Insight Distribution Layer
The Insight Distribution Layer is the key interface for releasing the value generated by the AI models. It is responsible for delivering analysis results to different types of users with precision and efficiency. This system not only provides understandable and actionable strategic recommendations but also enables task-driven services and contributor rewards, completing the full loop of AI training → value generation → feedback distribution.
This module focuses on three core functions:
AI-Driven Recommendation Outputs
Using structured insights generated by the semantic engine, the platform delivers highly targeted and actionable recommendations, including:
Content Optimization Suggestions: For content creators, the system provides language style improvements and structural adjustment advice to enhance readability and shareability.
Trend Forecasting: Pushes real-time insights on the popularity trajectory of projects/topics in the Web3 community, predicting potential market movements and narrative momentum.
Behavioral Prompts: Based on user profiles and market data, the system offers clear action signals such as whether to follow, engage, or avoid specific projects or topics.
Task-Based Intelligent Services
The platform features standardized “Information-as-a-Service” modules that users can subscribe to, such as:
Daily Airdrop Rankings: Automatically aggregates verified airdrop information from social semantics, ranking them daily based on trust level, participation barrier, and potential returns.
Customized Alpha Signals: Based on user-preferred sectors and interaction history, the system smartly identifies Alpha project signals aligned with individual interests.
Opinion Comparison Summaries: Compiles and contrasts views from KOLs, project teams, and researchers into concise visual summaries, saving users time in evaluating divergent perspectives.
Narrative Radar Alerts: When specific narratives (e.g., Modular L2, DePIN, AI+Crypto) heat up rapidly, users receive proactive alerts on related projects, key messages, and leading sources.
Incentive Mechanism for Content Contributors
To encourage the submission of high-quality social content, the platform implements a feedback-based incentive system. When user-contributed content is repeatedly referenced, analyzed, or used by the AI to generate recommendations for others, the contributor receives token rewards. Key mechanisms include:
Usage Tracking: The system records how often a piece of content is analyzed, cited, or recombined by the model—serving as a metric of value.
Training Value Scoring: Each submission is evaluated based on factors like semantic uniqueness, emotional diversity, and structural clarity to determine its training value.
Incentive Distribution: Smart contracts automatically issue rewards in the form of $SOCIAL (the native protocol token) or $BRAIN (training credits), with no need for manual claims—rewards are delivered directly to the contributor’s wallet.
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