NVIDIA Discusses Self-Improving Agents
AllThingsApx · x · 2026-07-11
NVIDIA Health shared and discussed a research concept for self-improving agents: an agent can only continue to improve if the evaluation system is sufficiently reliable. To address this, they proposed using a Red Queen Gödel Machine to allow the agent and evaluator to co-evolve while remaining anchored to reliable ground truth.
The post outlined two experimental findings:
- Coding tasks: Achieved better results than previous baselines while using 1.35–1.72× fewer search tokens.
- Paper review experiment: Combining Nemotron 3 Ultra worker agents with a frontier meta-agent achieved performance close to "using only a frontier model," but at approximately 13× lower search-token cost.
Finally, the post noted that deploying such self-improving agents into biology and chemistry scenarios will require domain-specific tools, models, and evaluation loops. NVIDIA believes the BioNeMo Agent Toolkit represents a key part of the future direction.
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