OpenLedger @ Openledger HQ Research Report: Explorers Building Decentralized AI Data Infrastructure Da Mao&Foundation Establishment&Earn Points for Airdrops 🪂： https://testnet.openledger.xyz/?referral_code=ka7svjsxoq What is OpenLedger? OpenLedger is a decentralized AI infrastructure platform with blockchain technology at its core, aimed at solving data bottlenecks in artificial intelligence development by building permissionless and verifiable data layers. Its core goal is to establish a transparent and fair value distribution ecosystem for developers, data contributors, and model trainers, and promote the popularization and commercialization of specialized language models (SLM). Technical Architecture | Advantages The project revolves around three core modules: Datanets: A vertical data marketplace (such as healthcare, finance, art, etc.) that records data sources, usage counts, and contributor rights through blockchain. Proof of Attribution: A cryptographic based contribution tracking system that quantifies the impact of data on model output and automatically allocates benefits. Payable AI: Transforming AI models into assets that can be automatically distributed. After developers deploy the models, the revenue generated by user usage is distributed proportionally to data providers, developers, and other participants. Key Developments July 2024: Completed a seed round financing of $8 million, led by Polychain Capital and Borderless Capital, with participation from HashKey Capital, EigenLayer founder Sreeram Kannan, and others. December 2024: Testing online, supporting users to earn points by running nodes, contributing data, or completing community tasks, which can be exchanged for ecological tokens in the future. Project Advantage: Why is OpenLedger worth paying attention to? Innovation of data ownership and incentive mechanisms Traditional AI models rely on unauthorized data collection, and the rights of contributors are ignored. OpenLedger uses blockchain to record data sources and usage, combined with smart contracts to achieve automatic profit sharing, solving industry pain points of data abuse and lack of incentives. For example, after an artist uploads their work to Datanets, if the AI model generates content that references their data, the revenue will be distributed proportionally. Efficient deployment of specialized models (SLM) Unlike general large-scale models such as GPT, OpenLedger focuses on vertical domain SLM and achieves parallel running of thousands of models on a single GPU through the lightweight framework OpenLoRA, reducing costs by 99%. This technological breakthrough enables small and medium-sized developers to participate in AI innovation, such as developing legal contract review or medical diagnostic specialized models. Anti Monopoly of Decentralized Networks Data and models are stored in decentralized global nodes to avoid the risk of single point control on centralized platforms such as OpenAI. For example, users can choose to store their data locally on a node and ensure privacy through encryption. Secure collaboration with EigenLayer By utilizing EigenLayer's re staking protocol (TVL exceeding $20 billion), OpenLedger enhances network security, ensuring data integrity and resistance to attacks, providing a trusted environment for highly sensitive areas such as finance and healthcare. Token Economics (OPN) Although the token economy model has not yet been fully disclosed, according to the testnet and whitepaper information, OPN tokens will undertake the following functions: Governance: Holders vote to decide on fund allocation, protocol upgrades, and other decisions. Payment and Incentives: Used to pay network gas fees and reward data contributors, node operators, and developers. Pledge and Security: AI agents need to pledge OPN to ensure service quality, and malicious behavior will result in confiscation. Potential risk: Details of token allocation (such as team and investor unlocking cycles) have not been disclosed, and early selling pressure should be monitored. Future planning and challenges Short term goal (2025) Main network launched, optimized OpenLoRA framework, supports deployment of multiple GPUs and edge devices. Expand the coverage of Datanets and attract enterprise partners (such as Sony and Wal Mart) to provide industry data. Long term vision Build an 'AI Agent Economy' where users can train and trade personalized AI assistants (such as investment advisors, language translation agents). Compared to the Web3 protocol (such as http://Ether.fi ）Deep integration enhances cross chain data interaction capabilities. challenge Data compliance: The use of data in sensitive areas such as healthcare must comply with regulations in multiple regions, which may limit ecological expansion. Intensifying competition: Spectral and similar projects are also targeting the decentralized AI data track, and OpenLedger needs to quickly establish technical barriers. Financing situation The seed round of $8 million funding will be used for technology research and ecological expansion, with a luxurious lineup of investors including Polychain, Borderless Capital, and several Web3 leaders (such as Balaji Srinivasan and Polygon co-founder Sandeep Nailwal), demonstrating market recognition. Financing and team background Team Highlights The core members include former Google DeepMind engineers who led the development of the data intelligence layer. The consulting team includes project founders such as EigenLayer and Polygon, providing technical and ecological resource support. Personal opinion: Opportunities and hidden worries coexist Track potential: The AI data infrastructure market is expected to reach $826 billion by 2030, and OpenLedger's permissionless model is expected to disrupt centralized platforms such as Scale AI. Early dividends: Testing the network's point mechanism or providing opportunities for airdrop ambushes, projects such as Grass have brought high returns to early participants. Hidden worries Technical complexity: The accuracy of attribution proof algorithms directly affects the fairness of profit sharing, and any deviation may lead to a crisis of community trust. Commercialization landing: SLM's vertical demand needs to be deeply tied to the industry, and it is difficult to see large-scale revenue in the short term. OpenLedger's innovation in data ownership and dedicated model tracks is forward-looking. Whether it can become a benchmark for the integration of Web3 and AI depends on the ecological activity and technological stability of the mainnet after its launch. For investors, it is recommended to participate in testing network tasks to accumulate potential airdrops at low cost, and continue to monitor their cooperation progress with traditional enterprises. Openledger Opnup @cookiedotfun