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Decentralized Machine Learning (DML) ICO

ICO
Past
Feb 08, 2018 – Apr 12, 2018

Decentralized Machine Learning aims to create a blockchain-based decentralized machine learning protocol and ecosystem.

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Decentralized Machine Learning (DML) ICO ratings

ICObench.com Decentralized Machine Learning (DML) icobench 2.5 / 5
ICOmarks.com Decentralized Machine Learning (DML) icomarks NA
TrackICO.io Decentralized Machine Learning (DML) trackico 4.6 / 5
ICOholder.com Decentralized Machine Learning (DML) icoholder NA
Our rating
7.1
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Overview

Project industry Other
Product type Platform

What is Decentralized Machine Learning

Mission Statement

Our goal is to create a blockchain-based decentralized machine learning protocol and ecosystem through:

  • utilizing untapped private data for machine learning while protecting data privacy,
  • connecting and leveraging idle processing power of individual devices for machine learning,
  • encouraging involvement from the periphery by creating a developer community and algorithm marketplace that promotes innovation to build machine learning algorithms that match practical utilities,
  • improving and correcting existing machine learning algorithms and models through crowdsourced fine-tuning model trainers,
  • creating a new DML utility token and leveraging on blockchain smart contract technology to provide a trustless and middle-man free platform that connects potential contributors in machine learning from all aspects.
  • We aim to create a decentralized machine learning protocol and ecosystem, where customers, such corporate customers, research institutions, government and non-government organizations or even individuals, who wish to run analytical predictions can acquire appropriate algorithms from crowdsourced developers through the DML marketplace. With the aid of DML protocol, the machine learning algorithms can be run on the untapped private data and leverage the idle processing power of individual devices resulting in more precise predictions. Furthermore, the developers can improve their algorithm and its predictability by the crowdsourced model trainers in the DML protocol.

    Details

    Public sales: Feb 08, 2018 - Apr 12, 2018
    Token supply: 272,937,007 DML
    Raised: 10,425,492 USD

    Legal

    Blockchain Platform: Ethereum
    Country limitations: China, Hong Kong, Singapore, Taiwan, United States

    Token info

    Ticker: DML
    Type: Utility-token
    Token standard: ERC-20
    Token price in USD: 1 DML = 0.170000 USD
    Accepted currencies: ETH
    Token distribution:
    36% - Sale
    19.5% - Team. Advisors & Early Contributors
    15% - Reserves
    9.9% - Ecosystem Bonus for Public Contributors
    8.8% - Strategic Business & Research Partners
    8.3% - Debug, Development & Protocol Upgrade Bonus for Developer Community
    2.5% - PR & Marketing Partners
    Funds allocation:
    50% - Project Development
    15% - Marketing & Community Building
    12.5% - Research
    11.1% - Business Development
    8.1% - Operation & Reserves
    3.3% - Legal & Compliance

    Decentralized Machine Learning Roadmap

    1
    February 2016

    Google published the research paper on federated learning

    2
    March 2016

    AlphaGo beat Lee Sedol in Go

    3
    March 2017

    Idea generation of decentralization in machine learning

    4
    April 2017

    Google published research blog in federated learning

    5
    May 2017

    Development of proof of concept

    6
    September 2017

    Idea generation of decentralization in algorithms

    7
    December 2017

    Whitepaper published and DecentralizedML.com online

    8
    February 2018

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

    9
    April 2018

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

    10
    May 2018

    DML Algo Marketplace online

    11
    June 2018

    Release of DML Protocol Gen 1 alpha (decentralized machine learning on-device private data)
    Research of state channels for increasing DML scalability

    12
    July 2018

    First DML Algo competition to grow and support developers’ community
    Release of DML Protocol Gen 1 beta

    13
    September 2018

    DML Protocol Gen 1 online

    14
    December 2018

    Release of customized state channels for increasing DML scalability

    15
    Q1 2019

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

    16
    Q2 2019

    DML Protocol Gen 2 online

    17
    July 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)

    18
    September 2019

    DML Protocol Gen 3 online

    19
    Q4 2019

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

    20
    Q1 2020

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

    21
    Q2 2020

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

    22
    Q4 2020

    DML Protocol Gen 4 online

    Project team

    Victor Cheung
    Victor Cheung
    Blockchain Developer
    linkedin
    Michael Kwok
    Michael Kwok
    Project Lead Director
    linkedin
    Jacky Chan
    Jacky Chan
    Blockchain and Software Developer
    linkedin
    Wilson Lau
    Wilson Lau
    Machine Learning Engineer
    linkedin
    Patrick Sum
    Patrick Sum
    System Security Engineer
    linkedin

    Advisors

    Pascal Lejolif
    Pascal Lejolif
    linkedin
    Guillaume Huet
    Guillaume Huet
    linkedin
    Michael Edesess
    Michael Edesess
    linkedin
    Roderik van der Graaf
    Roderik van der Graaf
    linkedin
    Kyle Wong
    Kyle Wong
    linkedin
    Scott Christensen
    Scott Christensen
    linkedin
    Steven Cody Reynolds
    Steven Cody Reynolds
    linkedin
    Matthew Slipper
    Matthew Slipper
    linkedin
    Jesmer Wong
    Jesmer Wong
    linkedin
    Eugene Tay
    Eugene Tay
    linkedin
    Eric Byron
    Eric Byron
    linkedin
    Fabrice Fischer
    Fabrice Fischer
    linkedin

    Social media

    Web-site Reddit: Decentralized Machine Learning (DML) Medium: Decentralized Machine Learning (DML) YouTube: Decentralized Machine Learning (DML) Telegram: Decentralized Machine Learning (DML) Twitter: Decentralized Machine Learning (DML) Facebook: Decentralized Machine Learning (DML) Github: Decentralized Machine Learning (DML)

    User rating:

    5/5 ( 1 )

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