NVIDIA shows AI agents teaching a robot to walk an obstacle course in sim
tomaszbednarz · x · 2026-11-04
NVIDIA's technical blog details an end-to-end workflow where AI agents (Hermes, Nemotron 3.5 Bolt, Astra) turn a prompt into a project plan, build 3D assets in FreeCAD/Blender, assemble the scene in Isaac Sim with Newton physics, then train a perception-and-locomotion policy in Isaac Lab across 4,096 parallel environments on an RTX PRO 6000 Blackwell GPU. The policy is validated locally on RTX Spark before sim-to-real transfer with better actuator models and domain randomization. All assets and a Hugging Face sim-to-real tutorial are publicly available.
More from coding & agent
- Free no-sign-in MCP server compiles LaTeX (pdflatex/xelatex) and explains errors in plain words — PurplelinkPL · 2026-11-04
- Multi-agent review pipeline: Claude coordinates, Grok reviews, Codex fixes — PawelHuryn · 2026-11-04
- WoW x League of Legends Arena mashup: roguelike 2v2v2v2 PvP with per-round drafts — TAbrodi · 2026-11-04
- Kimi K3.1 Pro weights drop tomorrow: 2.8T params, 1M-token context — togethercompute · 2026-11-04
- 86% of orgs run AI agents, but under 18% can automatically stop a misbehaving one — amasad · 2026-11-04
- CMU Study: Harness Engineering Boosts Scientific Agents Without Retraining — niloofar_mire · 2026-11-04