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AI Connect Whitepaper
  • Project Introduction
  • 1. Project Background and Vision
  • 2. Introduction to Computing Power Networks
    • 2.1 Data as a New Factor of Production, Giving Rise to Computing Power Networks
    • 2.2 The Current Distribution of Computing Power Supply and Demand Shows Decentralized and Unbalanced
    • 2.3 The Metaverse Era, Where New Technologies Like VR and AR Are Closely Related to High Bandwidth a
    • 2.4 Computing Power Networks Refer to the Integration of Cloud, Network, and Edge for Unified Comput
    • 2.5 Computing Power Networks Build the Network Foundation for the Development of the Metaverse
  • 3. Market Demand for the Development of Computing Power Networks
    • 3.1 The AI Wave Boosts Computing Power Demand, and Achieving Scalability of Intelligent Technology R
    • 3.2 Industry Applications of Large Model Training Also Require a Large Amount of Intelligent Computi
    • 3.3 The AI Application Has a Long Tail Effect, and Achieving Scalability Requires First Achieving Un
  • 4. AIConnect Computing Power Network Construction Plan
    • 4.1 Computing Power Supply Services
    • 4.2 The Infrastructure and Marketization of Computing Power Scheduling
    • 4.3 The Commercial Demand for Computing Power Scheduling
  • 5. Global Development of Computing Power Networks and DePIN
    • 5.1 Development Advantages of DePIN Combined with AI and Crypto
    • 5.2 AIConnect's Investment in AI Edge Computing Model Training and Development
  • 6. Joint Construction and Participation in AIConnect's Computing Power Network
    • 6.1 Introduction to the Role of AIC Token Assets in AIConnect
    • 6.2 Design Advantages of AIC Tokens
    • 6.3 Introduction to the Business Model of AIC Tokens
      • 6.3.1 AIC Token Production
      • 6.3.2 Node Participation
  • 7. Development Roadmap
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  1. 3. Market Demand for the Development of Computing Power Networks

3.3 The AI Application Has a Long Tail Effect, and Achieving Scalability Requires First Achieving Un

AIGC has brought about an explosion in the artificial intelligence industry, and the scaled application of intelligent technology has a typical long tail problem. That is, powerful departments with strong AI capabilities (such as cybersecurity, research institutes, and meteorological bureaus), as well as research institutions and large and medium-sized enterprises, only account for about 20% of the main body of computing power demand. The remaining 80% are small and medium-sized enterprises (SMEs), which are often limited by company size and budget. They often find it difficult to access computing power resources or are constrained by the high cost of computing power, making it hard for them to benefit from the AI era. Therefore, to achieve the scaled application of intelligent technology and make the AI industry both popular and profitable, there is a need for a large amount of affordable and easy-to-use intelligent computing power, allowing SMEs to use computing power conveniently and affordably. Thus, achieving universal access to computing power can support the development of advanced technology, empower more industries with AI, and also bring AI into every household, achieving AI for all.

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Last updated 1 year ago