We talk a lot about "AI + Web3," but how much of it is actually running on-chain?

The reality is that most AI protocols today use crypto purely as a payment layer, while the actual data sourcing and model training remain entirely centralized. This is why I've been researching @OpenLedger lately.

They are building an EVM-compatible infrastructure designed to bring the entire AI lifecycle—data contribution, model fine-tuning, and inference execution—directly onto the blockchain. A few native concepts to keep on your radar:

• Datanets: Community-curated, domain-specific data networks.

• OpenLoRA: A framework allowing thousands of lightweight, optimized AI models to run efficiently on a single GPU (massive cost-saver).

• Proof of Attribution: The core mechanic that rewards contributors transparently.

The entire loop is fueled by $OPEN , serving as both network gas and the staking asset needed to deploy active AI agents safely without malicious behavior.

It feels refreshing to see a protocol focusing heavily on data provenance rather than just standard speculative hype. Will decentralized data curation eventually outperform corporate data silos? Let me know your thoughts on #OpenLedger below.