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Nvidia showed that the harness, not the AI model, is now the real hero
Nvidia research shows that AI agents can perform well, and not go off the deep end, through fine-tuning, even if the AI model isn't that great at the task.
TL;DR
- Nvidia's research demonstrates that the AI 'harness' (software wrapper) is more crucial than the AI model for long-horizon tasks.
- A custom-tuned harness with good memory management and a 'supervisor' component enabled Claude Opus 5 to achieve a 100% score on the ARC-AGI-3 benchmark.
- Without the harness, Opus 5 scored only 30% on the same benchmark.
- The harness acts as the agent's scaffolding, managing memory, context, and tools, effectively turning a raw model into an agent.
- Open harnesses offer users greater control and the ability to significantly improve AI accuracy and manage costs.
- OpenAI's own research also found that tweaking harness settings dramatically improved their models' scores on similar benchmarks, though not to the 100% level achieved by Nvidia.