What is OpenLedger:

OpenLedger is an AI-focused blockchain project aimed at enabling data, models, and agents to collaborate on-chain in a traceable and settlement-friendly manner: what data was contributed, how it influences model outputs, can all be recorded and rewarded based on impact.

Technical roadmap:

• Datanets: Organize documents/knowledge into community-built datasets, contributions and version history can be traced, which can serve as a basis for subsequent profit sharing and auditing.

• Model Factory & OpenLoRA: Complete the fine-tuning and deployment of small models (LoRA) in a few steps; developers can expose capabilities as APIs for applications to call.

• PoA (Proof of Attribution): Use scalable technologies like Infini-gram to trace the source fragments of model outputs at the 'token level', providing a basis for distributing rewards based on impact (verifiable, auditable).

OpenLedger follows the L2 route of the Ethereum ecosystem: built on OP Stack and integrated with EigenDA for data availability (DA), providing higher throughput and lower fees while retaining Ethereum's secure settlement, suitable for AI's high-frequency interactions and billing needs; EVM compatibility facilitates developer migration and expansion.

What pain points can it solve?

• Transparency: Data/models/call records are publicly auditable, reducing 'black box';

• Attribution and Incentives: Quantify 'how much impact does someone's data bring' and distribute profits accordingly;

• Implementation efficiency: OpenLoRA supports serving a large number of LoRA variants with minimal GPU resources, suitable for rapid trial and deployment in multiple scenarios.

Three use cases

1. Legal/Compliance Assistant: Answers must have a 'source'; PoA can point answers to specific articles/case fragments; enterprises find it easier for auditing and payment settlement.

2. Manufacturing SOP Copilot: Create Datanets from equipment manuals and quality inspection standards, directly ask on workstation tablets; answers are both low-latency and can trace back versions and responsible persons.

3. Wallet AI Assistant: Create small models for strategy Q&A/risk control prompts, launch as an API, called by users or DApps and settled by usage.

Risks and Alerts

• Content and data must have compliant authorization, be cautious regarding privacy/copyright;

• Profit sharing depends on the number of real usage and quality, no guaranteed income;

• Any token has volatility and project execution risks, always DYOR. $OPEN

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