The future of AI hinges on data transparency. Projects building decentralized mesh networks for AI training are gaining traction—particularly those that reward participants for contributing bandwidth and computational resources while ensuring data traceability throughout the pipeline.

Unlike traditional black-box AI systems, human-centric data networks create verifiable, transparent intelligence infrastructure. Contributors aren't just passive users; they're stakeholders in the economic model, earning rewards proportional to their contributions.

The question isn't whether decentralized data networks matter—it's whether open, traceable human data sources can genuinely unlock AGI development. When contributors retain insight into how their data shapes AI evolution, the entire ecosystem becomes more resilient and trustworthy.

What's your take? Can decentralized data commons accelerate AGI's timeline, or are we still missing crucial pieces?