#openledger $OPEN OpenLedger is an AI blockchain that unlocks liquidity between data, models, applications, and agents.
It supports the training, deployment, and on-chain tracking of professional AI models and datasets, tackling key challenges around transparency, attribution, and verifiability.
At its core is Proof of Attribution, a mechanism that identifies the data points influencing model outputs and rewards their contributors.
OpenLedger is built on over a decade of research from Stanford University, developed by four leading scholars.
OpenLedger addresses two aspects of the problem:
OpenLedger empowers developers to gather professional data from the community through a data network and build AI models using a no-code model factory, directly deploying them onto the OpenLedger blockchain.
Each model is embedded with Proof of Attribution, ensuring incentives for data contributors, interpretability of model outputs, and full traceability of the AI lifecycle.
The OPEN token is the native gas token of the OpenLedger blockchain, playing a central role in shaping network economics and governance.
Attribution rewards: When the data from contributors is deemed to influence model inference, they will receive OPEN tokens.
Payments and settlements: OPEN tokens are used for transactions within the OpenLedger AI blockchain QT network, including inference fees, model access, staking, and data network usage.
Governance: OPEN token holders can participate in protocol governance. The governance system will oversee protocol parameters, upgrades, ownership transfers, and other key network decisions.
Ecosystem incentives: The distribution of OPEN tokens is designed to encourage the development of models, data networks, and agents within the ecosystem.
OpenLedger consists of three main components:
Products:
Model Factory and OpenLoRA: An end-to-end infrastructure for training, fine-tuning, and hosting models, and validating LoRA adapters on-chain.
Proof of Attribution (PoA): An on-chain attribution system that identifies the impact of data on model outputs and pays contributors in OPEN tokens.
Data Network: A community-driven platform for collecting raw data and transforming it into LLM-ready enhanced datasets.
AI Studio: A development environment for building, deploying, and monetizing AI agents and applications using an on-chain registry.
It supports the training, deployment, and on-chain tracking of professional AI models and datasets, tackling key challenges around transparency, attribution, and verifiability.
At its core is Proof of Attribution, a mechanism that identifies the data points influencing model outputs and rewards their contributors.
OpenLedger is built on over a decade of research from Stanford University, developed by four leading scholars.
OpenLedger addresses two aspects of the problem:
OpenLedger empowers developers to gather professional data from the community through a data network and build AI models using a no-code model factory, directly deploying them onto the OpenLedger blockchain.
Each model is embedded with Proof of Attribution, ensuring incentives for data contributors, interpretability of model outputs, and full traceability of the AI lifecycle.
The OPEN token is the native gas token of the OpenLedger blockchain, playing a central role in shaping network economics and governance.
Attribution rewards: When the data from contributors is deemed to influence model inference, they will receive OPEN tokens.
Payments and settlements: OPEN tokens are used for transactions within the OpenLedger AI blockchain QT network, including inference fees, model access, staking, and data network usage.
Governance: OPEN token holders can participate in protocol governance. The governance system will oversee protocol parameters, upgrades, ownership transfers, and other key network decisions.
Ecosystem incentives: The distribution of OPEN tokens is designed to encourage the development of models, data networks, and agents within the ecosystem.
OpenLedger consists of three main components:
Products:
Model Factory and OpenLoRA: An end-to-end infrastructure for training, fine-tuning, and hosting models, and validating LoRA adapters on-chain.
Proof of Attribution (PoA): An on-chain attribution system that identifies the impact of data on model outputs and pays contributors in OPEN tokens.
Data Network: A community-driven platform for collecting raw data and transforming it into LLM-ready enhanced datasets.
AI Studio: A development environment for building, deploying, and monetizing AI agents and applications using an on-chain registry.