Nexсhain
  • πŸ™ŒOverview
  • πŸ“‚Introduction
  • 🎯Market Opportunity
    • πŸ’ͺBlockchain vs DAG
    • πŸ“ŠCompetitor Analysis
    • πŸ“ˆMarket Growth Potential
  • βš™οΈPlatform Features
    • πŸ”„Hybrid Consensus Mechanism
    • πŸ€–AI-Enhanced Smart Contracts
    • πŸ“ˆScalability and Interoperability
    • πŸ› οΈDeveloper Tools and Ecosystem
    • ♻️Energy Efficiency and Sustainability
    • πŸ”—Chain Abstraction
    • πŸ“Data Infrastructure
    • 🌐Web3 Apps
  • πŸ“±Applications
    • πŸ’ΈFinance
    • πŸ₯Healthcare
    • πŸ“¦Supply Chain Management
    • πŸ“‘Internet of Things (IoT)
    • 🧠Decentralized AI Services
    • πŸ›οΈGovernance
  • πŸ“ŠTokenomics
    • 🎁Token Distribution
    • βš–οΈGovernance and Utility
    • ⚑Presale stages
  • πŸ›‘οΈSecurity
  • πŸ—ΊοΈRoadmap
  • πŸ‘₯Team and Advisors
  • βœ…Conclusion
Powered by GitBook
On this page
  1. Applications

Decentralized AI Services

AI models require significant computational resources for training and inference, making decentralized AI services a natural application for Nexchain. Traditional AI platforms rely on centralized infrastructure, leading to concerns about data privacy, security, and censorship. Nexchain enables decentralized AI training and deployment through smart contracts that facilitate collaborative model development while preserving data sovereignty.

The platform supports distributed AI model training using federated learning, allowing multiple entities to contribute to model development without exposing raw data. AI-powered smart contracts automate model execution and parameter tuning, ensuring efficient inference across decentralized networks. By integrating cross-chain compatibility, Nexchain allows AI models to interact with multiple blockchain ecosystems, expanding their applicability across industries.

PreviousInternet of Things (IoT)NextGovernance

Last updated 2 months ago

πŸ“±
πŸ§