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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. Technical Designs
  2. Additional Information

The AI Kernel Market

The Nesa team envisions a future where AI models become so critical to daily life that they assume the role and level of importance of today’s mobile app ecosystem, like those on operating systems like Google and Apple, where they are sellable and monetizable in an open marketplace.

OpenAI’s marketplace of GPTs operates on OpenAI’s private model, closed off to the public, meaning a model that is off-chain and not connected to any decentralized environment, and customizable only via OpenAI’s black box fine-tuning. The work invested into careful fine-tuning and model update provenance can evaporate overnight under such a setup. This is the inherent danger of centralization and AI.

The future that we envision is an AI Kernel Marketplace where containerized AI’s on the Nesa could be browsed through, reviewed, piloted, and purchased in an instant to handle any task that a user requires. Nesa wants to give freedom and complete flexibility to creators who want to own, monetize, and control their AI evolution. Each container in the Kernel Market would be fully customized, controlled, updated, and managed by its owner.

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Last updated 1 year ago