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Rachel, Bitchain Vision Realm
On November 27, Zhao Changpeng posted on X that the tasks such as AI data labeling are very suitable for completion through the blockchain. It can use the global low -cost labor and real -time payment through cryptocurrencies to break regional restrictions.
Data marking refers to the labeling of artificial or automation of original data (such as text, images, audio, etc.) to make it have specific structured information.The marked data is used to train machine learning or artificial intelligence models. For example, the textbook (positive, negative, neutral) is a data mark.The use of blockchain for artificial intelligence data is particularly suitable for data labeling scenarios that require high transparency, credibility and distributed collaboration.This can not only improve the efficiency and quality of data marking, but also create new possibilities for global collaboration and data transactions.
What are the high -quality projects in this track?What is the prospect of the track development?
The role of the blockchain in the AI data mark
Blockchain is a decentralized distributed ledger technology, which hasTransparencyAs well asNot tampered withandTraceabilityThe characteristics.These features can solve the following problems in the data mark:
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Data authenticity and tampering:Each mark of the mark is written into the blockchain and cannot be changed at will, ensuring the credibility of the marking.
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Mission distribution transparency:The blockchain can record the distribution, execution, and review process of tasks to prevent the task allocating unfairness or results tampering.
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Incentive mechanism:Using blockchain intelligent contract technology, data markers can automatically get cryptocurrencies or other rewards by completing the task.
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Data traceability:The source of each label, the marker, and the auditors can be tracked.
Application scenarios
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Distributed labeling:Use the blockchain to distribute the data marking tasks to the global marking staff, and the data processing efficiency is higher.
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Quality review:The result of multiplayer marking results through comparison and review through blockchain technology to ensure the accuracy of labeling.
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Mark data transaction:The labeled data can be traded on the blockchain, and the buyers and sellers do not need to worry about the integrity or authenticity of the data.
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Privacy protection:Use the blockchain to encrypt the marked data to ensure the security of privacy data.
Related projects
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OORT DATAHUB:Provide blockchain -based decentralized data labeling services, and use the Proof of Honesty algorithm for quality control.Its platforms have distributed tasks, review data quality, and paid compensation through intelligent contracts, attract global bids to join, and ensure the transparency and privacy protection of marked data.
The economic model of the project token is as follows:
Community reward: By participating in data marking and analysis, users can get the $ OORT token reward.In addition, it may also obtain a unique NFT linked to contributions. These NFTs provide additional equity, such as increasing the annual yield (APY) rewards, equipment discounts and DAO voting rights.
Mortgage: Participants need to mortgage at least 210 $ OORT tokens to show their commitments to the task. After completing the task, they will be returned to the token and issued rewards.
Sales income division: Some NFT holders can also divide them from future data sales revenue to further increase long -term returns.
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Publicai:The AI ecological project on the Solana chain aims to connect data demanders and global bidders to reward participants through cryptocurrency incentive mechanisms. At the same time, the details of the blockchain technical records are used to ensure data security and privacy.
The economic model of the project token is as follows:
Community rewards:10%PUBLIC tokens will be used for airdrop rewards for users in the early stage. SpecificallyThree types,Become AI Builder: Collect high -quality Internet content;Become AI Validator: Verify and collect; become AI Developer: Use verified data sets to train AI proxy.
Token distributionTheThe project completed the seed wheel financing of $ 2 million in January 2024. Investors include IOBC Capital, ForeSight Ventures, Solana Foundation, Evertate Capital and a number of well -known academician professors in the artificial intelligence.clear.
Challenge
At present, several major factors are bound to the development of the track: one is that the AI data mark requires higher calculation and storage resources; the second is that the project performance is subject to the scalability of the blockchain; the third is that the technical standardization and supervision are not yet complete.
Among them, the second point may be the biggest challenge facing.Because AI data marks and model training usually require a large amount of computing resources, and the node computing power in the blockchain network is limited.How to effectively integrate and use distributed computing resources on the premise of ensuring the centralized characteristics of the blockchain to meet the calculation needs of the AI data label project is an urgent problem.It is reported that Greenfield, a subsidiary of Binance is providing storage support for this track, looking forward to more storage and computing resources in this field.
