AI Agent · Nvidia · China · Import AI
Import AI 463: Self-improving robots; a 10k Chinese GPU cluster; and an elegiac essay for the human era
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The system both evaluates their success and also resets itself when they fail.
Key facts
- Some AI systems are better than others, but many AI systems are always better than fewer: GPT-5.5 within Codex and Opus 4.7 within Claude Code trade off with one another for best performance
- Hardware “Each station comprises two YAM (Yet Another Manipulator) arms from I2RT in a fixed bimanual configuration, a set of cameras, and a single workstation that runs the FastAPI server, policy inference, and the station’s agent
- As the number of robots scales, MRU decreases while GPU active utilization increases,” they write
- Researchers with NVIDIA have developed ENPIRE, software to get physical robotics to go through the same kind of autonomous experimentation and execution loop that AI agents go
Summary
Welcome to Import AI, a newsletter about AI research. NVIDIA sets up a crude self-improvement loop for real world robotics: …What if you could take the best ideas from AI agents and put them into the real world?. Researchers with NVIDIA have developed ENPIRE, software to get physical robotics to go through the same kind of autonomous experimentation and execution loop that AI agents go through. ENPIRE works the same way that coding agents work - a scaffold supervises some physical robots which are asked to complete tasks. Hardware “Each station comprises two YAM (Yet Another Manipulator) arms from I2RT in a fixed bimanual configuration, a set of cameras, and a single workstation that runs the FastAPI server, policy inference, and the station’s agent.