AI "Data Staking": Masa Network Launches New Train AI to Earn Model
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AI "Data Staking": Masa Network Launches New Train AI to Earn Model
Masa aims to bring billions of users into the AI data economy through its innovative AI pricing model.
Navigating Web3 tides with focused insightsAuthor: Masa
Translation: Paimeng, Foresight News
Introduction
In the era of artificial intelligence, data has become the world's most valuable commodity. The datasets most valuable to AI typically originate from the daily digital lives of billions of users—browsing the internet, engaging on social platforms, and other online activities.
For years, large technology companies have been "abusing" user data, and the rise of AI has only intensified this issue. Today’s widely adopted generative AI models require vast amounts of data for personalized training. To obtain effective datasets, AI companies are scraping user data from open web sources and social platforms through various means. In essence, this constitutes "stealing" the private data of users worldwide.
At the same time, most tech companies have generated billions—or even trillions—of dollars in value by training AI models on user data, without sharing any economic benefits with the users themselves. Users have effectively been stripped of control over their personal data, their privacy, and their right to fair compensation.
Masa aims to fundamentally transform how users benefit from the AI boom—by monetizing their digital "footprints" while protecting their privacy, thereby providing them with fair compensation. This article will delve into Masa’s revolutionary AI pricing model, which enables billions of users to participate in the AI data economy.
AI Data Staking: Earning Rewards for AI Training
Masa runs in the background, collecting users’ digital footprints left behind through activities such as reading emails, browsing social platforms, visiting websites, and interacting with the digital world, while ensuring these traces remain private and secure within a personal database using zkSBTs (Zero-Knowledge Soulbound Tokens).
Users simply need to open the Masa App, view their data on the Masa Network, assess its value, and choose different liquidity pools to stake it—all to earn rewards. The specific methods are as follows:
Providing Data to Masa Network
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Quest to Earn: Participate in specific activities or tasks to contribute data—such as joining Discord groups, taking part in trading competitions, or training AI models—and complete data staking to earn rewards in the Masa App.
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Surf to Earn: Use the Masa extension on Chrome to browse the web and earn rewards. This extension autonomously captures valuable data points and stores them securely in a private database.
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Nodes-to-Earn: Users and node operators automatically serve as distributed data collection nodes via the Masa Chrome extension and Masa Data Oracle, acquiring public and private data with low technical barriers and receiving network incentives.
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Passive Rewards: Masa’s ecosystem partners can use the Masa SDK to aggregate data and observe communities, enabling users to earn passive rewards from data aggregated through Masa’s ecosystem partners.
Data Tokenization
Masa uses a points system to quantify the value of users’ data within the Masa Network. After the launch of the Masa mainnet on April 11, users will be able to directly view their accumulated data points in the Masa App.
Users can then stake their data in designated pools to earn rewards. Developers within the Masa ecosystem will create various staking pools that reward contributions across different data dimensions—for example, developers of AI trading bots may prioritize rewarding users who contribute wallet interaction data.
Empowering Hyper-Personalized AI Use Cases Through Data Contribution
By rewarding users for staking their data, Masa powers AI applications and opens the door to broad innovation. Masa firmly believes that future AI models will understand users better than they understand themselves—a vision built upon users voluntarily opening their personal datasets for AI training and optimization. For example:
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AI for Cryptocurrency Market Prediction: By providing developers with real-time datasets covering user browsing history, social sentiment, and on-chain interactions, Masa equips AI with market insights to identify cryptocurrency trends, uncover investment opportunities, and generate more accurate price forecasts.
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AI for NFT Management: Masa’s network data oracle feeds structured data on the latest NFT market trends and community sentiment into AI systems, enhancing AI-powered NFT management tools to develop and evaluate more effective trading strategies.
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AI for Political Prediction: Masa’s diverse data—including social sentiment, civic engagement metrics, and link click-through rates—could even be used to effectively predict voter sentiment in presidential elections.
Conclusion
Masa firmly believes that users have the right to reap economic benefits from the rapid development of AI. Therefore, Masa offers a new paradigm that allows users to train AI models with their personal data while safeguarding their privacy and control.
By participating in the Masa ecosystem, users can not only effectively protect their digital footprints but also contribute to the data economy in a fairer and more transparent way. As AI rapidly advances, human data contributors and AI developers will collaborate through platforms like Masa to fully unlock the potential of the AI data economy—ensuring that every click, search, and interaction generates greater value.
The era of the AI data economy is approaching. The Masa Network mainnet and token are set to launch around April 11—participants should get ready.
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