Grafilab
  • Getting Started
  • Whitepaper
    • Introduction
    • Market Overview
    • Challenges
    • Goal
    • What Are We Building?
    • Grafi Cloud
      • Core Features
      • How It Works
      • Payment and Incentives
      • Advanced Features
    • Grafi Co-Builder
      • Main Services of Co-Builder
      • How It Works
      • Supporting Large-Language-Model
      • Supporting Framework
    • Grafi AI App Store
      • Key Features of the Grafi AI App Store
    • Grafi AI Data Layer
      • Key Components of the Data Layer
      • How the Data Layer Works
    • Ecosystem (Flywheel)
      • Revenue Streams of Grafilab
      • Grafi's Universal Payment and Burning Mechanism
    • Token Info
      • Token Distribution and Allocations
      • Token Utility
      • Token Emission
  • Roadmap
Powered by GitBook
On this page
  1. Whitepaper

Challenges

As the global AI industry is projected to grow to $1.81 trillion by 2030, the path to achieving Artificial General Intelligence (AGI) faces significant challenges:

AI Commercialization: AI models need an App Store to reach users and generate revenue. Grafi AI App Store provides a seamless AI-as-a-Service (AIaaS) platform for developers to monetize their work.

Barriers for Developers: Small teams and startups face high costs and limited access to tools. Our AI Co-Builder lets anyone build, deploy, and scale AI models using fractional GPUs.

Insufficient Compute Power: The existing infrastructure can’t keep up with the demand for AI. Our CeDePIN Cloud solves this by offering scalable, cost-effective compute resources.

Data Integrity, Ownership & Security: Data ownership and model integrity are critical. Our AI Data Layer ensures tamper-proof, verifiable records of AI development on-chain, protecting data rights and usage.

PreviousMarket OverviewNextGoal

Last updated 2 months ago