DIN: Data Intelligence Network
  • Data Intelligence Network - The Blockchain for AI
    • Overview
    • Purpose and scope of this whitepaper
  • Market and Trend Analysis
    • Overview of the current data trend and market
    • Overview of the current AI trend and market
    • Existing gaps and opportunities in the market
  • Data Layer: All for the Data
    • Data Flow of AI
    • DIN Protocol Architecture
    • Data Collection
    • Data Validation
    • Data Vectorization
    • The Reward Mechnism
  • Service Layer - Toolkit for dAI-Apps
    • LLMOps
    • RAG (Retrieval Augmented Generation)
      • Hybrid Search
      • Rerank
      • Retrieval
    • Annotation Reply
  • Application Layer: The Ecosystem and Product
    • Analytix
    • xData
    • Reiki
  • Tokenomics and Utilities
    • Details about the $DIN Token.
    • Use cases for the token within the ecosystem
  • Future Outlook
    • Roadmap in 2024
    • Future Developments of DIN
      • Data Marketplace
      • The Multi-Agent system(MAS)
  • References
    • Citations and Sources
    • Glossary of Terms
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Data Layer: All for the Data

PreviousExisting gaps and opportunities in the marketNextData Flow of AI

Last updated 1 year ago

"Every data scientist should spend 80% of their time on data pre-processing and 20% on performing the analysis."

As shown in Fig 1. , data plays a very important role in the whole AI workflow and is fundamental to AI blockchain—all dAI apps rely on high-quality data. We design and implement the DIN protocol to guarantee the network can obtain high-quality data by adopting an incentivized mechanism.

This chapter will explain how the DIN protocol works for the network participants and how they can be rewarded for participating in the data activity.

Fig 1. AI workflow