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Decentralized Machine Learning

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

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

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

2020
DML Protocol Gen 4 online<br />
<br />
2020
Release of DML Protocol Gen 4 beta (Support deployment of general applications)<br />
<br />
2020
Research of new blockchain supporting mass adaption of general purpose decentralized applications and data privacy<br />
<br />
2019
Research of general purpose API start for expanding usage of DML marketplace from machine learning to general applications<br />
<br />
2019
DML Protocol Gen 3 online<br />
<br />
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)<br />
<br />
2019
DML Protocol Gen 2 online<br />
<br />
2019
Release of DML Protocol Gen 2 beta (decentralized machine learning on-device private data with third-party service and data access)<br />
Research of multi-chain support and interoperability<br />
<br />
2018
Release of customized state channels for increasing DML scalability<br />
<br />
2018
DML Protocol Gen 1 online<br />
<br />
2018
First DML Algo competition to grow and support developers’ community<br />
Release of DML Protocol Gen 1 beta<br />
<br />
2018
Release of DML Protocol Gen 1 alpha (decentralized machine learning on-device private data)<br />
Research of state channels for increasing DML scalability<br />
<br />
2018
DML Algo Marketplace online<br />
<br />
2018
Token Generation Event and Launch of DML Protocol Gen 0 (DML Algo Marketplace) Beta<br />
<br />
2018
Release of DML Protocol Gen 0 (DML Algo Marketplace) Prototype<br />
<br />
2017
Whitepaper published and DecentralizedML.com online<br />
<br />
2017
Idea generation of decentralization in algorithms<br />
<br />
2017
Development of proof of concept<br />
<br />
2017
Google published research blog in federated learning<br />
<br />
2017
Idea generation of decentralization in machine learning<br />
<br />
2016
AlphaGo beat Lee Sedol in Go<br />
<br />
2016
Google published the research paper on federated learning<br />
<br />

People

TEAM
Patrick Sum
System Security Engineer
Wilson Lau
Machine Learning Engineer
Jacky Chan
Blockchain and Software Developer
Michael Kwok
Project Lead Director
Victor Cheung
Blockchain Developer
Fabrice Fischer
Eric Byron
Eugene Tay
Jesmer Wong
Matthew Slipper
Steven Cody Reynolds
Scott Christensen
Kyle Wong
Roderik van der Graaf
Michael Edesess
Guillaume Huet
Pascal Lejolif

Legal

Incorporation

There is a registered company for this ICO

Country

Singapore

KYC

No

Crowdsale

  • Whitelist: No