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  • Nesa Docs
    • Introduction to Nesa
    • Overview of the Nesa System
      • AI Models: Repository, Standardization, Uniformity
      • Users: Why Do We Need Private Inference?
      • Node Runners: Doing Inference and Earning $NES
    • Organization of the Documentation
  • Technical Designs
    • Decentralized Inference
      • Overview
      • Model Partitioning and Deep Network Sharding
      • Dynamic Sharding of Arbitrary Neural Networks
      • Cache Optimization to Enhance Efficiency
      • BSNS with Parameter-efficient Fine-tuning via Adapters
      • Enhanced MTPP Slicing of Topological Order
      • Swarm Topology
      • Additional: Free-Riding Prevention
    • Security and Privacy
      • Overview
      • Hardware Side: Trusted Execution Environments (TEEs)
      • Software/algorithm Side: Model Verification
        • Zero-knowledge Machine Learning (ZKML)
        • Consensus-based Distribution Verification (CDV)
      • Software/algorithm Side: Data Encryption
        • Visioning: Homomorphic Encryption
        • Implementation: Split Learning (HE)
      • Additional Info
        • Additional Info: Trusted Execution Environments (TEEs)
        • Additional Info: Software-based Approaches
    • Overview of $NES
      • $NES Utility
    • The First Application on Nesa: DNA X
    • Definitions
    • Additional Information
      • Dynamic Model Versioning and Fork Management
      • Nesa's Utility Suite
      • The AI Kernel Market
      • Privacy Technology
        • Trusted Execution Environment (TEE)
        • Secure Multi-Party Computation (MPC)
        • Verifiable Random Function (VRF)
        • Zero-Knowledge Proof (ZKP)
      • The Integration of Evolutionary AI to Evolve the Nesa Ecosystem
      • Interoperability and Nesa Future Plans
  • Using Nesa
    • Getting Started
      • Wallet Setup
      • Testnet Nesa Faucet
    • Via Web
      • Your Nesa Account
      • Selecting an AI Kernel
      • Submitting a Query
    • Via SDK
    • Via IBC
    • Via NESBridge
      • On Sei
  • Run a Nesa Node
    • Prerequisites
    • Installation
    • Troubleshooting
    • FAQ
  • Links
    • nesa.ai
    • Nesa Discord
    • Nesa Twitter
    • Nesa dApp: dnax.ai
    • Nesa dApp: DNA X Docs
    • Terms of Service
    • Privacy Policy
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  1. Nesa Docs

Organization of the Documentation

PreviousNode Runners: Doing Inference and Earning $NESNextDecentralized Inference

Last updated 12 months ago

The documentation is organized into three parts

The is centered around the technology innovations around Nesa:

  • : In this section, we outline the design of Nesa's decentralized inference framework, including how to split large AI models into small pieces for distributed inference.

  • : In this section, we describe our security and privacy measures to protect user data and privacy. The key techniques include zero-knowledge proof ML, split learning, and more

  • : To use Nesa for AI model inference, rollup developers submit PayForQuery transactions on the network for a fee denominated in $NES.

  • : DNA X describes the first decentralized application on the network, focused on autonomous personality agents on-chain.

  • provide terminologies and technical definitions of the system

  • Additional Information provides additional details about our technical designs.

The of the documentation describes how to use Nesa:

  • shows how to set up the wallet and Nesa faucet for the testnet

  • describes how to interact with Nesa Chain via the web

  • describes how to interact with Nesa Chain via the official SDK

  • describes how to interact with Nesa Chain via IBC

  • describes how to interact with Nesa Chain via Nesa CCI

The documentation concludes with useful links, including our website, discord, X, etc.

first part
Decentralized Inference
Security and Privacy
Overview of $NES
The First Application on Nesa
Definitions
second part
Getting Started
Via Web
Via SDK
Via IBC
Via Nesa CCI