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Why your AI models are about to go obsolete 🤯

Julian Goldie Agency15 July 2026Watch on YouTube

Part of series

Ep. 13 · Hermes: AI-raad wint

Hoe Hermes Mixture of Agents meerdere AI-modellen combineert om individuele topmodellen te overtreffen.

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What you'll learn

  • AI models become obsolete quickly, but the underlying infrastructure remains stable and reusable
  • Hermes Mixture of Agents combines multiple frontier models that work together instead of relying on a single model
  • A judge model selects the best answer from outputs of multiple models, leading to better results
  • A multi-model approach provides future-proofing against model obsolescence

Frequently asked questions

What is the problem with current AI models?
Specific AI models become obsolete quickly and are constantly replaced by newer versions, making systems built on a single model not future-proof.
How does the Hermes Mixture of Agents approach work?
Multiple frontier models work together and provide answers, after which a judge model selects and refines the best answer for the final output.
Why is infrastructure more important than individual models?
While models change, the underlying infrastructure remains constant and can integrate new models, keeping your system flexible and future-proof.
Can a multi-model approach deliver better results than a single model?
Yes, by using a council of models that debate and a judge that refines, the system performs better than relying on a single model.

Topics

Description from the channel

While specific AI models evolve rapidly and face constant obsolescence, the underlying infrastructure remains constant. This exploration highlights the Hermes Mixture of Agents, demonstrating how integrating a council of frontier models can outperform single-model solutions. By utilizing a panel approach where models debate and a judge refines the final output, users can build a future-proof agent operating system that adapts to the shifting landscape of artificial intelligence. #AI #TechTrends #ArtificialIntelligence #MachineLearning #AgentOS