teams also burn significantly more tokens, as agents spend more time reading each other's logs, summarizing branches, and coordinating, leaving robots idle while waiting for inference to complete\. NVIDIA plans to open\-source ENPIRE, which would allow universities, startups, and hobbyists to run their own self\-improving robot labs\. Jim Fan, who co\-leads the GEAR lab,[**described it**](https://www.linkedin.com/feed/?trk=public_post_embed_linkedin-logo-image)as enabling autonomous research in the physical world for the first time\. The next test will be whether it holds up outside NVIDIA's own controlled lab environment\. Join Our Newsletter Join the TweakTown Newsletter for daily tech updates delivered to your inbox\.**Plus, win awesome prizes in our exclusive subscriber\-only global giveaways\!** By subscribing, you agree to our[Privacy Policy](https://www.tweaktown.com/legal/index.html#pp)\. You can unsubscribe anytime, and your data will not be shared without your consent\. [](https://www.tweaktown.com/author/Hassam-Nasir/index.html) [Hassam Nasir](https://www.tweaktown.com/author/Hassam-Nasir/index.html) Tech Reporter [](mailto:[email protected])[](https://x.com/technjunction)[](https://www.linkedin.com/in/hassam-nasir/) Hassam is a veteran tech journalist and editor with over eight years of experience embedded in the consumer electronics industry\. His obsession with hardware began with childhood experiments involving semiconductors, a curiosity that evolved into a career dedicated to deconstructing the complex silicon that powers our world\. From benchmarking PC internals to stress\-testing flagship CPUs and GPUs, Hassam specializes in translating high\-level engineering into deep, unbiased insights for the enthusiast community\. Stay Updated Follow TweakTown for breaking tech news, reviews, and daily updates\. [](https://www.google.com/preferences/source?q=tweaktown.com)[](https://apple.news/TK0sqd4X7QnWMc5EULcqp1w)