AIRTIST
  • GETTING STARTED
    • Welcome
    • Official Links
    • Background
    • What is AIRTIST?
      • Why AIRTIST?
  • AIRTIST ECOSYSTEM
    • Outline
    • Inception
      • Creation of MASTER
      • Creation of the MAESTRO
      • Storage of DNN and Minting of the NFT
    • Manifestation
    • Proliferation
    • Other Technical Features
  • OVERALL CONSIDERATION
    • Why Blockchain?
    • Why MATRIX?
    • Why Ethereum?
      • Why Fractional NFT
    • AIRTIST as a Decentralised Ecosystem
      • Distributed Training
      • Distributed computing
      • Distributed storage
  • TOKENOMICS
    • AIRT Token
    • Token Distribution
    • Token Release Schedule and Rules for the Ecosystem
    • AIRT Mining
    • Utility of AIRTs
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  1. AIRTIST ECOSYSTEM

Other Technical Features

AIRTIST can be enhanced in the future to incorporate automatic machine learning (AutoML) capabilities. AutoML aims to automate the design and training of DNNs and other AI models. The basic idea is to use a certain encoding to capture the overall solution space of DNNs and then search for a solution in the space to best meet a given objective.

As an exhaustive traversal of the solution space is infeasible, adopting an efficient search algorithm like reinforcement learning or evolutionary algorithm is essential. AutoML can generate high-quality models at the cost of intensive computation.

With AutoML, AIRTIST can be constructed through automatic design and optimisation by leveraging the distributed computing network. Such an approach revolutionises the process of building MASTER/MAESTRO by allowing users without AI backgrounds to participate in the ecosystem.

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Last updated 2 years ago