The shift toward decentralized AI is reshaping how intelligence gets distributed and monetized. Rather than gatekeeping models behind corporate walls, projects like DeepNode AI are experimenting with an open-market approach where different AI models compete directly on performance.

Here's how the mechanism works: accuracy becomes the competitive edge—better models attract more usage. Token holders and validators participate in the ecosystem by staking or contributing resources. Builders ship models, validators ensure quality, and compute providers supply the infrastructure that runs everything. Rewards flow back to each stakeholder based on their contribution.

This is a stark contrast to centralized platforms where value extraction happens at a single point. With DeepNode AI and DN tokens, you're looking at an experiment in network economics where incentives theoretically align across the entire stack—from model developers to infrastructure operators.

Whether this model scales beyond hype is the real question, but it's worth watching how the token distribution and validator participation actually play out in practice.