Decentralized Machine Learning

Decentralized Machine Learning

Created using Figma
Created using Figma
Libérez des données privées inexploitées, une puissance de traitement inactive et des algorithmes externalisés
  • Marché
    Paire
    Prix
    Volume 24H
    24H (prix)
    24H (volume)
  • Hotbit
    DML/ETH il y a une heure
    $ 0.0004
    $ 10.376 K
    -0.65%
    -2.26%
  • DDEX
    DML/WETH % count% months ago
    $ 0.0133
    $ 14.53
    -
    -
  • Joyso
    DML/ETH % count% months ago
    $ 0.0345
    -
    -
    -
  • Idex
    DML/ETH % count% months ago
    $ 0.0008
    -
    -
    -
  • Bamboo Relay
    DML/WETH % count% months ago
    -
    -
    -
    -
mars, 2018
mars, 2018
100% terminé
$10 425 492
100% objectif terminé
past
Détails du jeton
Téléscripteur
DML
Détails de l'entreprise
Pays enregistré
Singapore
Détails supplémentaires
Liste blanche
Oui ,
Les catégories
Autre

Sur Decentralized Machine Learning

La domination des techniciens dans le paysage actuel de l’apprentissage automatique a entraîné une anticoncurrentielle et une allocation inégale des ressources. DML rend aux gens l'autonomie de l'apprentissage automatique et des données en décentralisant le développement des données, de la puissance de traitement et des algorithmes dans une infrastructure et un écosystème open source.

L’infrastructure DML appliquera les technologies d’apprentissage sur machine, de blockchain et d’apprentissage fédérées intégrées à l’appareil. Il libère une utilisation inexploitée des données sans extraction ni puissance de traitement inutilisée pour l’apprentissage automatique. Les algorithmes seront fournis par une communauté de développeurs sur le marché, ce qui résultera d’une innovation de la périphérie.

% name% roadmap

  • February 2016

  • Google published the research paper on federated learning
  • March 2016

  • AlphaGo beat Lee Sedol in Go
  • March 2017

  • Idea generation of decentralization in machine learning
  • April 2017

  • Google published research blog in federated learning
  • Lire la suite
  • May 2017

  • Development of proof of concept
  • September 2017

  • Idea generation of decentralization in algorithms
  • December 2017

  • Whitepaper published and DecentralizedML.com online
  • February 2018

  • Release of DML Protocol Gen 0 (DML Algo Marketplace) Prototype
  • April 2018

  • Token Generation Event and Launch of DML Protocol Gen 0 (DML Algo Marketplace) Beta
  • May 2018

  • DML Algo Marketplace online
  • June 2018

  • Release of DML Protocol Gen 1 alpha (decentralized machine learning on-device private data)
    Research of state channels for increasing DML scalability
  • July 2018

  • First DML Algo competition to grow and support developers’ community
    Release of DML Protocol Gen 1 beta
  • September 2018

  • DML Protocol Gen 1 online
  • December 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)
    Research of multi-chain support and interoperability
  • Q2 2019

  • DML Protocol Gen 2 online
  • 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)
  • September 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 2020

  • Release of DML Protocol Gen 4 beta (Support deployment of general applications)
  • Q4 2020

  • DML Protocol Gen 4 online

Activité

Suiveurs:
1 675
LOW
Tweets:
306
HIGH
Croissance de 30 jours:
-7

Decentralized Machine Learning Équipe

Vérifié 0%

Attention. Il y a un risque que les membres non vérifiés ne soient pas réellement membres de l'équipe

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

Conseillers

Vérifié 0%

Attention. Il y a un risque que les membres non vérifiés ne soient pas réellement membres de l'équipe

Guillaume Huet
Advisor
non vérifié
Michael Edesess
Advisor
non vérifié

3 ICO

$10 425 492

Roderik van der Graa...
Advisor
non vérifié

2 ICO

$10 425 492

Kyle Wong
Advisor
non vérifié
Scott Christensen
Advisor
non vérifié

2 ICO

$100 425 492

Steven Cody Reynolds
Advisor
non vérifié
$ 0.0004
-3.08%
Coin Stats
Daily, %:
-3.08%
Weekly, %:
-8.84%
Monthly, %:
-69.85%
Market Info
Market Cap:
Volume 24h:
$ 10.376 K
Circ. Supply:
0 DML
Ticker:
DML

% nom%

icocrunch.io
review

It’s predicted that by 2020 the machine learning industries revenue will exceed $210 billion. Many IT market monsters as Microsoft, Amazon, and Google invest hugely into development of the machine learning technology. Returning to the story about the Go match, the AlphaGo program was developed by Google DeepMind. The idea of DML to create an open source decentralized platform to encourage developers to contribute into the machine learning technology will definitely accelerate innovations in this sphere and give businesses both brand-new and improved algorithms. DML has already made the first important step to the goal – they’ve launched a working prototype of their DML Protocol. The idea is straightforward, the hype behind the machine learning technology is huge, and the team is excellent. All in all, the project is very promising and is definitely worth your attention.
A strong project standing a step ahead of its competitors and aiming to put the machine learning technology on a decentralized basement.

Lire la suite
Ian Balina

Decentralized Machine Learning (DML) is an interesting project, but development is still very early. I think it would be better if they waited until having a testnet to do an ICO. Not looking to fund research/development phase of projects right now, especially during ICO winter.

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DiddyCarter
B+

Decentralized machine learning. Looks good. need proof of care to get higher allocations

Lire la suite
Coin Bloq

DML wants to build a decentralized machine learning protocol that harnesses the idol processing power of users devices for AI training and modeling while protecting users data.
The team have actually collaborated and worked on well-known projects in the blockchain space.
Finally the DML project has a video showcasing the prototype in action with use of algorithm, marketplace and the DML application. It is concern whether people are ready to submit their data over to DML and other third parties, and finally the success of DML AI training protocol actually hinges on the number of users running the DML app.
I actually gave them 4 out of 10 for hype, I think this is definitely under the radar. When it comes for the team I think they have a very strong and capable team, actually gave them 7.5 out of 10.
For the token economics I am very bullish I gave them 7.5 out of 10 and that’s for two reasons on the hard cap is set at only 28,000 ETH, which I think is great under the current market and the whitelisted participants are only going to be getting 10% bonus.

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Crypto Briefing
75%

DML offers a product with the potential to unlock a huge source of value for developers, enterprises and users. Compared to other machine learning solutions that focus exclusively on incentivizing developers, DML have designed a more comprehensive and inclusive ecosystem.
Of course, the success of that ecosystem will ultimately depend on user adoption, which remains the big question at the moment.

Lire la suite
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