DGPT Docs
  • πŸ¦Ήβ€β™‚οΈOverview
  • πŸ“–Introduction
  • Product Overview
    • πŸ“ͺObjectives and vision of the APP
    • πŸ“²Core functions and features
    • πŸ’°How to make money from AI arithmetic at DGPT
    • πŸ†DGPT Innovative Blockchain Core Business Model
    • πŸ₯³DGPT delivers new value in three ways
    • πŸ—ΏDGPT's proven and sophisticated business model
  • Project background
    • πŸŒ•Company Background
    • πŸ•ΈοΈAI Server Evolution and Parallelism
    • πŸ›€οΈAI Arithmetic Proliferation under ChatGPT's Demand
    • βœ…Computational power as a core production factor
    • ♻️Blockchain fuelling sustainable earning ecosystems
  • Product architecture
    • 🎨Calculation Platform
    • πŸ§‘β€πŸ«Core mechanism - distributed heterogeneous arithmetic infrastructure
    • πŸ§‘β€βš–οΈCalculation Node Platform
    • βš–οΈQuantitative Income Platform
    • 🌏Overview of AI techniques applied to DGPT
  • Calculation of proceeds
    • πŸ“ˆCalculation Power Settlement Formula
  • Token economics
    • πŸ™Œ (Coming Soon)
  • Summary
    • 🌐Summary
  • Link
    • πŸ–₯️Website
    • πŸ˜€Twitter
    • πŸ“”Medium
    • πŸ“ΊYoutube
    • πŸ—£οΈFacebook
    • πŸ“ΉTiktok
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  • Background and problem statement
  • Importance and value of the solution

Introduction

Unleash the idle arithmetic of everyday devices-earn the future of AI power

Background and problem statement

With the continuous development of Artificial Intelligence AI, we are currently in an era where there is a surge in the demand for models. In this era, the emergence of the ChatGPT Large Language Model (LLM) has revolutionised the technology landscape. Within this technology model architecture, the training of large numbers of AI-based models typically requires significant computational resources and time. To meet these demands, the GPU, a high-performance computational accelerator, has become an important tool for AI computation. For AI companies, the cost of affording a large amount of professional-grade NVIDIA A100 or equivalent GPU power is too high, and the lack of GPU power also leads to an oversupply of GPU resources from cloud service providers, which raises the cost of cloud services or limits the number of GPU resources available to users. And when GPU arithmetic is insufficient, training tasks take longer to complete, which directly slows down model iteration and innovation.Insufficient GPU arithmetic directly restricts the development of some large-scale and complex AI research and innovation projects. For example, in areas such as natural language processing, image generation, and reinforcement learning, greater computing power can support more complex models and algorithms, which makes computing resources extremely valuable.

Importance and value of the solution

The lack of GPU arithmetic directly leads to an oversupply of GPU resource devices from cloud service providers, which raises the cost of cloud services or limits the number of GPU resources available to users. For AI companies, the cost of affording tens of thousands of NVIDIA A100s is too high, and they have to look for various optimisation methods in order to run large models. Against this backdrop of heavy GPU capacity constraints, the DGPT "Idle Computing Power Rental and Revenue Platform" was born, which is an innovative platform designed to make full use of the idle computing power of dispersed devices of individuals and enterprises, and help them earn revenue by renting out idle computing power.

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Last updated 1 year ago

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