ASTRAI: A Web3-Native AI Infrastructure
ASTRAI introduces 3 foundational layers:
✅ 1. Decentralized Compute Network
Anyone with idle GPU/ASIC resources can stake $ASTRA to register as a compute node.
Tasks are distributed via smart contracts — nodes get rewarded in real-time based on compute contributed.
All job logs are signed and verified on-chain (or via zkML in the future).
A node reputation system impacts task priority and rewards.
💡 DePIN-compliant: A fully on-chain Compute-to-Earn protocol.
✅ 2. Train-to-Earn Model Incentives
ASTRAI rewards contributors who help create and improve AI models — making training and fine-tuning an economic activity.
🧠 Incentivized Model Training:
Any user can propose a model training/fine-tuning task, stake $ASTRA, and crowdsource compute + data.
Participants (data providers, optimizers, model tweakers) get paid proportionally based on contribution.
All resulting models are tokenized as NFTs and attributed transparently.
🔁 Usage-Based Royalties:
Whenever a model is used (e.g., via API), the original contributors receive automatic revenue shares.
Revenue flow is governed by smart contracts, not centralized intermediaries.
🔗 Web3-native AI collaboration becomes possible — anyone can co-train a model and earn ongoing income.
✅ 3. Model-as-NFT (M-NFT)
Trained models are wrapped as composable, programmable NFTs with:
Ownership registry — includes creator address, data contributors, trainers
Usage licensing — on-chain permissioned inference
Royalty logic — splits income from usage/inference
API Key access — NFT owners get inference or plugin access
All model usage is metered and enforceable via smart contract, with optional zk-proof logs oracles.
📦 Models become programmable digital assets, not static files.
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