Decentralized Machine Learning

Unleash untapped private data, idle processing power and crowdsourced algorithms

The DML Infrastructure


On-Device Machine Learning without Data Extraction

Utilize untapped private data in individual devices for machine learning with privacy protected

Unleash Innovation from Periphery

Unlock innovation by creating a developer community and competitions in algorithm marketplace

Connect Idle Processing Power of Billions Devices

Leverage processing power of all connected devices for running machine learning algorithms

Mass Participation in Machine Learning Training

Create an algorithm trainer community to improve algorithms through collective efforts

Multi-Blockchain Adoption and Interoperability

Communicate across multi-chains to achieve blockchain-agnostic protocol

Return Power to Ecosystem Owners

Avoid centralization and control by a few oligopolies via blockchain and tokenization

How DML Works



DML infrastructure will apply on-device machine learning, blockchain and federated learning technologies. It unleashes untapped data usage without extraction and idle processing power for machine learning. Algorithms will be crowdsourced from a developer community through the marketplace resulting innovation from periphery.



DML Workflow


DML Prototype Demo




Key Features of DML Prototype:

  • Searching, requesting and listing for machine learning algorithms in DML Algo Marketplace;
  • Creation of machine learning application requests and selection of relevant individual device owners for private data access;
  • Deployment of machine learning algorithms into smart devices;
  • Running of the machine learning algorithms with idle processing power in the DML App;
  • Submission of machine learning results (and raw data remains within the devices) from the DML App;
  • Generation of aggregated machine learning prediction analytics reports;
  • Smart contract transactions in DML Tokens for machine learning models.

Token Distribution



Total Token Supply: 272,937,007 DML (to the nearest integer)

Use of Proceeds






Partners and Contributors


Roadmap


  • Feb 2016

    Google published the research paper on federated learning

  • Mar 2016

    AlphaGo beat Lee Sedol in Go

  • Mar 2017

    Idea generation of decentralization in machine learning

  • Apr 2017

    Google published research blog in federated learning

  • May 2017

    Development of proof of concept

  • Sep 2017

    Idea generation of decentralization in algorithms

  • Dec 2017

    Whitepaper published and DecentralizedML.com online

  • Feb 2018

    Release of DML Protocol Gen 0 (DML Algo Marketplace) Prototype

  • Apr 2018

    Token Generation Event and Launch of DML Protocol Gen 0 (DML Algo Marketplace) Beta

  • Apr-May 2018

    DML Algo Marketplace online

  • Jun-Jul 2018

    Release of DML Protocol Gen 1 alpha (decentralized machine learning on-device private data)

  • Jun 2018

    Research of state channels for increasing DML scalability

  • Jul-Aug 2018

    First DML Algo competition to grow and support developers’ community

  • Jul-Aug 2018

    Release of DML Protocol Gen 1 beta

  • Sep 2018

    DML Protocol Gen 1 online

  • Dec 2018

    Release of customized state channels for increasing DML scalability

  • Q1 2019

    Release of DML Protocol Gen 2 beta (decentralized machine learning on-device private data with third-party service and data access)

  • Q1 2019

    Research of multi-chain support and interoperability

  • Q2 2019

    DML Protocol Gen 2 online

  • Jul-Aug 2019

    Release of DML Protocol Gen 3 beta (decentralized machine learning on-device private data with third-party service and data access and mobile sensors/ IoT connection capability)

  • Sep-Oct 2019

    DML Protocol Gen 3 online

  • Q4 2019

    Research of general purpose API start for expanding usage of DML marketplace from machine learning to general applications

  • Q1 2020

    Research of new blockchain supporting mass adaption of general purpose decentralized applications and data privacy

  • Q2-Q3 2020

    Release of DML Protocol Gen 4 beta (Support deployment of general applications)

  • Q4 2020

    DML Protocol Gen 4 online

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