📍 OpenledgerHQ is a Web3 project focused on AI models and data incentive mechanisms, attempting to reconstruct the value distribution of the entire AI industry chain. In the past, AI model training often relied on massive amounts of freely scraped web data, while the actual contributors of this data received no compensation.

OpenLedger aims to change this situation, with its core idea being that every data upload, model training, and invocation can be clearly recorded on the chain, allowing for incentives based on real contributions.

The most notable technology of the project is PoA (Proof of Attribution), which can track which data truly played a role in training and inference, and distribute rewards accordingly. The logic behind this is quite simple: those who provide valuable data or models should receive corresponding rewards.

Under this mechanism, model training is no longer a matter of 'taking without giving back,' but rather a public, transparent, and clearly incentivized collaborative process.

🔧 OpenLedger has also created a whole set of tools to lower the participation threshold.

For example, Model Factory allows non-technical users to fine-tune mainstream models like LLaMA or Mistral through a graphical interface, while OpenLoRA enables these fine-tuned models to be combined, invoked, and paid for like LEGO, even allowing for profit-sharing. This means that any model developed by an individual can be called like an API, truly realizing the concept of 'model as a service.'

The infrastructure behind the project is also quite robust, built on the OP Stack, combined with the data availability support provided by EigenDA, ensuring not only performance and cost advantages but also a secure execution environment for AI models.

🎈 Of course, this path is not easy. Establishing data ownership, accurately assessing model value, and reasonably designing incentive mechanisms are not simple issues. But OpenLedger has already taken the first step through the launch of the testnet, expanding its collaborative network, and integrating multiple AI projects.

If traditional AI is a 'black box system' dominated by centralized giants, then what OpenLedger aims to do is open this black box and lay out the data, models, invocation processes, and profit-sharing methods on the table. This is not only a change in the technical route but also possibly a shift in business logic.

✈️ OpenLedger's Asia tour concluded perfectly with its last stop in Shanghai.