NVIDIA Demos Agent-Led Research Workflow
NVIDIA Developer · youtube · 2026-07-15
NVIDIA demonstrated an "agent-led autoresearch" workflow integrating NeMo RL, NeMo Gym, and Brev, enabling Codex to automatically configure GPU environments, run experiments, and log results via agent skills.
The video showcased two examples:
- Visual Counting + Reinforcement Learning: Building a visual star-counting environment for Qwen3-VL-2B-Instruct, boosting accuracy from 25.0% to 96.875% after training.
- Paper-to-code Validation: Using an agent to convert papers into code and initiate validation training, while researchers still manage research goals, budgets, and final judgments.
Accompanying resources include the GitHub repos for NeMo RL and NeMo Gym, along with Brev's launchable environment.
Related event: NVIDIA shows coding agents autonomously running research(6 posts)→
More from coding & agent
- 'My intelligence stack': developer splits AI coding work across Opus 5.5, Fable and Astra with human review gates — sh_reya · 2026-10-27
- Baseten webinar: evaluate open models for coding agents by benchmarking on your own merged PRs — baseten · 2026-10-27
- Thorsten Ball on working with agents: run more evals, automate everything, use the best models — omarsar0 · 2026-10-27
- Where to draw the approval line for scheduled agent jobs — Reddit discussion — MemStrata · 2026-10-27
- 4 MCP servers worth a look: full-text YouTube search, Chrome session reuse, Framer editing — Prior_Engineering486 · 2026-10-27
- DeepMind paper: LLMs can't sample randomly on their own — pass random numbers from code instead — rohanpaul_ai · 2026-10-27