How OpenLedger Turns Attribution Into Real Rewards
Ever wondered how data contributors actually earn from AI models onchain?
@OpenLedger has built the answer — through Attribution Aggregation and Reward Distribution 🔥
Here’s how it works 👇
1️⃣ Every Model Output (zt) is traced back to the training points that shaped it.
2️⃣ Each training point belongs to a DataNet — a community-built dataset onchain.
3️⃣ The system sums up all influence scores from each DataNet that contributed.
4️⃣ These influence weights are normalized and recorded onchain, forming a verifiable trail.
⚙️ Formula in action:
I(Di, zt) = Total influence of DataNet Di on output zt
W(Di, zt) = Proportional weight → basis for real-time rewards 💸
This means contributors don’t just upload data — they own influence.
Every model inference becomes an opportunity to earn, track, and prove impact.
It’s not just AI — it’s an economy of intelligence.