We're thrilled to announce a major upgrade to the PURSE+ SocialFi browser plugin – welcome to PURSE+ SocialAI! This revolutionary concept marries the essence of SocialFi with the power of Artificial Intelligence, all happening seamlessly on X.com (formerly Twitter). As the first of its kind, PURSE+ SocialAI allows participants to contribute, collaborate, and produce valuable social data that fuels AI and machine learning, while earning real-world rewards.
PURSE+ SocialAI is an innovative browser plugin that takes the SocialFi experience to the next level by integrating AI capabilities into the heart of social interaction. Users can now actively participate in the tagging and labeling of tweets on X.com, contributing to the development of AI datasets. This process not only enhances AI learning but also offers participants the opportunity to earn FUGU points, which can later be converted into tokens for real-world use and spending.
Gamified Data Labeling
PURSE+ SocialAI introduces an easy-to-use, gamified tool where users can engage in various tasks such as analyzing tweet sentiments, categorizing topics, and tagging important entities within tweets. Each task completed helps to build and refine the AI dataset, making it more intelligent and effective.
Earn While You Contribute
By completing these tasks, users earn FUGU points, which function as a point system that enables the redemption of tokens, such as $PURSE, $FX, and others in the near future. This means you can turn your efforts into tangible rewards, allowing you to earn extra money for your time spent on social media or by contributing to the advancement of AI. Whether you're casually engaging in the platform or actively participating in the growth of AI, every task you complete brings you closer to real-world benefits.
AI-Driven Sentiment Analysis
One of the core functionalities of PURSE+ SocialAI is sentiment analysis. Users are invited to analyze tweets, determining the general sentiment and providing feedback that contributes to a broader AI learning process. This data is crucial for improving AI-driven content analysis and prediction models.