.@OpenledgerHQ aims to move the core elements of the AI world—data, models, and AI agents—onto the chain to become assets that are "Equity Confirmation, profit-sharing, and transparent." Using their Datanet, they restructure the fragmented training data, allowing every piece of data to be traceable and recorded on-chain.

The key point is that it is not a super giant like a large model, but rather focuses on SLM Specialized Language Model, a specialized small model. This type of model is lighter, easier to deploy, and more suitable for running on-chain, creating a complete AI ecosystem.

$OPEN tokens are not just for show. They serve multiple functions such as gas model invocation fees, data contribution incentives, and governance voting. This kind of multi-purpose token design is relatively reasonable in the AI + Web3 scenario because as long as there is data being contributed, models being updated, and agents running, the entire network can generate real value flow.

The ecological part is also moving quite fast. Various AI model markets, data markets, on-chain Agents, and the prototypes of these applications are already in operation. After the token launch, the on-chain activity has also clearly increased. If Datanet runs smoothly in the future, developers will be very willing to deploy small models on this chain.

To put it simply, OpenLedger wants to reclaim the value distribution of AI from centralized platforms and redistribute the value to data providers, model developers, and computing power contributors. If this narrative is implemented, it will represent a significant paradigm shift.

The infrastructure is still in its early stages, whether the model ecosystem can truly thrive depends on whether subsequent developers will come to build it. But at least the roadmap is correct.

The integration of AI on-chain may not take off today, but it is certainly one of the trends of the future, and OpenLedger is at this intersection, continuing to push forward.
@OpenledgerHQ #open $open