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Last updated
Last updated
DataTalk is a decentralized artificial intelligence data annotation platform for annotating text and image.We redefine the paradigm of data annotation and build a trusted data foundation layer for decentralized AI. DataTalk decentralizes the annotation process for text, images, videos, and audio, and enhances labeling efficiency and accuracy by integrating manual labeling with AI-driven pre-labeling techniques, providing high-quality labeled data for AI model training.
DataCollect is a collect data to earn product, we allow users collect data from public internet or collect from real world and. Users can also pre-label the collected online or offline data through DataTalk, or trade the collected data directly on DataBazaar. If other users pruchase for the data, users will get both payment from AI entity and DeData platfrom token emission rewards
DataBazaar is a marketplace for trading AI training data, allowing any organization or individual to exchange high quality labeled or raw data for compensation. These datasets are traded as NFTs, and anyone who obtains ownership of the data can use it to train AI models.
DataEngine is a data pre-labeling system based on open source models. It pre-processes data labels through AI models to improve the efficiency of manual data labeling.
Union NFT is a collection of non-fungible tokens designed for union leaders to form teams and undertake more specialized and confidential tasks from AI companies. Union NFTs are limited in number, with only one NFT mintable per wallet address. Union Node needs to stake a certain amount of assets, taking on the responsibility of efficiently completing high-value annotation tasks, and in return, they will receive dividend rights from Union Group. Union Node will become a contributor and guardian of Union Group.
The main mechanism of Dedata is "label to earn." Users receive dual rewards of tokens and project funds for their data annotation efforts. The platform's proprietary reward and penalty algorithm, along with a risk control engine, incentivizes high-quality annotations while mitigating the risk of malicious users submitting incorrect data. Dedata intelligently calculates project rewards based on users' annotation behavior, ensuring that high-quality users maximize their earnings.
We can tailor data collection tasks based on customer needs, incentivizing users to gather data and earn dual rewards from both the project and the DeData platform.
For example, if a customer needs to analyze the sentiment of Twitter user comments web3 users can mention the platform in relevant comments. The project will then collect and pre-verify this data. Verified data will be used for manual annotation, ensuring accuracy and reliability.
This approach not only meets customer requirements but also engages a broader user base in meaningful data collection, enhancing the overall quality of AI training datasets.
