I used to think better AI only came from bigger models.
But spending more time around AI workflows changed my perspective. Sometimes the biggest improvement comes from one useful correction, better labeling, or community feedback that helps the model respond more accurately.
The problem is most contributors never get recognized once their data enters the system.
That’s why @OpenLedger stands out to me. Instead of treating data contribution like invisible labor, the focus is on attribution, provenance, and rewarding the people who actually improve AI performance.
As AI adoption grows, infrastructure that tracks who contributed what could become just as important as the models themselves.
The future of AI should not forget the humans helping train it.